diff --git a/.github/push_templates_to_algolia.ipynb b/.github/push_templates_to_algolia.ipynb index edc094b22e..6b490b2e56 100644 --- a/.github/push_templates_to_algolia.ipynb +++ b/.github/push_templates_to_algolia.ipynb @@ -54,10 +54,10 @@ "id": "aa0e3e6f-1260-4452-8abf-7c084e26c8a4", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:53.135222Z", - "iopub.status.busy": "2023-09-27T12:04:53.134838Z", - "iopub.status.idle": "2023-09-27T12:04:53.192987Z", - "shell.execute_reply": "2023-09-27T12:04:53.192317Z" + "iopub.execute_input": "2023-09-27T12:39:15.190965Z", + "iopub.status.busy": "2023-09-27T12:39:15.190304Z", + "iopub.status.idle": "2023-09-27T12:39:15.248496Z", + "shell.execute_reply": "2023-09-27T12:39:15.247769Z" }, "papermill": {}, "tags": [] @@ -95,10 +95,10 @@ "id": "cfa97168-63eb-4e8c-89c3-0a5d26f47740", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:53.196574Z", - "iopub.status.busy": "2023-09-27T12:04:53.196346Z", - "iopub.status.idle": "2023-09-27T12:04:53.201271Z", - "shell.execute_reply": "2023-09-27T12:04:53.200655Z" + "iopub.execute_input": "2023-09-27T12:39:15.252481Z", + "iopub.status.busy": "2023-09-27T12:39:15.251865Z", + "iopub.status.idle": "2023-09-27T12:39:15.255953Z", + "shell.execute_reply": "2023-09-27T12:39:15.255289Z" }, "papermill": {}, "tags": [] @@ -141,10 +141,10 @@ "id": "7a9c86c2-931d-4113-abbc-31b3f517b6c4", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:53.204594Z", - "iopub.status.busy": "2023-09-27T12:04:53.204182Z", - "iopub.status.idle": "2023-09-27T12:04:53.219707Z", - "shell.execute_reply": "2023-09-27T12:04:53.218973Z" + "iopub.execute_input": "2023-09-27T12:39:15.259365Z", + "iopub.status.busy": "2023-09-27T12:39:15.258798Z", + "iopub.status.idle": "2023-09-27T12:39:15.274861Z", + "shell.execute_reply": "2023-09-27T12:39:15.274038Z" }, "tags": [] }, @@ -178,10 +178,10 @@ "id": "c50e96b2-4403-413c-a99a-9243be0c0a04", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:53.222782Z", - "iopub.status.busy": "2023-09-27T12:04:53.222343Z", - "iopub.status.idle": "2023-09-27T12:04:53.982327Z", - "shell.execute_reply": "2023-09-27T12:04:53.981475Z" + "iopub.execute_input": "2023-09-27T12:39:15.278355Z", + "iopub.status.busy": "2023-09-27T12:39:15.277781Z", + "iopub.status.idle": "2023-09-27T12:39:16.158199Z", + "shell.execute_reply": "2023-09-27T12:39:16.157464Z" }, "tags": [] }, @@ -230,10 +230,10 @@ "id": "da661ba3-fd15-4abc-bd4f-d13ae77b82b0", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:53.986249Z", - "iopub.status.busy": "2023-09-27T12:04:53.985785Z", - "iopub.status.idle": "2023-09-27T12:04:55.030778Z", - "shell.execute_reply": "2023-09-27T12:04:55.029882Z" + "iopub.execute_input": "2023-09-27T12:39:16.161924Z", + "iopub.status.busy": "2023-09-27T12:39:16.161520Z", + "iopub.status.idle": "2023-09-27T12:39:17.111412Z", + "shell.execute_reply": "2023-09-27T12:39:17.110673Z" }, "tags": [] }, @@ -260,10 +260,10 @@ "id": "f1482a8f-4ce5-4e04-93c8-ddd883375d67", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:55.034288Z", - "iopub.status.busy": "2023-09-27T12:04:55.033833Z", - "iopub.status.idle": "2023-09-27T12:04:55.051488Z", - "shell.execute_reply": "2023-09-27T12:04:55.050831Z" + "iopub.execute_input": "2023-09-27T12:39:17.115092Z", + "iopub.status.busy": "2023-09-27T12:39:17.114598Z", + "iopub.status.idle": "2023-09-27T12:39:17.132336Z", + "shell.execute_reply": "2023-09-27T12:39:17.131782Z" }, "tags": [] }, diff --git a/LangChain/LangChain_Vector_Search_on_PDF.ipynb b/LangChain/LangChain_Vector_Search_on_PDF.ipynb index f6e25ed743..d7a5a4de7f 100644 --- a/LangChain/LangChain_Vector_Search_on_PDF.ipynb +++ b/LangChain/LangChain_Vector_Search_on_PDF.ipynb @@ -27,16 +27,16 @@ }, "source": [ "# LangChain - Vector Search on PDF\n", - "\n", - "\n", - "\n", - "

Template request | Bug report" + "

Give Feedback | Bug report" ] }, { "cell_type": "markdown", "id": "religious-programmer", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "**Tags:** #langchain #pdf #weaviate #huggingface #llm #database #embeddings" ] @@ -44,7 +44,10 @@ { "cell_type": "markdown", "id": "1fe9f56e-561c-4f52-aef8-b861c9462107", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "**Author:** [Sriniketh Jayasendil](https://www.linkedin.com/in/sriniketh-jayasendil)" ] @@ -63,7 +66,10 @@ { "cell_type": "markdown", "id": "31ea7cdb-e10d-43fc-b026-f69249a59736", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "**Description:** This notebook is used to perform vector search on your PDF and it will answer basic questions that are closely related based on the prompt provided.\n", "\n", @@ -81,7 +87,10 @@ { "cell_type": "markdown", "id": "1a14806c-9da2-446e-b8fd-b55f8d7ac3f0", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "**References:**\n", "- [Langchain docs](https://python.langchain.com/docs/get_started/introduction.html)\n", @@ -103,7 +112,10 @@ { "cell_type": "markdown", "id": "numeric-mediterranean", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "### Import libraries" ] @@ -113,6 +125,7 @@ "execution_count": null, "id": "potential-surfing", "metadata": { + "papermill": {}, "tags": [] }, "outputs": [], @@ -148,7 +161,10 @@ { "cell_type": "markdown", "id": "64db5ac5-046f-4203-8503-990002927075", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "### Setup variables\n", "- `pdf_file`: Path to which the PDF file exists.\",\n", @@ -162,6 +178,7 @@ "execution_count": null, "id": "continuous-melbourne", "metadata": { + "papermill": {}, "tags": [] }, "outputs": [], @@ -175,7 +192,10 @@ { "cell_type": "markdown", "id": "registered-showcase", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "## Model" ] @@ -183,7 +203,10 @@ { "cell_type": "markdown", "id": "8ae9725c-161a-47f6-a115-7d74cee3bd2f", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "### Setup environ" ] @@ -193,6 +216,7 @@ "execution_count": null, "id": "bd067008-9cf1-45b1-a6d1-c37627dc4976", "metadata": { + "papermill": {}, "tags": [] }, "outputs": [], @@ -203,7 +227,10 @@ { "cell_type": "markdown", "id": "tested-astrology", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "### Extract text from PDF" ] @@ -237,7 +264,10 @@ { "cell_type": "markdown", "id": "8daa42c1-3a2b-4f96-a7dd-fb1deb395a84", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "### Split the text into chunks scraped from the PDF" ] @@ -267,7 +297,10 @@ { "cell_type": "markdown", "id": "ef1720bf-a28a-4757-b189-7df97947c158", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "### Create embeddings of the text make it compatible to store it in the database" ] @@ -277,6 +310,7 @@ "execution_count": null, "id": "e4a376ac-a10e-4d6a-ba01-e5445efdf091", "metadata": { + "papermill": {}, "tags": [] }, "outputs": [], @@ -290,7 +324,10 @@ { "cell_type": "markdown", "id": "4169feb2-05ac-4914-bbb2-501dae7dcd89", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "### Store the embeddings into the weaviate database" ] @@ -300,6 +337,7 @@ "execution_count": null, "id": "6922b1d4-e394-493a-8549-07ba3c947e7d", "metadata": { + "papermill": {}, "tags": [] }, "outputs": [], @@ -311,7 +349,10 @@ { "cell_type": "markdown", "id": "981fac74-2e1e-4b62-8b91-09d51d344bba", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "### Get the closest response to the user query on the PDF" ] @@ -321,6 +362,7 @@ "execution_count": null, "id": "bdf9e7a9-7de9-4c50-b677-97cb2a1d5d3b", "metadata": { + "papermill": {}, "tags": [] }, "outputs": [], @@ -339,7 +381,9 @@ "iopub.status.idle": "2021-07-02T23:32:10.796900Z", "shell.execute_reply": "2021-07-02T23:32:10.796358Z", "shell.execute_reply.started": "2021-07-02T23:32:10.789033Z" - } + }, + "papermill": {}, + "tags": [] }, "source": [ "## Output" @@ -348,7 +392,10 @@ { "cell_type": "markdown", "id": "890f7c86-b7bb-4f5d-9a1b-e492dd9580fd", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "source": [ "### Show the response" ] @@ -358,6 +405,7 @@ "execution_count": null, "id": "9c4e3b7b-6440-4844-8054-265f1aec65eb", "metadata": { + "papermill": {}, "tags": [] }, "outputs": [], @@ -370,7 +418,10 @@ "cell_type": "code", "execution_count": null, "id": "5e2bc7f1-acf9-402b-b0aa-93de14764f8b", - "metadata": {}, + "metadata": { + "papermill": {}, + "tags": [] + }, "outputs": [], "source": [] } @@ -393,6 +444,10 @@ "pygments_lexer": "ipython3", "version": "3.9.6" }, + "naas": { + "notebook_id": "327f0a8a8dfb334ce84fe3443964d4f1607c5346b593742909d57a379024620f", + "notebook_path": "LangChain/LangChain_Vector_Search_on_PDF.ipynb" + }, "papermill": { "default_parameters": {}, "environment_variables": {}, @@ -409,4 +464,4 @@ }, "nbformat": 4, "nbformat_minor": 5 -} +} \ No newline at end of file diff --git a/README.md b/README.md index 06b9a2dd3e..1786d3303b 100644 --- a/README.md +++ b/README.md @@ -608,6 +608,7 @@ We are committed to sharing templates and giving shout outs to the contributors * [Gmail Toolkit](https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_Gmail_Toolkit.ipynb) * [JSON Agent](https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_JSON_Agent.ipynb) * [Pandas Dataframe Agent](https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_Pandas_Dataframe_Agent.ipynb) +* [Vector Search on PDF](https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_Vector_Search_on_PDF.ipynb) ## LeFigaro * [House Price analysis](https://github.com/jupyter-naas/awesome-notebooks/blob/master/LeFigaro/LeFigaro_House_Price_analysis.ipynb) diff --git a/generate_readme.ipynb b/generate_readme.ipynb index 753ed6e98b..788a746e63 100644 --- a/generate_readme.ipynb +++ b/generate_readme.ipynb @@ -41,10 +41,10 @@ "id": "sitting-directory", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:41.952223Z", - "iopub.status.busy": "2023-09-27T12:04:41.951737Z", - "iopub.status.idle": "2023-09-27T12:04:45.122807Z", - "shell.execute_reply": "2023-09-27T12:04:45.121967Z" + "iopub.execute_input": "2023-09-27T12:39:04.002201Z", + "iopub.status.busy": "2023-09-27T12:39:04.001752Z", + "iopub.status.idle": "2023-09-27T12:39:07.196823Z", + "shell.execute_reply": "2023-09-27T12:39:07.195991Z" }, "tags": [] }, @@ -94,10 +94,10 @@ "id": "guided-edgar", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:45.128187Z", - "iopub.status.busy": "2023-09-27T12:04:45.126561Z", - "iopub.status.idle": "2023-09-27T12:04:45.133096Z", - "shell.execute_reply": "2023-09-27T12:04:45.132475Z" + "iopub.execute_input": "2023-09-27T12:39:07.201150Z", + "iopub.status.busy": "2023-09-27T12:39:07.200498Z", + "iopub.status.idle": "2023-09-27T12:39:07.206010Z", + "shell.execute_reply": "2023-09-27T12:39:07.205391Z" }, "tags": [] }, @@ -140,10 +140,10 @@ "id": "36c9011e-5f51-4779-8062-a627503100e1", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:45.136499Z", - "iopub.status.busy": "2023-09-27T12:04:45.135965Z", - "iopub.status.idle": "2023-09-27T12:04:45.395379Z", - "shell.execute_reply": "2023-09-27T12:04:45.394514Z" + "iopub.execute_input": "2023-09-27T12:39:07.209558Z", + "iopub.status.busy": "2023-09-27T12:39:07.208984Z", + "iopub.status.idle": "2023-09-27T12:39:07.433531Z", + "shell.execute_reply": "2023-09-27T12:39:07.432728Z" }, "tags": [] }, @@ -211,10 +211,10 @@ "id": "7fa60d66-a43a-4ba3-abfb-ee1779afdfc3", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:45.399046Z", - "iopub.status.busy": "2023-09-27T12:04:45.398519Z", - "iopub.status.idle": "2023-09-27T12:04:45.404187Z", - "shell.execute_reply": "2023-09-27T12:04:45.403545Z" + "iopub.execute_input": "2023-09-27T12:39:07.437267Z", + "iopub.status.busy": "2023-09-27T12:39:07.436650Z", + "iopub.status.idle": "2023-09-27T12:39:07.441196Z", + "shell.execute_reply": "2023-09-27T12:39:07.440478Z" }, "tags": [] }, @@ -251,10 +251,10 @@ "id": "f9a4c7b2-d667-4555-98ed-31786278e947", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:45.407960Z", - "iopub.status.busy": "2023-09-27T12:04:45.407577Z", - "iopub.status.idle": "2023-09-27T12:04:45.424909Z", - "shell.execute_reply": "2023-09-27T12:04:45.424271Z" + "iopub.execute_input": "2023-09-27T12:39:07.444502Z", + "iopub.status.busy": "2023-09-27T12:39:07.444043Z", + "iopub.status.idle": "2023-09-27T12:39:07.461507Z", + "shell.execute_reply": "2023-09-27T12:39:07.460806Z" }, "tags": [] }, @@ -386,10 +386,10 @@ "id": "9f21cfbb-2bcc-4bca-81a4-fad14b081371", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:45.428529Z", - "iopub.status.busy": "2023-09-27T12:04:45.428085Z", - "iopub.status.idle": "2023-09-27T12:04:45.435120Z", - "shell.execute_reply": "2023-09-27T12:04:45.434444Z" + "iopub.execute_input": "2023-09-27T12:39:07.464728Z", + "iopub.status.busy": "2023-09-27T12:39:07.464281Z", + "iopub.status.idle": "2023-09-27T12:39:07.472548Z", + "shell.execute_reply": "2023-09-27T12:39:07.471952Z" }, "tags": [] }, @@ -479,10 +479,10 @@ "id": "94dcc3bd-07e2-48a3-bf81-a327e940a934", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:45.438455Z", - "iopub.status.busy": "2023-09-27T12:04:45.438020Z", - "iopub.status.idle": "2023-09-27T12:04:45.443261Z", - "shell.execute_reply": "2023-09-27T12:04:45.442666Z" + "iopub.execute_input": "2023-09-27T12:39:07.475986Z", + "iopub.status.busy": "2023-09-27T12:39:07.475539Z", + "iopub.status.idle": "2023-09-27T12:39:07.480510Z", + "shell.execute_reply": "2023-09-27T12:39:07.479854Z" }, "tags": [] }, @@ -521,10 +521,10 @@ "id": "e45fc17e-ba5a-4317-92b3-f6de4c1a0bde", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:45.446425Z", - "iopub.status.busy": "2023-09-27T12:04:45.445899Z", - "iopub.status.idle": "2023-09-27T12:04:48.504678Z", - "shell.execute_reply": "2023-09-27T12:04:48.503988Z" + "iopub.execute_input": "2023-09-27T12:39:07.483934Z", + "iopub.status.busy": "2023-09-27T12:39:07.483367Z", + "iopub.status.idle": "2023-09-27T12:39:10.533825Z", + "shell.execute_reply": "2023-09-27T12:39:10.533150Z" }, "tags": [] }, @@ -624,10 +624,10 @@ "id": "younger-consensus", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:48.508548Z", - "iopub.status.busy": "2023-09-27T12:04:48.507948Z", - "iopub.status.idle": "2023-09-27T12:04:48.514108Z", - "shell.execute_reply": "2023-09-27T12:04:48.513446Z" + "iopub.execute_input": "2023-09-27T12:39:10.537399Z", + "iopub.status.busy": "2023-09-27T12:39:10.536741Z", + "iopub.status.idle": "2023-09-27T12:39:10.543567Z", + "shell.execute_reply": "2023-09-27T12:39:10.542822Z" }, "tags": [] }, @@ -661,10 +661,10 @@ "id": "2a95cba3-027c-4a57-8bfa-2ee1e9053bb7", "metadata": { "execution": { - "iopub.execute_input": "2023-09-27T12:04:48.517204Z", - "iopub.status.busy": "2023-09-27T12:04:48.516961Z", - "iopub.status.idle": "2023-09-27T12:04:48.555486Z", - "shell.execute_reply": "2023-09-27T12:04:48.554712Z" + "iopub.execute_input": "2023-09-27T12:39:10.546880Z", + "iopub.status.busy": "2023-09-27T12:39:10.546311Z", + "iopub.status.idle": "2023-09-27T12:39:10.583681Z", + "shell.execute_reply": "2023-09-27T12:39:10.582906Z" }, "tags": [] }, diff --git a/templates.json b/templates.json index f57536c484..8d34b7fd32 100644 --- a/templates.json +++ b/templates.json @@ -1 +1 @@ -[{"objectID": "3e342697d70a5fc4884c84d82b7b2d1efc9f8dde26b142ec2e63c2246dbfd05b", "tool": "AWS", "notebook": "Daily biling notification to slack", "action": "", "tags": ["#aws", "#cloud", "#storage", "#S3bucket", "#slack", "#operations", "#automation"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2021-09-14", "description": "This notebook sends a daily notification to a Slack channel with the billing information from an AWS account. It allows users to easily keep track of their AWS spending.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AWS/AWS_Daily_biling_notification_to_slack.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AWS/AWS_Daily_biling_notification_to_slack.ipynb", "imports": ["datetime", "boto3", "naas", "dateutil.relativedelta", "pandas", "naas_drivers"], "image_url": ""}, {"objectID": "e5cc5c59cca0de48fbaf2a7d65708d416a50968635cadc60e18a669fd52c075a", "tool": "AWS", "notebook": "Get files from S3 bucket", "action": "", "tags": ["#aws", "#cloud", "#storage", "#S3bucket", "#operations", "#snippet", "#url"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2021-09-20", "description": "This notebook provides a step-by-step guide to retrieving files from an Amazon Web Services (AWS) S3 bucket, allowing users to easily access their data stored in the cloud.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AWS/AWS_Get_files_from_S3_bucket.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AWS/AWS_Get_files_from_S3_bucket.ipynb", "imports": ["boto3"], "image_url": ""}, {"objectID": "db1e517c78d01b715869cb9f08c6c818cd09715bf0134dd92c4440869d176e77", "tool": "AWS", "notebook": "Read dataframe from S3", "action": "", "tags": ["#aws", "#cloud", "#storage", "#S3bucket", "#operations", "#snippet", "#dataframe"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-04-28", "description": "This notebook demonstrates how to read a dataframe from an Amazon Web Services (AWS) Simple Storage Service (S3) bucket.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AWS/AWS_Read_dataframe_from_S3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AWS/AWS_Read_dataframe_from_S3.ipynb", "imports": ["awswrangler", "awswrangler"], "image_url": ""}, {"objectID": "0d5fe4330975af3c53c528f914bd8d0124c25dea14afe09df1119b430a9bb2b2", "tool": "AWS", "notebook": "Send dataframe to S3", "action": "", "tags": ["#aws", "#cloud", "#storage", "#S3bucket", "#operations", "#snippet", "#dataframe"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-04-28", "description": "This notebook demonstrates how to use AWS to send a dataframe to an S3 bucket.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AWS/AWS_Send_dataframe_to_S3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AWS/AWS_Send_dataframe_to_S3.ipynb", "imports": ["awswrangler", "awswrangler", "pandas", "datetime.date"], "image_url": ""}, {"objectID": "f5955b1a7c1209b77d470bfeb5eb20bcdf6ecf7fcba22a304dd0ea03164a0539", "tool": "AWS", "notebook": "Upload file to S3 bucket", "action": "", "tags": ["#aws", "#cloud", "#storage", "#S3bucket", "#snippet", "#operations", "#AWS - Upload file to S3 bucket"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2021-08-03", "description": "This notebook provides instructions on how to upload a file to an Amazon Web Services (AWS) S3 bucket, allowing for secure storage and easy access to the file. It is a simple and efficient way to store and manage data in the cloud.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AWS/AWS_Upload_file_to_S3_bucket.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AWS/AWS_Upload_file_to_S3_bucket.ipynb", "imports": ["boto3", "boto3"], "image_url": ""}, {"objectID": "5916af637e577797931145d971b180db20f2a1d595fec71b99bc547da2ee8dbd", "tool": "Abstract API", "notebook": "Check Email Validation", "action": "", "tags": ["#abstractapi", "#email", "#validation", "#api", "#check", "#tester"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-23", "description": "This notebook will demonstrate how to use Abstract API to check if an email is valid.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Abstract%20API/Abstract_API_Check_Email_Validation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Abstract%20API/Abstract_API_Check_Email_Validation.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "8d77689e05cc016ea0eed7a995b0ef55adc9998684802cc44b3cccf702baed41", "tool": "Abstract API", "notebook": "Get IP Geolocation", "action": "", "tags": ["#api", "#abstract-api", "#ip", "#geolocation", "#stream", "#multithread", "#queues", "#operations", "#dataprocessing", "#automation"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook provides a way to get the geolocation of an IP address using the AbstractAPI service.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Abstract%20API/Abstract_API_Get_IP_Geolocation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Abstract%20API/Abstract_API_Get_IP_Geolocation.ipynb", "imports": ["threading", "queue", "time", "requests", "pandas", "json", "ratelimiter.RateLimiter", "ratelimiter.RateLimiter"], "image_url": ""}, {"objectID": "1fc79d1caf15ef3a1adf0874fa85f6a8b05e172f5e45f0fc6ce7ee40e5c54cae", "tool": "Advertools", "notebook": "Analyze website content using XML sitemap", "action": "", "tags": ["#advertools", "#xml", "#sitemap", "#website", "#analyze", "#seo"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-05-23", "created_at": "2023-05-09", "description": "This notebook helps you get an overview of a website's content by analyzing and visualizing its XML sitemap. It's also an important SEO audit process that can uncover some potential issues that might affect the website.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Analyze_website_content_using_XML_sitemap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Analyze_website_content_using_XML_sitemap.ipynb", "imports": ["advertools", "adviz", "urllib.parse.urlsplit", "IPython.display.display"], "image_url": ""}, {"objectID": "2733269de8aa4a8a013af03ae7af3ac21d9d860849af4b06adb3b31fbfc13ad2", "tool": "Advertools", "notebook": "Audit robots txt and xml sitemap issues", "action": "", "tags": ["#advertools", "#xml", "#sitemap", "#website", "#audit", "#seo", "#robots.txt", "#google"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-05-30", "created_at": "2023-05-29", "description": "This notebook helps you check if there are any conflicts between robots.txt rules and your XML sitemap.\n\n* Are you disallowing URLs that you shouldn't?\n* Test and make sure you don't publish new pages with such conflicts.\n* Do this in bulk: for all URL/rule/user-agent combinations run all tests with one command.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Audit_robots_txt_and_xml_sitemap_issues.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Audit_robots_txt_and_xml_sitemap_issues.ipynb", "imports": ["advertools"], "image_url": ""}, {"objectID": "65fcbc3f91ea08c6a2feb69f5b9f702c91e1da37e5faa0f20f1b1d19f85ade58", "tool": "Advertools", "notebook": "Check status code and Send report by email", "action": "", "tags": ["#advertools", "#website", "#analyze", "#audit", "#seo", "#status_code", "#response_headers", "#naas", "#notification", "#scheduler"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook runs an automated status code checker with response headers using the HTTP `HEAD` method and send a report by email.\n\nNB:\n* Bulk and concurrent checking of status codes for a known list of URLs\n* Get all available response headers from all URLs\n* Set speed, number of concurent request and various other crawling options\n* Does NOT download the full HTML of a page, saving a lot of time, energy, and resources, and enabling an extreemely fast and light process", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Check_status_code_and_Send_notifications.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Check_status_code_and_Send_notifications.ipynb", "imports": ["advertools", "advertools", "datetime.datetime", "naas", "naas_drivers.emailbuilder", "plotly.express", "pandas"], "image_url": ""}, {"objectID": "3c5612a68165853c27d59d0068f4ee37bc3ca2172bb0a1383abe8544664b9524", "tool": "Advertools", "notebook": "Check status code in bulk", "action": "", "tags": ["#advertools", "#adviz", "#website", "#analyze", "#audit", "#seo", "#status_code", "#response_headers"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook runs an automated status code checker with response headers using the HTTP `HEAD` method.\n\n* Bulk and concurrent checking of status codes for a known list of URLs\n* Get all available response headers from all URLs\n* Set speed, number of concurent request and various other crawling options\n* Does NOT download the full HTML of a page, saving a lot of time, energy, and resources, and enabling an extreemely fast and light process", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Check_status_code_in_bulk.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Check_status_code_in_bulk.ipynb", "imports": ["adviz", "adviz", "advertools", "advertools", "datetime.datetime", "plotly.express", "pandas", "IPython.display.display"], "image_url": ""}, {"objectID": "09c6603c1e23892e966a1e1a19a577d94d56c38695e3e2ca640728e81024f848", "tool": "Advertools", "notebook": "Check website pages status code", "action": "", "tags": ["#advertools", "#website", "#status", "#code", "#check", "#pages"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-04", "created_at": "2023-08-04", "description": "This notebook crawls your website and checks the status code of all pages. It starts from the home page and discovers URLs by following links within the website. It is a useful tool for quickly checking the status of your website and generating a report to take necessary actions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Check_website_pages_status_code.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Check_website_pages_status_code.ipynb", "imports": ["advertools", "advertools", "datetime.datetime", "naas", "naas_drivers.emailbuilder, naasauth", "plotly.express", "pandas", "adviz", "adviz", "os"], "image_url": ""}, {"objectID": "1b68edcb30da94c5c5b1f9eece671a36a1cc832aa557bd6302f2b647aac96ba7", "tool": "Advertools", "notebook": "Crawling a website", "action": "", "tags": ["#advertools", "#adviz", "#crawling", "#website", "#analyze", "#seo", "#URL", "#audit", "#scraping", "#scrapy"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-07-20", "created_at": "2023-07-20", "description": "This notebook demonstrates how to crawl a website, starting with one of its pages, and discover and follow all links as well.\n\n* Convert a website to a CSV file\n* Follow links with certain conditions:\n * Whether or not a link matches a certain regex\n * Whether or not a link contains a certain query parameter(s)\n* Extract special elements from pages using CSS/XPath selectors\n* Manage your crawling process with advanced settings (number of concurrent requests, when to stop crawling, proxies, and much more)", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Crawl_a_website.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Crawl_a_website.ipynb", "imports": ["advertools", "advertools", "pandas"], "image_url": ""}, {"objectID": "5fc4529ca8156fe747658753b23728aa1f18141cf3f39703276b7fa6f028e7a6", "tool": "Advertools", "notebook": "Visualize status codes OK and KO", "action": "", "tags": ["#advertools", "#adviz", "#status_code", "#asset", "#plotly", "#naas"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-07-20", "created_at": "2023-07-20", "description": "This notebook creates a plotly treemap to visualize status code OK and KO from list.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Visualize_status_codes_OK_KO.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Visualize_status_codes_OK_KO.ipynb", "imports": ["adviz", "adviz", "naas"], "image_url": ""}, {"objectID": "b81f17379adfb8f806c07e73b25c89b733a11511e8fbf04be7cd54b6faa5ceac", "tool": "Advertools", "notebook": "Visualize status codes count", "action": "", "tags": ["#advertools", "#adviz", "#status_code", "#asset", "#plotly", "#naas"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-07-20", "created_at": "2023-07-20", "description": "This notebook creates a chat to visualize status code count.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Visualize_status_codes_count.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Visualize_status_codes_count.ipynb", "imports": ["adviz", "adviz", "naas"], "image_url": ""}, {"objectID": "3d3224a30d88e19593b49386c00bef0933deb4e3cbc16d8e9da64a102989a235", "tool": "Affinity", "notebook": "Sync with Notion database", "action": "", "tags": ["#automation", "#notification", "#Affinity", "#Notion"], "author": "Maxime Jublou", "author_url": "https://linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-05-18", "description": "This notebook allows users to easily sync their Notion database with their Affinity account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Affinity/Affinity_Sync_with_Notion_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Affinity/Affinity_Sync_with_Notion_database.ipynb", "imports": ["naas", "rich.print", "pandas", "pandas.DataFrame", "naas_drivers.notion", "notion_client.APIResponseError", "requests", "pydash", "requests.auth.HTTPBasicAuth", "string.Template"], "image_url": ""}, {"objectID": "fde19b055488d7f318ec541fd38a5195fe025974bb22c1cb2fbf869fbb2ac7c6", "tool": "Agicap", "notebook": "Export treasury plan", "action": "", "tags": ["#agicap", "#treasury", "#export", "#plan", "#finance", "#data", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-27", "created_at": "2023-04-26", "description": "This notebook will export the Excel treasury plan consolidated by month from Agicap and return a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Export_treasury_plan.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Export_treasury_plan.ipynb", "imports": ["requests", "naas", "pandas", "datetime.datetime", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "6e8192ab022b4bd38167bcad47bf5361f21f97d197b712c9c324fbc22e34c1a3", "tool": "Agicap", "notebook": "Export treasury plan by account", "action": "", "tags": ["#agicap", "#treasury", "#export", "#plan", "#finance", "#data", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-27", "created_at": "2023-04-27", "description": "This notebook will export the Excel treasury plan by account by month from Agicap and return a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Export_treasury_plan_by_account.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Export_treasury_plan_by_account.ipynb", "imports": ["requests", "naas", "pandas", "datetime.datetime", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "60ccdeaf932ef6f8fca9165c7451786434f49f667476e71971ae5eec00a549ea", "tool": "Agicap", "notebook": "Get banks accounts from company", "action": "", "tags": ["#agicap", "#bankaccount", "#company", "#finance", "#data", "#api"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-12", "created_at": "2023-07-12", "description": "This notebook will show how to get bank account from a company using Agicap API. It is usefull for organizations to quickly get the bank account of a company.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Get_banks_accounts_from_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Get_banks_accounts_from_company.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "71d55f60d4a6651a4020659b3bfa10cdbb7140d2eecf5287e21df984c3870670", "tool": "Agicap", "notebook": "Get inflow categories from company", "action": "", "tags": ["#agicap", "#categories", "#company", "#data", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-12", "created_at": "2023-07-12", "description": "This notebook will get inflow categories from a company in Agicap and return a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Get_inflow_categories_from_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Get_inflow_categories_from_company.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "00feab61f04c827086dcafd75d0532814272be3ecbef5608861024364dd1d02a", "tool": "Agicap", "notebook": "Get outflow categories from company", "action": "", "tags": ["#agicap", "#categories", "#company", "#data", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-12", "created_at": "2023-07-12", "description": "This notebook will get outflow categories from a company in Agicap and return a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Get_outflow_categories_from_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Get_outflow_categories_from_company.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "3d1b2dd49f1d4066bac81a72f725227fdfce1e44d69e304ec9dfae39cbfdbe4d", "tool": "Agicap", "notebook": "Get transactions by account", "action": "", "tags": ["#agicap", "#forecast", "#company", "#data", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-18", "created_at": "2023-09-18", "description": "This notebook is designed to retrieve all transactions for a specified company and account from Agicap. It will then organize this data into a structured DataFrame for easy analysis. \nThe DataFrame returned contains the following columns:\n- 'ENTREPRISE_ID': This column represents the unique identifier of the company.\n- 'COMPTE_ID': This column indicates the specific account ID related to the transaction.\n- 'TRANSACTION_ID': This column holds the unique transaction ID.\n- 'TRANSACTION_NAME': This column contains the name or description of the transaction.\n- 'CATEGORY_ID': This column represents the unique identifier of the transaction category.\n- 'CATEGORY_NAME': This column contains the name of the transaction category.\n- 'PROJECTS': This column is intended for any project-related information linked with the transaction.\n- 'CURRENCY': This column indicates the currency in which the transaction was made.\n- 'DATE_ORDER': This column holds the order date of the transaction in Unix timestamp format.\n- 'DATE': This column contains the date of the transaction in 'DD/MM/YYYY' format.\n- 'VALUE': This column represents the monetary value of the transaction.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Get_transactions_by_account.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Get_transactions_by_account.ipynb", "imports": ["requests", "naas", "pandas", "json"], "image_url": ""}, {"objectID": "5b0eeb327eb1d95fe850ad247b10ac8fb597a92887acf64a29dc564086e889e4", "tool": "Agicap", "notebook": "List companies", "action": "", "tags": ["#agicap", "#companies", "#accountingsoftware", "#financialmanagement", "#businessmanagement", "#financetracking", "#budgetplanning", "#invoicing", "#expensetracking", "#businessinsights", "#dataanalysis"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-10", "description": "This notebook lists all the companies within Agicap with their IDs. Agicap is a powerful accounting software for managing your company's finances. It offers features such as expense tracking, budget planning, invoicing, and data analysis to help you make informed business decisions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_List_companies.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_List_companies.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "32269a4228bf817ab1b2d51b7a5771d41e0381627b8e07487e9c7afa0ee0bf37", "tool": "Airtable", "notebook": "Delete data", "action": "", "tags": ["#airtable", "#database", "#productivity", "#spreadsheet", "#naas_drivers", "#operations", "#snippet", "#text"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides instructions on how to delete data from an Airtable database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Airtable/Airtable_Delete_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Airtable/Airtable_Delete_data.ipynb", "imports": ["naas_drivers.airtable"], "image_url": ""}, {"objectID": "f93453cccd04f72d5ec42afc790f102a05e6695c5b7d46347e25d1ac9bd3e67c", "tool": "Airtable", "notebook": "Get data", "action": "", "tags": ["#airtable", "#database", "#productivity", "#spreadsheet", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides an introduction to Airtable, a cloud-based database platform that allows users to easily access and manage data. It provides step-by-step instructions on how to get data from Airtable into a notebook for further analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Airtable/Airtable_Get_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Airtable/Airtable_Get_data.ipynb", "imports": ["naas_drivers.airtable"], "image_url": ""}, {"objectID": "718782ca423ea8e69fc7a4d05b5a28ebecc61ce558bff968d6466fe6279c0e3a", "tool": "Airtable", "notebook": "Insert data", "action": "", "tags": ["#airtable", "#database", "#productivity", "#spreadsheet", "#naas_drivers", "#operations", "#snippet", "#text"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides a step-by-step guide on how to insert data into an Airtable database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Airtable/Airtable_Insert_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Airtable/Airtable_Insert_data.ipynb", "imports": ["naas_drivers.airtable"], "image_url": ""}, {"objectID": "8f01544918dbd4ddadf8d4079fc2e2b7eee3af9b45a3baa3af433f2404df5bb2", "tool": "Airtable", "notebook": "Search data", "action": "", "tags": ["#airtable", "#database", "#productivity", "#spreadsheet", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook allows users to search through data stored in Airtable, making it easy to find the information they need quickly and efficiently.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Airtable/Airtable_Search_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Airtable/Airtable_Search_data.ipynb", "imports": ["naas_drivers.airtable"], "image_url": ""}, {"objectID": "f529085c0f2d4f78142501e664c14ab66edf02fb933d2d7c8bd49721d43a90df", "tool": "Algolia", "notebook": "Add or Replace all attributes in existing records", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#object", "#save", "#update", "#add"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-15", "description": "This notebook shows how to add new records (objects) to an index or replace existing records with an updated set of attributes.\nThis method redefines all of a record\u2019s attributes (except its objectID). In other words, it fully replaces an existing record.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_Add_or_Replace_all_attributes_in_existing_records.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_Add_or_Replace_all_attributes_in_existing_records.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "5d2df023819411f69ec17f94b0bfde745eb6a1292e39f5cded170e4c053333f6", "tool": "Algolia", "notebook": "Add or Replace all attributes in a single record", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#object", "#save", "#update", "#add"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-15", "description": "This notebook shows how to add new record (object) to an index or replace existing record with an updated set of attributes.\nThis method redefines all of a record\u2019s attributes (except its objectID). In other words, it fully replaces an existing record.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_Add_or_Replace_all_attributes_in_single_record.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_Add_or_Replace_all_attributes_in_single_record.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "bb72a24111a186d70f016c346ba1f037125524cba143537d2c214a354f1d3308", "tool": "Algolia", "notebook": "Delete multiples objects", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#object", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-15", "description": "This notebook shows how to delete multiples objects from an Algolia index using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_Delete_multiples_objects.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_Delete_multiples_objects.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "8d7294cbf8b3918f28680d17d1a9bb6465e72fb8129f2c7d2ff91b571a2de4d7", "tool": "Algolia", "notebook": "Delete a single object", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#object", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-15", "description": "This notebook shows how to delete a single object from an Algolia index using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_Delete_single_object.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_Delete_single_object.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "815211fb3ee83348a3785424987de3ef51856933b6fddbd4c2beea49609ffbe2", "tool": "Algolia", "notebook": "Get all records from an index", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#records", "#browse"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-14", "description": "This notebook shows how to get all records from an Algolia index using Python. It is usefull for organizations that need to access and manipulate data stored in Algolia.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_Get_all_records_from_an_index.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_Get_all_records_from_an_index.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "f5ee3a4a99ee8df9d2b7751ff23b22e1813c83a7c0eb3aae1d3ea0995563ccf2", "tool": "Algolia", "notebook": "List indices", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#list"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-15", "description": "This notebook shows how to get a list of indices with their associated metadata from Algolia using Python. This method retrieves a list of all indices associated with a given Application ID.\nThe returned list includes the names of the indices as well as their associated metadata, such as the number of records, size, and last build time.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_List%20indices.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_List%20indices.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "d18163bf41ff8dd85cbae1e18aa4d976a3244f48089b3cd6c9058b1fd3523720", "tool": "AlphaVantage", "notebook": "Get balance sheet", "action": "", "tags": ["#alphavantage", "#trading", "#market_data", "#investors", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides a way to access financial data from AlphaVantage, specifically balance sheet information for a given company. It allows users to quickly and easily access up-to-date financial information for their analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AlphaVantage/AlphaVantage_Get_balance_sheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AlphaVantage/AlphaVantage_Get_balance_sheet.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "44205360daf5879c2a0eeecd80a0dfc2f4c502dd671b5247ce5234287cddadff", "tool": "AlphaVantage", "notebook": "Get cashflow statement", "action": "", "tags": ["#alphavantage", "#trading", "#market_data", "#investors", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides a way to access financial data from AlphaVantage, including cashflow statements.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AlphaVantage/AlphaVantage_Get_cashflow_statement.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AlphaVantage/AlphaVantage_Get_cashflow_statement.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "03196420b0ecd1331f5511875ff18643e432128254644221a0b139019b1c42cd", "tool": "AlphaVantage", "notebook": "Get company overview", "action": "", "tags": ["#alphavantage", "#trading", "#market_data", "#investors", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides an overview of the AlphaVantage API, which allows users to access real-time and historical financial data for global equities, commodities, and currencies. It provides a comprehensive set of tools to analyze and visualize financial data for a variety of purposes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AlphaVantage/AlphaVantage_Get_company_overview.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AlphaVantage/AlphaVantage_Get_company_overview.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "759fbfe0ce1a7a0c043f30bf8ba8539d3a446058a8f88dee12063444ac6ba3c4", "tool": "AlphaVantage", "notebook": "Get income statement", "action": "", "tags": ["#alphavantage", "#trading", "#market_data", "#investors", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides a way to access income statement data from AlphaVantage, a financial data provider. It allows users to quickly and easily access financial information to make informed decisions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AlphaVantage/AlphaVantage_Get_income_statement.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AlphaVantage/AlphaVantage_Get_income_statement.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "e51bed9276f9ce9924e82646245d4ed0e8815cd7992187fdf8715a68a7bb8a46", "tool": "Azure Blob Storage", "notebook": "List blobs", "action": "", "tags": ["#azure", "#blob", "#storage", "#list", "#blobs"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-14", "created_at": "2023-07-14", "description": "This notebook will demonstrate how to use the List Blobs operation to return a list of the blobs under the specified container. This is usefull for organizations that need to store and access large amounts of data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Azure%20Blob%20Storage/Azure_Blob_Storage_List_blobs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Azure%20Blob%20Storage/Azure_Blob_Storage_List_blobs.ipynb", "imports": ["azure.storage.blob.BlobServiceClient", "azure.storage.blob.BlobServiceClient", "naas"], "image_url": ""}, {"objectID": "5211f802b4119d49640d75844e0de08b997cd5ec85ee5d76e9af6fa027925578", "tool": "Azure Blob Storage", "notebook": "Upload files", "action": "", "tags": ["#azure", "#datalake", "#naas", "#snippet"], "author": "Alexandre Stevens", "author_url": "https://www.linkedin.com/in/
", "updated_at": "2023-04-12", "created_at": "2023-02-06", "description": "This notebook explains how to upload files to Azure Blob Storage using the Azure Python SDK.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Azure%20Blob%20Storage/Azure_Blob_Storage_Upload_files.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Azure%20Blob%20Storage/Azure_Blob_Storage_Upload_files.ipynb", "imports": ["azure.storage.blob.BlobServiceClient", "azure.storage.blob.ContentSettings", "azure.storage.blob.BlobServiceClient", "azure.storage.blob.ContentSettings"], "image_url": ""}, {"objectID": "94f5a9a6634caea4d03c1756a001a4f834c1fd06920b6183b034b0b60c449401", "tool": "Azure Machine Learning", "notebook": "Univariate Timeseries Inference", "action": "", "tags": ["#azure", "#machinelearning", "#univariate", "#timeseries", "#inference", "#ml"], "author": "Tobias Zwingmann", "author_url": "https://www.linkedin.com/in/tobias-zwingmann/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook provides an example of how to use Azure Machine Learning to perform univariate timeseries inference. It is useful for organizations that need to analyze and predict future trends in their data. It requires a timeseries forecasting model hosted on Microsoft Azure and deployed as a web service. (See references below).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Azure%20Machine%20Learning/Azure_Machine_Learning_Univariate_Timeseries_Inference.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Azure%20Machine%20Learning/Azure_Machine_Learning_Univariate_Timeseries_Inference.ipynb", "imports": ["pandas", "requests", "json", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "70cdbff79ec94526b10df7cf0dde2e985f5507c53ef94d0f3c7dd5a925a1c454", "tool": "Bazimo", "notebook": "Get export Actifs", "action": "", "tags": ["#bazimo", "#pm", "#naas_drivers", "#asset", "#scheduler", "#naas", "#csv", "#operations", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-02", "description": "This notebook provides an easy way to export active assets from Bazimo, allowing users to quickly and efficiently manage their assets. It is a great tool for keeping track of assets and ensuring that they are up to date.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bazimo/Bazimo_Get_export_Actifs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bazimo/Bazimo_Get_export_Actifs.ipynb", "imports": ["naas_drivers.bazimo", "naas"], "image_url": ""}, {"objectID": "57013d1c1890e25d5d71579c29c5fd1136a0f99afd6c302de27830221b68f816", "tool": "Bazimo", "notebook": "Get export Baux", "action": "", "tags": ["#bazimo", "#pm", "#naas_drivers", "#asset", "#scheduler", "#naas", "#csv", "#operations", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-02", "description": "This notebook provides an easy way to export data from Baux, allowing users to quickly and efficiently access their data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bazimo/Bazimo_Get_export_Baux.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bazimo/Bazimo_Get_export_Baux.ipynb", "imports": ["naas_drivers.bazimo", "naas"], "image_url": ""}, {"objectID": "f427f26405a8fcd2677cd6850508051cbfae87c2590c8d8f6932f742c88c0e73", "tool": "Bazimo", "notebook": "Get export Factures", "action": "", "tags": ["#bazimo", "#pm", "#naas_drivers", "#asset", "#scheduler", "#naas", "#csv", "#operations", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-02", "description": "This notebook allows you to easily export invoices from Bazimo, making it easy to keep track of your finances.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bazimo/Bazimo_Get_export_Factures.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bazimo/Bazimo_Get_export_Factures.ipynb", "imports": ["naas_drivers.bazimo", "naas"], "image_url": ""}, {"objectID": "075f91fbf86042edf26814810f71ebdf1ce1f37dcd9cd8ebf960c548f0d87f64", "tool": "Bazimo", "notebook": "Get export Locataires", "action": "", "tags": ["#bazimo", "#pm", "#naas_drivers", "#asset", "#scheduler", "#naas", "#csv", "#operations", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-02", "description": "This notebook provides an easy way to export tenant information from Bazimo.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bazimo/Bazimo_Get_export_Locataires.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bazimo/Bazimo_Get_export_Locataires.ipynb", "imports": ["naas_drivers.bazimo", "naas"], "image_url": ""}, {"objectID": "fec0b2c09dbb0faa29db645a2802320abbfadc22f77dea4fac1a5c75d7b6cb30", "tool": "Bazimo", "notebook": "Get export Lots", "action": "", "tags": ["#bazimo", "#pm", "#naas_drivers", "#asset", "#scheduler", "#naas", "#csv", "#operations", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-02", "description": "This notebook allows you to quickly and easily export large amounts of data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bazimo/Bazimo_Get_export_Lots.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bazimo/Bazimo_Get_export_Lots.ipynb", "imports": ["naas_drivers.bazimo", "naas"], "image_url": ""}, {"objectID": "200a5dcebfc9ff32f08e84aaba44cb6125fbc8bbde5f686f467b8626c7ef5f78", "tool": "BeautifulSoup", "notebook": "List social network links from website", "action": "", "tags": ["#beautifulsoup", "#webscraping", "#python", "#html", "#css", "#url"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-02", "created_at": "2023-05-02", "description": "This notebook will use BeautifulSoup to list all the social network links from a website. It is usefull for organizations to quickly get a list of all the social networks they are present on.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/BeautifulSoup/BeautifulSoup_List_social_network_links_from_website.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/BeautifulSoup/BeautifulSoup_List_social_network_links_from_website.ipynb", "imports": ["requests", "bs4.BeautifulSoup"], "image_url": ""}, {"objectID": "12ef03c9788da13b430b0d23171c6c0949ff23c86a70281d36e19d8a6237b135", "tool": "BeautifulSoup", "notebook": "Scrape emails from URL", "action": "", "tags": ["#beautifulsoup", "#python", "#scraping", "#emails", "#url", "#webscraping", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-16", "description": "This notebook will show how to scrape emails stored in HTML webpage using BeautifulSoup.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/BeautifulSoup/BeautifulSoup_Scrape_emails_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/BeautifulSoup/BeautifulSoup_Scrape_emails_from_URL.ipynb", "imports": ["re", "requests", "urllib.parse.urlsplit", "collections.deque", "bs4.BeautifulSoup", "pandas"], "image_url": ""}, {"objectID": "b8dae3c0c48ff11cf99e98ae8c12001027c397f0898d06da9154692ec1a16e62", "tool": "BigQuery", "notebook": "Create table from csv", "action": "", "tags": ["#bigquery", "#database", "#snippet", "#operations", "#dataframe"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-08-08", "description": "This notebook demonstrates how to create a BigQuery table from a CSV file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/BigQuery/BigQuery_Create_table_from_csv.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/BigQuery/BigQuery_Create_table_from_csv.ipynb", "imports": ["naas_drivers.bigquery"], "image_url": ""}, {"objectID": "752be3434483e20df49126952868c6537832491976d513a39ebaa74913771f35", "tool": "BigQuery", "notebook": "Read Table", "action": "", "tags": ["#bigquery", "#database", "#snippet", "#operations", "#dataframe"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-08-08", "description": "This notebook provides an example of how to read data from a BigQuery table.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/BigQuery/BigQuery_Read_Table.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/BigQuery/BigQuery_Read_Table.ipynb", "imports": ["naas_drivers.bigquery"], "image_url": ""}, {"objectID": "9f9713992be8f9af16d3e66e5ea4486c72b84576fa7353df24f29f45ca8331aa", "tool": "Bitly", "notebook": "Create Links", "action": "", "tags": ["#bitly", "#link", "#shorten", "#url", "#create", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-16", "description": "This notebook will show how to create short links with Bitly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Create_Links.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Create_Links.ipynb", "imports": ["requests", "json"], "image_url": ""}, {"objectID": "cd555eb47a32680c309420899038ccaaf7d29a82018a807210599465b6a69fdd", "tool": "Bitly", "notebook": "Delete a Bitlink", "action": "", "tags": ["#bitly", "#api", "#delete", "#bitlink", "#hash", "#unedited"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will show how to delete an unedited hash Bitlink.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Delete_a_Bitlink.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Delete_a_Bitlink.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "3eabe9ed9dcfdcd75e1a510995d981dfc8bd4c2b98f24591b46f59ef5b7a9e18", "tool": "Bitly", "notebook": "Get Clicks for a Bitlink", "action": "", "tags": ["#bitly", "#api", "#getclicks", "#bitlink", "#python", "#dev"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will show how to use the Bitly API to get the click counts for a specified link in an array based on a date.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_Clicks_for_a_Bitlink.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_Clicks_for_a_Bitlink.ipynb", "imports": ["requests", "naas", "json"], "image_url": ""}, {"objectID": "d4eda72f6942beabed764b0411c2d70a3d2841d82e9d26386ee0e3b185c99186", "tool": "Bitly", "notebook": "Get Metrics for a Bitlink by City", "action": "", "tags": ["#bitly", "#api", "#metrics", "#city", "#bitlink", "#dev"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will return the city origins of click traffic for the specified link. This feature is only available for paid account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_City.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_City.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "59334b21ea4228991b77a580a1aaae1c1630d7f1386a8c933d06ca7ac3c459d9", "tool": "Bitly", "notebook": "Get Metrics for a Bitlink by Country", "action": "", "tags": ["#bitly", "#api", "#metrics", "#bitlink", "#country", "#reference"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-23", "description": "This notebook will demonstrate how to use the Bitly API to get metrics for a Bitlink by Country.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Country.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Country.ipynb", "imports": ["requests", "naas", "pandas", "plotly.graph_objects", "dataprep.clean.clean_country", "dataprep.clean.clean_country", "json", "warnings"], "image_url": ""}, {"objectID": "495e8ac289e12e30a84012c1ce626f510ef6a88551618416ab311a12ddd18040", "tool": "Bitly", "notebook": "Get Metrics for a Bitlink by Devices", "action": "", "tags": ["#bitly", "#api", "#metrics", "#devices"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-28", "description": "This notebook will show how to use the Bitly API to get metrics for a Bitlink by devices. This endpoint is only available for paid account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Devices.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Devices.ipynb", "imports": ["requests", "pprint.pprint", "naas"], "image_url": ""}, {"objectID": "27fe513fb49fdd22a120381d7c1a4f927b39395cf488ecce01bedb545a23f099", "tool": "Bitly", "notebook": "Get Metrics for a Bitlink by Referrers", "action": "", "tags": ["#bitly", "#api", "#metrics", "#bitlink", "#referrers", "#dev"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will show how to use the Bitly API to get metrics for a Bitlink by Referrers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Referrers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Referrers.ipynb", "imports": ["requests", "pprint.pprint", "naas"], "image_url": ""}, {"objectID": "b3fa30866ed0675034945aa524ab4cf0cdd9935b491ef7df58d789a7aa1717c4", "tool": "Bitly", "notebook": "Get a Clicks Summary for a Bitlink", "action": "", "tags": ["#bitly", "#api", "#clicks", "#summary", "#bitlink", "#reference"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-23", "description": "This notebook will show how to get a Clicks Summary for a Bitlink using the Bitly API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_a_Clicks_Summary_for_a_Bitlink.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_a_Clicks_Summary_for_a_Bitlink.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "40ce36dc1641790e5117bdab22021f520604f1c26bee66d5fe6d6fd685ed8ee3", "tool": "Bitly", "notebook": "Retrieve Bitlink", "action": "", "tags": ["#bitly", "#api", "#list", "#active", "#links", "#python", "#bitlink"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-23", "description": "This notebook will return information for a specified bitlink using the Bitly API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Retrieve_Bitlink.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Retrieve_Bitlink.ipynb", "imports": ["requests", "json", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "aa9e096cfaf039d08eaa4194d361639e661083ff97b300d6fd2d9d4749c60eef", "tool": "Bitly", "notebook": "Update a Bitlink", "action": "", "tags": ["#bitly", "#api", "#update", "#bitlink", "#reference", "#dev"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will show how to update fields in the specified link using Bitly API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Update_a_Bitlink.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Update_a_Bitlink.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "bfc8dd18a5cb62ba07ffe255ff507cbb6e7d09de0f14feab596ad7718e28b7f1", "tool": "Boursorama", "notebook": "Get CDS", "action": "", "tags": ["#boursorama", "#finance", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-09", "description": "This notebook provides a way to access and analyze CDS data from Boursorama.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Boursorama/Boursorama_Get_CDS.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Boursorama/Boursorama_Get_CDS.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "916217867d00e933791e4bd89337ec26ce052f7e856663b80b8707fb16257d4e", "tool": "Boursorama", "notebook": "Get EURIBOR 3 MOIS", "action": "", "tags": ["#boursorama", "#euribor", "#pandas", "#read_html", "#finance", "#data"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will show how to get EURIBOR 3 MOIS using pandas.read_html().", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Boursorama/Boursorama_Get_EURIBOR_3_MOIS.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Boursorama/Boursorama_Get_EURIBOR_3_MOIS.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "f969028b22c1a3a446445dd979298e843d9b00e67cfcdc6d9f0e0ca94ed9e8fa", "tool": "Bubble", "notebook": "Send data", "action": "", "tags": ["#bubble", "#naas_drivers", "#operations", "#snippet"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "This notebook allows users to easily send data through a secure, cloud-based platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bubble/Bubble_Send_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bubble/Bubble_Send_data.ipynb", "imports": ["naas_drivers.bubble"], "image_url": ""}, {"objectID": "d32e84a4975bcf6f6343720e6e7ab190036193ef0512dd09ce63387dcee3bfce", "tool": "CCXT", "notebook": "Calculate Support and Resistance", "action": "", "tags": ["#ccxt", "#bitcoin", "#trading", "#investors", "#analytics", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a guide to using the CCXT library to calculate support and resistance levels for cryptocurrency trading.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/CCXT/CCXT_Calculate_Support_and_Resistance.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/CCXT/CCXT_Calculate_Support_and_Resistance.ipynb", "imports": ["naas", "ccxt", "pandas", "datetime.datetime", "naas_drivers", "trendln", "plotly.tools", "plotly.graph_objects"], "image_url": ""}, {"objectID": "f91ca561288c0eb0c1d84e6a165300ce2af7db52fca7389f551767b209a2de24", "tool": "CCXT", "notebook": "Predict Bitcoin from Binance", "action": "", "tags": ["#ccxt", "#bitcoin", "#trading", "#investors", "#ai", "#analytics", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook uses the CCXT library to predict Bitcoin prices on the Binance exchange.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/CCXT/CCXT_Predict_Bitcoin_from_Binance.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/CCXT/CCXT_Predict_Bitcoin_from_Binance.ipynb", "imports": ["naas", "ccxt", "pandas", "datetime.datetime", "naas_drivers.plotly, prediction"], "image_url": ""}, {"objectID": "2fac04a0e47274af3af50087ce42c66a7c88cdc4d2187f530ae968310c7cefe9", "tool": "Canny", "notebook": "Create", "action": "", "tags": ["#canny", "#product", "#operations", "#snippet"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu", "updated_at": "2023-04-12", "created_at": "2021-01-26", "description": "This notebook provides an easy-to-use interface for creating custom Canny edge detection filters.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Canny/Canny_Create.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Canny/Canny_Create.ipynb", "imports": ["requests", "json", "pandas"], "image_url": ""}, {"objectID": "e99b960cfb98cd5fe1eefc5ab9734d32cd7328846af6b8258321e40463768645", "tool": "Canny", "notebook": "Github issue update", "action": "", "tags": ["#canny", "#product", "#operations", "#snippet", "#github"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu", "updated_at": "2023-04-12", "created_at": "2021-01-26", "description": "This notebook provides an automated way to keep track of Github issues and their updates.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Canny/Canny_Github_issue_update.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Canny/Canny_Github_issue_update.ipynb", "imports": ["requests", "json", "github.Github", "pandas"], "image_url": ""}, {"objectID": "5f7c655a1a23609d607d4d123f44853440b27a11ac985de645279ef85c92db1a", "tool": "Canny", "notebook": "Read", "action": "", "tags": ["#canny", "#product", "#operations", "#snippet"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu", "updated_at": "2023-04-12", "created_at": "2021-01-26", "description": "This notebook is a comprehensive guide to understanding and applying the Canny edge detection algorithm.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Canny/Canny_Read.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Canny/Canny_Read.ipynb", "imports": ["requests", "json", "pandas"], "image_url": ""}, {"objectID": "b5d3fc12c82fbcc5bfc6f310e38b0d4fd5270da588df0c8926fbacb000c99f54", "tool": "Celestrak", "notebook": "Satellites over time", "action": "", "tags": ["#celestrak", "#opendata", "#satellites", "#analytics", "#plotly"], "author": "Dumorya", "author_url": "https://github.com/Dumorya", "updated_at": "2023-04-12", "created_at": "2021-06-11", "description": "This notebook provides a visual representation of the changing number of satellites in Earth's orbit over time.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Celestrak/Celestrak_Satellites_over_time.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Celestrak/Celestrak_Satellites_over_time.ipynb", "imports": ["pandas", "plotly.express", "plotly.graph_objects", "numpy"], "image_url": ""}, {"objectID": "688e1d955c26c14cf79153c9ba1bfaf124451cc614bd2e48229eb64ef5534683", "tool": "Cityfalcon", "notebook": "Get data from API", "action": "", "tags": ["#cityfalcon", "#news", "#opendata", "#snippet", "#investors", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-23", "description": "This notebook provides a guide to using the Cityfalcon API to access data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Cityfalcon/Cityfalcon_Get_data_from_API.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Cityfalcon/Cityfalcon_Get_data_from_API.ipynb", "imports": ["naas_drivers.cityfalcon"], "image_url": ""}, {"objectID": "0aa8bc599e4d5c5ed18242a663e9bddbcb379065d173c33908fa9d29cf0d7085", "tool": "Clockify", "notebook": "Add a new client", "action": "", "tags": ["#clockify", "#client", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to add a new client using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Add_a_new_client.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Add_a_new_client.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "e1eded982d49f9a550f7db5cfbf935d98e51bfed0d93c90121ddc84e4dac2b03", "tool": "Clockify", "notebook": "Add a new project", "action": "", "tags": ["#clockify", "#project", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-17", "created_at": "2023-05-17", "description": "This notebook will show how to add a new project using Clockify API to a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Add_a_new_project.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Add_a_new_project.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "77854836bd7b25aefc0458b51b50db3432c4fffbeb389be924bb4df7ef2ecd0f", "tool": "Clockify", "notebook": "Create time entries database on a workspace", "action": "", "tags": ["#clockify", "#timeentry", "#database", "#workspace", "#user", "#create"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-26", "created_at": "2023-07-26", "description": "This notebook creates a time entries database on a specific timeframe, adding client, project and task name. It is usefull for organizations to track time entries and optimize their workflow.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Create_time_entries_database_on_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Create_time_entries_database_on_workspace.ipynb", "imports": ["requests", "naas", "pandas", "datetime.datetime"], "image_url": ""}, {"objectID": "fb1e32f0bf0dae62327dfc4282ebd8b8b3102727e3484a5ac9ec5c47cb78e959", "tool": "Clockify", "notebook": "Delete client", "action": "", "tags": ["#clockify", "#client", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to delete an existing client using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Delete_client.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Delete_client.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "d57352246f90d2636fbe59bbd56770cd15f64252f8f7f9d0495f907809369af8", "tool": "Clockify", "notebook": "Delete project", "action": "", "tags": ["#clockify", "#project", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-17", "created_at": "2023-05-17", "description": "This notebook will show how to delete an existing project using Clockify API from a specific workspace. You can only delete archived project. Active project can not be deleted.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Delete_project.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Delete_project.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "889fc1d9060a7d6797b56f68349eabd2bedb1e4e9627fcb1ebac0236ceca3330", "tool": "Clockify", "notebook": "Find all users on workspace", "action": "", "tags": ["#clockify", "#workspace", "#users", "#find", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to find all users on a workspace using Clockify API.\nIt will return a dataframe with columns as follow:\n- id: This column stores an identifier or unique identifier associated with a user. It likely contains alphanumeric values that uniquely identify each user in the DataFrame.\n- email: This column stores the email addresses associated with the users in the DataFrame. It likely contains text values representing the email addresses of the users.\n- name: This column stores the names or titles associated with the users in the DataFrame. It likely contains text values representing the names of the users.\n- memberships: This column represents the memberships or group affiliations of the users. It likely contains a list or nested data structure that indicates the groups or memberships the users belong to.\n- profilePicture: This column stores the URLs or paths to the profile pictures of the users. It likely contains text values representing the image URLs or file paths.\n- activeWorkspace: This column represents the identifier or unique identifier of the active workspace for each user. It likely contains alphanumeric values that uniquely identify the active workspace.\n- defaultWorkspace: This column stores the identifier or unique identifier of the default workspace for each user. It likely contains alphanumeric values that uniquely identify the default workspace.\n- settings: This column stores user-specific settings or configurations. It likely contains nested data structures or dictionaries that hold various settings related to the user, such as the week start day and timezone.\n- status: This column indicates the status of the users, whether they are active or inactive. It likely contains text values such as \"ACTIVE\" or \"INACTIVE\".\n- customFields: This column stores custom fields or additional information specific to each user. It may contain nested data structures or lists that hold user-specific custom field values.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Find_all_users_on_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Find_all_users_on_workspace.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "27f82b7d0a5b14067a0ddf876dab8649394f189567eecf8a87d260783e7b44d8", "tool": "Clockify", "notebook": "Find clients on workspace", "action": "", "tags": ["#clockify", "#workspace", "#client", "#api", "#python", "#find"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to find clients on a workspace using the Clockify API. It will return a dataframe with columns as follow:\n- id: This column represents an identifier or unique identifier associated with a record or entity. It contains alphanumeric values that uniquely identify each row in the DataFrame.\n- name: This column stores the name or title associated with a particular record or entity. It likely contains text values representing the name of a person, object, or entity.\n- email: This column stores email addresses associated with the records in the DataFrame. It likely contains text values representing the email addresses of individuals or entities.\n- workspaceId: This column represents an identifier or unique identifier associated with a workspace. It likely contains alphanumeric values that uniquely identify each workspace.\n- archived: This column indicates whether a record or entity is archived or not. It likely contains boolean values (True or False), with True indicating that the record is archived and False indicating that it is not.\n- address: This column stores addresses associated with the records in the DataFrame. It likely contains text values representing physical or postal addresses.\n- note: This column stores additional notes or comments related to the records in the DataFrame. It may contain text values providing extra information or details about a particular record or entity.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Find_clients_on_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Find_clients_on_workspace.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "78681e3bc7de22fcb89133eb27fcb13afb59ba5dc01a777f4b0fafb2fda819de", "tool": "Clockify", "notebook": "Find tasks on project", "action": "", "tags": ["#clockify", "#task", "#project", "#find", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will help you find tasks on a project using Clockify API. It will return a dataframe with columns as follow:\n- id: This column stores an identifier or unique identifier associated with a task. It likely contains alphanumeric values that uniquely identify each task in the DataFrame.\n- name: This column stores the names or titles associated with the tasks. It likely contains text values representing the names or titles of the tasks.\n- projectId: This column represents the identifier or unique identifier of the project to which each task belongs. It likely contains alphanumeric values that uniquely identify the project.\n- assigneeIds: This column stores the identifiers or unique identifiers of the assignees assigned to the tasks. It likely contains a list or nested data structure that indicates the assignees associated with each task.\n- assigneeId: This column stores the identifier or unique identifier of a single assignee assigned to the task. It likely contains a single value indicating the assignee for the task.\n- userGroupIds: This column stores the identifiers or unique identifiers of the user groups associated with the tasks. It likely contains a list or nested data structure that indicates the user groups associated with each task.\n- estimate: This column stores the estimate or estimated duration for each task. It likely contains a time duration format, such as \"PT0S\" (indicating zero duration).\n- status: This column indicates the status of the tasks, whether they are active or inactive. It likely contains text values such as \"ACTIVE\" or \"INACTIVE\".\n- duration: This column stores the actual duration or time taken for each task. It likely contains a time duration format, such as \"PT2H42M1S\" (indicating a duration of 2 hours, 42 minutes, and 1 second).\n- billable: This column indicates whether the task is billable or not. It likely contains boolean values (True or False), with True indicating that the task is billable and False indicating that it is not.\n- hourlyRate: This column stores the hourly rate associated with the task. It likely contains numerical values representing the rate for the task, such as an hourly billing rate.\n- costRate: This column stores the cost rate associated with the task. It likely contains numerical values representing the cost rate for the task, such as the rate at which the task incurs costs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Find_tasks_on_project.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Find_tasks_on_project.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "a0b6e7901a2279ecf1696d79f06b9f10b174ad1d6e1af1afdf173c4aefe92635", "tool": "Clockify", "notebook": "Get all my workspaces", "action": "", "tags": ["#clockify", "#api", "#workspace", "#get", "#python", "#rest"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-04-05", "description": "This notebook will show how to get all workspaces of a user using the Clockify API and return a dict.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Get_all_my_workspaces.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Get_all_my_workspaces.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "26994336a93d1f5c9ce8b985beda6b15c3739af1bb21802a977f33b5083da2a5", "tool": "Clockify", "notebook": "Get all projects on workspace", "action": "", "tags": ["#clockify", "#api", "#projects", "#workspace", "#get", "#python"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-05-17", "created_at": "2023-04-05", "description": "This notebook will show how to get all projects on a workspace using the Clockify API and return a dict.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Get_all_projects_on_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Get_all_projects_on_workspace.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "dde1e297a4f5047b497f5ff860a3d36770571578f3c400c2528091607ce82058", "tool": "Clockify", "notebook": "Get client by ID", "action": "", "tags": ["#clockify", "#client", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to get a client using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Get_client_by_ID.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Get_client_by_ID.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "e0be8e4e76433300e789b377ab059f135ee55e69afac5dddbe0d479c67696650", "tool": "Clockify", "notebook": "Get project by ID", "action": "", "tags": ["#clockify", "#project", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-17", "created_at": "2023-05-17", "description": "This notebook will show how to get a project using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Get_project_by_ID.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Get_project_by_ID.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "b40e1e0366358c58a01662a2ec775ec47ecfb7a75fb0790826c477378b0e6657", "tool": "Clockify", "notebook": "Get time entries for a user on workspace", "action": "", "tags": ["#clockify", "#timeentry", "#api", "#python", "#workspace", "#user"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to get time entries for a user on a workspace using Clockify API. It will return a dataframe with columns as follow:\n- id: This column stores an identifier or unique identifier associated with a time entry. It likely contains alphanumeric values that uniquely identify each time entry in the DataFrame.\n- description: This column stores the description or details associated with the time entry. It likely contains text values representing a description of the activity or task performed during the time entry.\n- tagIds: This column stores the identifiers or unique identifiers of the tags associated with the time entry. It likely contains a list or nested data structure that indicates the tags associated with the time entry.\n- userId: This column represents the identifier or unique identifier of the user who created the time entry. It likely contains alphanumeric values that uniquely identify the user.\n- billable: This column indicates whether the time entry is billable or not. It likely contains boolean values (True or False), with True indicating that the time entry is billable and False indicating that it is not.\n- taskId: This column stores the identifier or unique identifier of the task associated with the time entry. It likely contains alphanumeric values that uniquely identify the task.\n- projectId: This column represents the identifier or unique identifier of the project associated with the time entry. It likely contains alphanumeric values that uniquely identify the project.\n- timeInterval_start: This column stores the start timestamp of the time interval for the time entry. It likely contains timestamp values indicating when the time entry started.\n- timeInterval_end: This column stores the end timestamp of the time interval for the time entry. It likely contains timestamp values indicating when the time entry ended.\n- timeInterval_duration: This column stores the duration of the time entry. It likely contains a time duration format, such as \"PT37M16S\" (indicating a duration of 37 minutes and 16 seconds).\n- workspaceId: This column represents the identifier or unique identifier of the workspace associated with the time entry. It likely contains alphanumeric values that uniquely identify the workspace.\n- isLocked: This column indicates whether the time entry is locked or not. It likely contains boolean values (True or False), with True indicating that the time entry is locked and False indicating that it is not.\n- customFieldValues: This column stores custom field values associated with the time entry. It likely contains nested data structures or lists that hold custom field values specific to the time entry.\n- type: This column indicates the type or category of the time entry. It likely contains text values representing the type of activity or task associated with the time entry.\n- kioskId: This column stores the identifier or unique identifier of the kiosk associated with the time entry. It likely contains alphanumeric values that uniquely identify the kiosk.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Get_time_entries_for_a_user_on_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Get_time_entries_for_a_user_on_workspace.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "55ff26f7546527d35891d67642ff3558b55cbe046d7c2611c52da19231ce24bd", "tool": "Clockify", "notebook": "Remove user from workspace", "action": "", "tags": ["#clockify", "#workspace", "#remove", "#user", "#api", "#rest"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-05-16", "created_at": "2023-04-05", "description": "This notebook explains how to remove a user from a workspace using the Clockify API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Remove_user_from_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Remove_user_from_workspace.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "e9dd7f3721289c5cacbb673f835f8704f69b9c284464098a10e7a324a52b8a32", "tool": "Clockify", "notebook": "Send time entries database to a Google Sheets spreadsheet", "action": "", "tags": ["#clockify", "#timeentry", "#database", "#workspace", "#user", "#task", "#project", "#gsheet", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will send the time entries database from Clockify to a Google Sheets spreadsheet. This is usefull for organizations to keep track of their time entries and analyze them.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Send_time_entries_database_to_Google_Sheets_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Send_time_entries_database_to_Google_Sheets_spreadsheet.ipynb", "imports": ["requests", "naas", "pandas", "datetime.datetime", "naas_drivers.gsheet"], "image_url": ""}, {"objectID": "40a719b2a9fd405a4bac1dd9864c9832a49dcbab49584008dbede718c03e8ee7", "tool": "Clockify", "notebook": "Update client", "action": "", "tags": ["#clockify", "#client", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to update a client using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Update_client.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Update_client.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "00cfb28fd1d25a93635ff29385838c7c9f14d989cbb35e6a77b60c5d156718ce", "tool": "Clockify", "notebook": "Update project", "action": "", "tags": ["#clockify", "#project", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-17", "created_at": "2023-05-17", "description": "This notebook will show how to update a project using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Update_project.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Update_project.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "c5fcb9a6ae84c92e74a8dd8b916b7741c133dc3e1efc59b1a730f711ae61f834", "tool": "Cloud Mercato", "notebook": "Compare VM pricing", "action": "", "tags": ["#cloud", "#infrastruture", "#pricing", "#vm", "#iaas", "#analytics", "#compute"], "author": "Anthony Monthe", "author_url": "https://www.linkedin.com/in/anthonymonthe/", "updated_at": "2023-04-12", "created_at": "2022-11-01", "description": "Cloud Mercato is an online platform that allows users to compare virtual machine pricing from different cloud providers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Cloud%20Mercato/Cloud_Mercato_Compare_VM_pricing.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Cloud%20Mercato/Cloud_Mercato_Compare_VM_pricing.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "a420b595b58b994e4a8054607be73c2945ba0b41c37a582aac12836ae0fb9cef", "tool": "Creditsafe", "notebook": "Get Company Credit Report", "action": "", "tags": ["#creditsafe", "#api", "#enterprise", "#integrations", "#company", "#creditreport"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-08", "description": "This notebook will demonstrate how to use the Creditsafe API to get a company credit report.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Creditsafe/Creditsafe_Get_Company_Credit_Report.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Creditsafe/Creditsafe_Get_Company_Credit_Report.ipynb", "imports": ["requests", "naas", "pprint.pprint", "json"], "image_url": ""}, {"objectID": "99dc0ea3413e44582f05edc31fb2079f4e0778981f68d58246b80aae2b23be24", "tool": "D-Tale", "notebook": "Visualize dataframe", "action": "", "tags": ["#csv", "#pandas", "#snippet", "#read", "#dataframe", "#visualize", "#dtale", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-04-11", "description": "D-Tale is a tool that allows users to quickly and easily visualize dataframes in an interactive and intuitive way.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/D-Tale/D-Tale_Visualize_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/D-Tale/D-Tale_Visualize_dataframe.ipynb", "imports": ["pandas", "dtale", "dtale.app"], "image_url": ""}, {"objectID": "27f443089a00055bee93b043b9b42d368258d639ffac4a99a34bcac72a8c6f06", "tool": "Dash", "notebook": "Add a customisable sidebar", "action": "", "tags": ["#dash", "#offcanvas", "#sidebar", "#customisable", "#component", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook demonstrates how to use the Offcanvas component to add a customisable sidebar to your apps. It is usefull for organisations that need to add a sidebar to their Dash apps.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Add_a_customisable_sidebar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Add_a_customisable_sidebar.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.Input, Output, State, html"], "image_url": ""}, {"objectID": "800cd47399958fce0bb44cc5202abf7b490ca015760efa4088ac69124bf4787e", "tool": "Dash", "notebook": "Create Datatable With Dropdown", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Ismail Chihab", "author_url": "https://www.linkedin.com/in/ismail-chihab-4b0a04202/", "updated_at": "2023-04-12", "created_at": "2022-08-26", "description": "Create a basic table that can be updated through a dcc.dropdown menu.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Datatable_With_Dropdown.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Datatable_With_Dropdown.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, Input, Output, dcc, dash_table", "pandas"], "image_url": ""}, {"objectID": "e9818d91a4e391da8889aa702a1be52ddf216175ed60dd4ce1b70b4b4b817cd7", "tool": "Dash", "notebook": "Create Dropdown Callback", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-18", "description": "Create a basic dropdown, provide options and a value to dcc.Dropdown in that order.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Dropdown_Callback.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Dropdown_Callback.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, Input, Output, State, dcc"], "image_url": ""}, {"objectID": "0c5da456dd8bf84ccd405188c1a60872fa082aae7a99567911a59be09a5b9fcd", "tool": "Dash", "notebook": "Create Dropdown with multiples output callbacks", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-18", "description": "Create a basic dropdown, provide options and a value to dcc.Dropdown in that order.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Dropdown_with_multiples_output_callbacks.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Dropdown_with_multiples_output_callbacks.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, Input, Output, State, dcc, dash_table", "plotly.graph_objs", "dash.exceptions.PreventUpdate"], "image_url": ""}, {"objectID": "68a887dfaaa80942ddb1a232171e004e74e6ef6db41fa8bbdb0454c220e10f3e", "tool": "Dash", "notebook": "Create Interactive Plot", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-05-29", "created_at": "2023-05-25", "description": "This notebook creates an interactive plot using Dash app infrastructure.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Interactive_Plot.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Interactive_Plot.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express", "io", "requests"], "image_url": ""}, {"objectID": "1774258ba69e802f126a725e1df40f6af2f051dcc113cb134a808e1bbfbc2236", "tool": "Dash", "notebook": "Create Navbar", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#asset", "#analytics", "#navbar", "#bootstrap"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-17", "description": "A simple app demonstrating how to manually construct a navbar with a customised layout using the Navbar component and the supporting Nav, NavItem, NavLink, NavbarBrand, and NavbarToggler components.\n\nRequires dash-bootstrap-components 0.3.0 or later", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Navbar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Navbar.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, Input, Output, State"], "image_url": ""}, {"objectID": "d4243fd641f0b712b1154b26fc159e3c1bb7df479750d063f11935eef3874ac6", "tool": "Dash", "notebook": "Create Navbar board", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#asset", "#analytics", "#navbar", "#bootstrap"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-18", "description": "This notebook allows users to create a customizable navigation bar for their website or application.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Navbar_Dashboard.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Navbar_Dashboard.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, Input, Output, State, dcc"], "image_url": ""}, {"objectID": "d195aeb80452c89e129ea46a655d09b2460d9fecc0f9770ce742bf3fc6cff0e9", "tool": "Dash", "notebook": "Create Navbar Search", "action": "", "tags": ["#dash", "#snippet", "#dashboard", "#plotly", "#dash", "#analytics"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-15", "description": "This notebook provides a tutorial on how to create a searchable navigation bar using the Dash library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Navbar_Search.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Navbar_Search.ipynb", "imports": ["dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc", "dash.dependencies.Input, Output", "os"], "image_url": ""}, {"objectID": "4b333f42522abb0ce297502127eba3288b9cd14336f94c563c7523156c545ceb", "tool": "Dash", "notebook": "Create button to refresh page", "action": "", "tags": ["#dash", "#python", "#button", "#refresh", "#page", "#stackoverflow"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-02", "created_at": "2023-06-02", "description": "This notebook explains how to create a button in Dash to refresh the page.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_button_to_refresh_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_button_to_refresh_page.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc, Output, Input, State"], "image_url": ""}, {"objectID": "5d0ec204e1adc070996a900d4212c1d45f5925dc25a522b3e3f45b857e1e6f54", "tool": "Dash", "notebook": "Create conditional formatting on HTML element", "action": "", "tags": ["#dash", "#html", "#conditional", "#formatting", "#element", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to create conditional formatting of an HTML element using Dash.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_conditional_formatting_on_HTML_element.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_conditional_formatting_on_HTML_element.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc, Output, Input, State"], "image_url": ""}, {"objectID": "e8bf48a389426d3ffba1975c7da90f59b8784773a0440500b8d64869357abfc7", "tool": "Dash", "notebook": "Create conditional formatting on number value", "action": "", "tags": ["#dash", "#html", "#conditional", "#formatting", "#element", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to create conditional formatting of an HTML element using Dash.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_conditional_formatting_on_number_value.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_conditional_formatting_on_number_value.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc, Output, Input, State"], "image_url": ""}, {"objectID": "0884edbacf735f45bc43e534555b0b0c3293fcfe22599d60ec7a9461e2e52e7e", "tool": "Dash", "notebook": "Create download button", "action": "", "tags": ["#dash", "#button", "#download", "#create", "#python", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook will show how to create a download button with Dash.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_download_button.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_download_button.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html"], "image_url": ""}, {"objectID": "8724d5174822ed9a031f96f8bb87140b72d60f7a27a664065d744aab70131681", "tool": "Dash", "notebook": "Create loading button", "action": "", "tags": ["#dash", "#plotly", "#loading", "#button", "#python", "#web"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-02", "created_at": "2023-06-02", "description": "This notebook explains how to create a loading button with Dash Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_loading_button.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_loading_button.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "dash.Dash, html, dcc, callback, Output, Input, State", "time"], "image_url": ""}, {"objectID": "dd2c5fe6315560fa638685fb739dc1b4a6d39089220f430d269c01b78c7dd953", "tool": "Dash", "notebook": "Create spinner button", "action": "", "tags": ["#dash", "#button", "#download", "#create", "#python", "#library", "#spinner"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook will show how to create a spinner button with Dash. The `Spinner` component can be used inside buttons to indicate that an action is currently processing or taking place.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_spinner_button.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_spinner_button.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html"], "image_url": ""}, {"objectID": "162e8064b2a3e2bb21972a90cb77673df932c178555c3a985b7218c3c2786444", "tool": "Dash", "notebook": "Deploy app in Naas", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#asset", "#automation", "#analytics"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-01", "description": "This notebook provides a step-by-step guide to deploying an app with Dash on Naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Deploy_app_in_Naas.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Deploy_app_in_Naas.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc", "plotly.express", "plotly.graph_objects"], "image_url": ""}, {"objectID": "477b2f627d6fc1d842945d36a8661d2f63c69d27ec2afe9612e5ccbf54aaba0a", "tool": "Dash", "notebook": "LinkedIn posts metrics dashboard", "action": "", "tags": ["#dash", "#linkedin", "#dashboard", "#plotly", "#naas", "#asset", "#automation", "#analytics"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-06", "description": "This notebook provides a dashboard to track and analyze metrics related to LinkedIn posts.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_LinkedIn_posts_metrics_dashboard.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_LinkedIn_posts_metrics_dashboard.ipynb", "imports": ["os", "os.environ", "pandas", "naas", "datetime.datetime", "naas_drivers.gsheet", "plotly.graph_objects", "plotly.express", "plotly.subplots.make_subplots", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc, Input, Output, State", "dash_bootstrap_components._components.Container.Container", "dash.exceptions.PreventUpdate"], "image_url": ""}, {"objectID": "950b5ed31417ee13e856d45afc141338d870a01592a83e9f71131ed42d8d2f02", "tool": "Dash", "notebook": "Plotly Dynamic Link", "action": "", "tags": ["#dash", "#plotly", "#naas", "#analytics"], "author": "Oguz Akif Tufekcioglu", "author_url": "https://www.linkedin.com/in/oguzakiftufekcioglu/", "updated_at": "2023-04-12", "created_at": "2022-10-18", "description": "This notebook provides an interactive way to explore data with Dash and Plotly, allowing users to create dynamic links between visualizations.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Plotly_Dynamic_Link.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Plotly_Dynamic_Link.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "webbrowser", "dash.dependencies.Input, Output", "dash.html, dcc", "dash.exceptions.PreventUpdate", "plotly.express", "plotly.graph_objects"], "image_url": ""}, {"objectID": "506d501ebff0f9b3a6ab229a88a2464ece6c09bfdd29e7b5ce5d43731c3a3c5d", "tool": "Dash", "notebook": "Upload mutiples CSV Excel", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#upload", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-11-22", "description": "This notebook allows users to upload multiple CSV and Excel files to create interactive visualizations with Dash.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Upload_mutiples_CSV_Excel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Upload_mutiples_CSV_Excel.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.Dash, dcc, html, Input, Output, State", "pandas", "base64", "datetime", "io", "dash.dcc, html, dash_table"], "image_url": ""}, {"objectID": "61bc9b898dcd8659c49a5ac5fe46a212b5f7217286b9bccdbfec9183f9cd9732", "tool": "Dask", "notebook": "Parallelize operations on multiple csvs", "action": "", "tags": ["#csv", "#pandas", "#snippet", "#read", "#dataframe", "#parallel", "#parallelize", "#dask", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-04-13", "description": "This notebook demonstrates how to use Dask to efficiently process and analyze multiple CSV files in parallel.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dask/Dask_parallelize_operations_on_multiple_csvs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dask/Dask_parallelize_operations_on_multiple_csvs.ipynb", "imports": ["os", "graphviz", "graphviz", "dask.dataframe", "dask.dataframe", "pandas", "glob"], "image_url": ""}, {"objectID": "6a8d408c93bbef46e9136bfea9c5e3416c18cccde9528f35a88f44c763960c08", "tool": "Data.gouv.fr", "notebook": "COVID19 - FR - Entr\u00e9es et sorties par r\u00e9gion pour 1 million d'hab.", "action": "", "tags": ["#data.gouv.fr", "#opendata", "#france", "#analytics"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook provides an analysis of the entry and exit of one million people in each region of France due to the COVID-19 pandemic.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Data.gouv.fr/COVID19%20-%20%20FR%20-%20Entr%C3%A9es%20et%20sorties%20par%20r%C3%A9gion%20pour%201%20million%20d%27hab..ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Data.gouv.fr/COVID19%20-%20%20FR%20-%20Entr%C3%A9es%20et%20sorties%20par%20r%C3%A9gion%20pour%201%20million%20d%27hab..ipynb", "imports": ["requests", "pandas", "datetime.datetime, timedelta", "plotly.graph_objects", "plotly.subplots.make_subplots", "numpy"], "image_url": ""}, {"objectID": "2725c6bbe45eba9e5d58de0a89d96d7ad467ef8dbe42a084dbfb28b3328a03aa", "tool": "Data.gouv.fr", "notebook": "R\u00e9cup\u00e9ration donn\u00e9es l\u00e9gales entreprise", "action": "", "tags": ["#data.gouv.fr", "#snippet", "#naas", "#societe", "#opendata"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-05-04", "description": "This notebook provides a guide to retrieving legal data from data.gouv.fr for businesses.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Data.gouv.fr/Data.gouv.fr_R%C3%A9cup%C3%A9ration_donn%C3%A9es_l%C3%A9gales_entreprise.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Data.gouv.fr/Data.gouv.fr_R%C3%A9cup%C3%A9ration_donn%C3%A9es_l%C3%A9gales_entreprise.ipynb", "imports": ["requests", "pprint.pprint"], "image_url": ""}, {"objectID": "14ddb09c734bc7d6e5f8c0adfd7ac2d7c8f2002d6e506149cf3e833c788c9ce9", "tool": "Datetime", "notebook": "Calculate relative time delta between two dates", "action": "", "tags": ["#datetime", "#datetime", "#relativedelta", "#calculate", "#date", "#time", "#dateutil"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-05-22", "description": "This notebook calculates the relative time delta between two dates.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Calculate_relative_time_delta_between_two_dates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Calculate_relative_time_delta_between_two_dates.ipynb", "imports": ["datetime.datetime", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "f7399e612e827014cbd261e6dfd655c72c29ebdcaa7f136699463a2cb8d5ae82", "tool": "Datetime", "notebook": "Calculate time delta between two dates", "action": "", "tags": ["#datetime", "#timedelta", "#calculate", "#date", "#time"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-05-22", "description": "This notebook calculates the time delta between two dates.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Calculate_time_delta_between_two_dates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Calculate_time_delta_between_two_dates.ipynb", "imports": ["datetime.datetime"], "image_url": ""}, {"objectID": "ee2454efaf6543bbecbe368327aa987b1cf2c65b67a0d60de28d59966ca7e3de", "tool": "Datetime", "notebook": "Convert datetime object to a formatted date string", "action": "", "tags": ["#datetime", "#snippet", "#operations", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-07-05", "description": "This notebook provides an introduction to using the Python datetime library to work with dates and times.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Convert_datetime_object_to_string_date.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Convert_datetime_object_to_string_date.ipynb", "imports": ["datetime.datetime"], "image_url": ""}, {"objectID": "527179e27a2e54e5090aa8ae94593c5883ba100a886199344c55e8a046e103de", "tool": "Datetime", "notebook": "Convert with Timezone to ISO 8601 date string", "action": "", "tags": ["#datetime", "#timezone", "#iso8601", "#string", "#conversion"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-02-15", "description": "This notebook will demonstrate how to convert a datetime with timezone to an ISO 8601 date string.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Convert_datetime_with_timezone_to_ISO_8601_date_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Convert_datetime_with_timezone_to_ISO_8601_date_string.ipynb", "imports": ["datetime.datetime", "pytz"], "image_url": ""}, {"objectID": "2e58cf9199f74e34fc1aae9761efc23814d7a0f9ce53e6d9464203e0b82e651a", "tool": "Datetime", "notebook": "Convert relative time delta to months", "action": "", "tags": ["#datetime", "#relativedelta", "#calculate", "#date", "#time", "#dateutil"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-05-22", "description": "This notebook is designed to convert the relative time delta between two dates into months. By utilizing the `relativedelta` function, the conversion becomes more accurate compared to using `timedelta`, as `relativedelta` considers the varying number of days in each month.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Convert_relative_time_delta_to_months.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Convert_relative_time_delta_to_months.ipynb", "imports": ["datetime.datetime", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "c2bafcf6bd3d8bd05a9b45ff7085dcc9a41d4300fdb65f762e0256546d40fd20", "tool": "Datetime", "notebook": "Convert a string date to a datetime object", "action": "", "tags": ["#datetime", "#snippet", "#operations", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-07-05", "description": "This notebook converts a string date to a datetime object", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Convert_string_to_datetime_object.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Convert_string_to_datetime_object.ipynb", "imports": ["datetime.datetime"], "image_url": ""}, {"objectID": "deacb63cb8ea46333f7b10672b968a20991c44cc34048cecbd7af276488cdc36", "tool": "Datetime", "notebook": "Convert timestamp to a datetime object", "action": "", "tags": ["#datetime", "#python", "#timestamp", "#convert", "#datetimeobject", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-05", "created_at": "2023-07-05", "description": "This notebook will show how to convert a timestamp to a datetime object in Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Convert_timestamp_to_a_datetime_object.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Convert_timestamp_to_a_datetime_object.ipynb", "imports": ["datetime.datetime"], "image_url": ""}, {"objectID": "898c8b8d33cadf517a47046cf51115935b579a8a1797b5c0b098af29e2075b8f", "tool": "Deepl", "notebook": "Translated string to txt", "action": "", "tags": ["#deepl", "#translate", "#text", "#txt", "#api", "#string"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook show how to translate a string with Deepl API and save it in a txt file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Deepl/Deepl_Translated_string_to_txt.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Deepl/Deepl_Translated_string_to_txt.ipynb", "imports": ["naas", "deepl", "deepl"], "image_url": ""}, {"objectID": "8f82e653557ca28f058454ad86c1553add053a2e1d00829c8a1a7cc052d5df90", "tool": "Draft Kings", "notebook": "Get MLB Moneylines", "action": "", "tags": ["#draftkings", "#mlb", "#betting", "#python", "#analytics", "#automation", "#sports", "#sports_betting", "#opendata", "#notification", "#email"], "author": "JA Williams", "author_url": "https://www.linkedin.com/in/ja-williams-529517187/", "updated_at": "2023-04-12", "created_at": "2022-06-15", "description": "This notebook provides an analysis of Major League Baseball moneylines from DraftKings.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Draft%20Kings/Draft_Kings_Get_MLB_Moneylines.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Draft%20Kings/Draft_Kings_Get_MLB_Moneylines.ipynb", "imports": ["naas", "requests", "pandas", "bs4.BeautifulSoup", "naas_drivers.emailbuilder", "datetime.datetime", "pytz"], "image_url": ""}, {"objectID": "ceb5a587fbb4c9f40cba42de520895d00c40bba339419b224bf452d40c83e02c", "tool": "Draft Kings", "notebook": "Get NBA Moneylines", "action": "", "tags": ["#draftkings", "#nba", "#betting", "#python", "#analytics", "#automation", "#sports", "#sports_betting", "#opendata", "#notification", "#email"], "author": "JA Williams", "author_url": "https://www.linkedin.com/in/ja-williams-529517187/", "updated_at": "2023-04-12", "created_at": "2022-04-13", "description": "This notebook provides an analysis of NBA Moneylines from Draft Kings to help you make informed betting decisions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Draft%20Kings/Draft_Kings_Get_NBA_Moneylines.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Draft%20Kings/Draft_Kings_Get_NBA_Moneylines.ipynb", "imports": ["naas", "requests", "pandas", "bs4.BeautifulSoup", "naas_drivers.emailbuilder", "datetime.datetime", "pytz"], "image_url": ""}, {"objectID": "543ef2600b507345bc7b6cd2db8351aaed78fab51441bd3fb69d88cc5ec3f5e2", "tool": "EM-DAT", "notebook": "Natural disasters", "action": "", "tags": ["#em-dat", "#emdat", "#opendata", "#analytics", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-28", "description": "In 1988, the Centre for Research on the Epidemiology of Disasters (CRED) launched the Emergency Events Database (EM-DAT). [EM-DAT](https://www.emdat.be/) was created with the initial support of the World Health Organisation (WHO) and the Belgian Government.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/EM-DAT/EM-DAT_natural_disasters.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/EM-DAT/EM-DAT_natural_disasters.ipynb", "imports": ["pandas", "plotly.express"], "image_url": ""}, {"objectID": "30d15767a0d67fbb7c1aa3b0d8047bf5075074c348588a11dc34cfdf9bf52161", "tool": "Elasticsearch", "notebook": "Connect to server", "action": "", "tags": ["#elasticsearch", "#elastic", "#search", "#snippet", "#operations"], "author": "Ebin Paulose", "author_url": "https://www.linkedin.com/in/ebinpaulose/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "### 1. Prerequisites", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Elasticsearch/Elasticsearch_Connect_to_server.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Elasticsearch/Elasticsearch_Connect_to_server.ipynb", "imports": ["elasticsearchconnector.ElasticsearchConnector"], "image_url": ""}, {"objectID": "ba28d491fd759da0887e597f60ac8ca271d9e76837bd293f62d2557875a1d594", "tool": "Excel", "notebook": "Apply Custom Styles", "action": "", "tags": ["#excel", "#openpyxl", "#font", "#border", "#background", "#naas", "#finance", "#snippet"], "author": "S\u00e9bastien Grech", "author_url": "https://www.linkedin.com/in/s%C3%A9bastien-grech-4433a7150/", "updated_at": "2023-04-12", "created_at": "2023-02-07", "description": "This notebook provides instructions on how to apply custom styles to an Excel spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_Apply_Custom_Styles.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_Apply_Custom_Styles.ipynb", "imports": ["naas", "openpyxl.load_workbook", "openpyxl.cell.Cell", "openpyxl.styles.Color, PatternFill, Font, Border", "openpyxl.styles.borders.Border, Side"], "image_url": ""}, {"objectID": "d90301be264b3cf72aeee61ab98051d15815adda6f6e494fc0587923ba51118d", "tool": "Excel", "notebook": "Consolidate files", "action": "", "tags": ["#excel", "#pandas", "#read", "#save", "#naas", "#asset", "#finance", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook provides a comprehensive guide to consolidating multiple Excel files into one.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_Consolidate_files.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_Consolidate_files.ipynb", "imports": ["pandas", "naas"], "image_url": ""}, {"objectID": "217fff1a4dbbe5cdb391c88dd2e230eef12ddbf46fc6b2a4b7e05c49db3758fb", "tool": "Excel", "notebook": "Get dynamic active range", "action": "", "tags": ["#excel", "#openpyxl", "#active-range", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-24", "description": "This notebook provides a method for dynamically retrieving the active range of an Excel worksheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_Get_dynamic_active_range.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_Get_dynamic_active_range.ipynb", "imports": ["openpyxl.load_workbook", "openpyxl.utils.get_column_letter"], "image_url": ""}, {"objectID": "b92ea8d1185531f94864792601a94a86b90d79e8d8da49977d1ffdc87a6cce41", "tool": "Excel", "notebook": "List sheets in workbook", "action": "", "tags": ["#excel", "#list", "#sheets", "#workbook", "#data", "#analysis"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook will list the sheet's name in an Excel workbook.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_List_sheets_in_workbook.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_List_sheets_in_workbook.ipynb", "imports": ["openpyxl", "os"], "image_url": ""}, {"objectID": "32e6a2bbb504fb622cc153607a48c61677401ab357a4d2117b6b3820be4fbd69", "tool": "Excel", "notebook": "Read file", "action": "", "tags": ["#excel", "#pandas", "#read", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook reads an Excel file and allows users to manipulate the data within it.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_Read_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_Read_file.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "89dbd7dbd81efb97de7af6a3f612379e28d249f769af1c6aaec979867b4c796b", "tool": "Excel", "notebook": "Save file", "action": "", "tags": ["#excel", "#pandas", "#save", "#opendata", "#yahoofinance", "#naas_drivers", "#finance", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook allows users to save their Excel files quickly and easily.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_Save_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_Save_file.ipynb", "imports": ["pandas", "naas_drivers.yahoofinance"], "image_url": ""}, {"objectID": "82f6147c6bace8c4fe20f3c99ff957454a2ff4a331301a7201a9f3550feb508b", "tool": "FAO", "notebook": "Consumer price indice", "action": "", "tags": ["#fao", "#opendata", "#food", "#analytics", "#plotly"], "author": "Dereck DANIEL", "author_url": "https://github.com/DANIEL-Dereck", "updated_at": "2023-04-12", "created_at": "2021-06-10", "description": "This notebook provides an analysis of the changes in consumer prices over time as measured by the Food and Agriculture Organization's Consumer Price Index.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FAO/FAO_Consumer_price_indice.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FAO/FAO_Consumer_price_indice.ipynb", "imports": ["requests, zipfile, io", "matplotlib.pyplot", "naas_drivers", "pandas", "plotly.express", "csv", "codecs", "plotly.graph_objects"], "image_url": ""}, {"objectID": "097bbecb865851c847e60decdb392721feca4070a51c0ee2a95069f1b539e0a7", "tool": "FEC", "notebook": "Creer un dashboard PowerBI", "action": "", "tags": ["#fec", "#powerbi", "#dataviz", "#analytics", "#finance"], "author": "Alexandre STEVENS", "author_url": "https://www.linkedin.com/in/alexandrestevenspbix/", "updated_at": "2023-04-12", "created_at": "2021-08-17", "description": "This notebook provides instructions for creating a PowerBI dashboard to visualize Federal Election Commission (FEC) data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Creer_un_dashboard_PowerBI.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Creer_un_dashboard_PowerBI.ipynb", "imports": ["pandas", "datetime.datetime, timedelta", "os", "re", "naas", "json"], "image_url": ""}, {"objectID": "05f3e5c7ae59b593be99118e8041cef4b465f18e633b6f8afc3b889762a1bb58", "tool": "FEC", "notebook": "Lecture des fichiers", "action": "", "tags": ["#fec", "#lecture", "#fichiers", "#python", "#data", "#analyse"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to read files with Python and how it is usefull for organization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Lecture_des_fichiers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Lecture_des_fichiers.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "ae95a038ed1b23ff84eb40e19039601cba8278c3d969caa4124defd23ecdca63", "tool": "FEC", "notebook": "Visualiser Bilan Treemap", "action": "", "tags": ["#fec", "#plotly", "#treemap", "#snippet", "#dataviz"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-31", "description": "Ce notebook affiche les \u00e9l\u00e9ments du bilan sous forme de graphique treemap. Le graphique \"treemap\" est tr\u00e8s utile pour montrer la r\u00e9partition des actifs et des passifs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Visualiser_Bilan_Treemap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Visualiser_Bilan_Treemap.ipynb", "imports": ["plotly.graph_objects", "plotly.subplots.make_subplots", "pandas", "naas"], "image_url": ""}, {"objectID": "f7c01654a85e3e8cfadc6c93c2c38c27b13bf29df99a6094094bae4462f19abc", "tool": "FEC", "notebook": "Visualiser Charges Horizontal Barchart", "action": "", "tags": ["#fec", "#plotly", "#horizontalbarchart", "#visualisation", "#charges", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-23", "description": "Ce notebook vous permettra de visualiser les charges de votre entreprise \u00e0 l'aide d'un barchart horizontal.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Visualiser_Charges_Horizontal_Barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Visualiser_Charges_Horizontal_Barchart.ipynb", "imports": ["plotly.graph_objects", "pandas", "naas"], "image_url": ""}, {"objectID": "6741d446a829e89f2b656fe139e0319b2cd7c49feb3643bb10209e4dfdfe9d2d", "tool": "FEC", "notebook": "Visualiser Comparer Ventes Line Chart", "action": "", "tags": ["#fec", "#plotly", "#naas", "#snippet", "#operations", "#linechart"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-02-08", "description": "Ce notebook vous permettra de visualiser et comparer les ventes de votre entreprise pour les p\u00e9riodes N et N-1 \u00e0 l'aide de deux courbes de tendance. Vous pourrez facilement voir les tendances et les diff\u00e9rences entre les deux p\u00e9riodes pour prendre des d\u00e9cisions \u00e9clair\u00e9es pour am\u00e9liorer vos ventes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Visualiser_Comparer_Ventes_Line_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Visualiser_Comparer_Ventes_Line_Chart.ipynb", "imports": ["plotly.graph_objects", "plotly.subplots.make_subplots", "pandas", "naas", "random"], "image_url": ""}, {"objectID": "d73ae271b1557432c42c76c41c62f94628dd97120e11e41b0f1c0f0eee97a9c5", "tool": "FEC", "notebook": "Visualiser Tr\u00e9sorerie Barline Chart", "action": "", "tags": ["#fec", "#plotly", "#naas", "#snippet", "#operations", "#barline"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-02-08", "description": "Ce notebook vous permettra de visualiser la tr\u00e9sorerie de votre entreprise \u00e0 l'aide d'un diagramme de barres. Vous pourrez facilement suivre les entr\u00e9es et les sorties d'argent, ce qui vous aidera \u00e0 mieux comprendre la situation financi\u00e8re de votre entreprise.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Visualiser_Tr%C3%A9sorerie_Barline_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Visualiser_Tr%C3%A9sorerie_Barline_Chart.ipynb", "imports": ["plotly.graph_objects", "plotly.subplots.make_subplots", "pandas", "naas", "random"], "image_url": ""}, {"objectID": "3d5d98e21d25b8ffe3b8c6deb3b9d8beecba5a65754590a020591220885efdd0", "tool": "FED", "notebook": "Visualize Inflation Rate", "action": "", "tags": ["#fed", "#inflation_rate", "#vizualization", "#plotly"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-04-12", "created_at": "2023-04-06", "description": "This notebook vizualize the inflation rate of the US using plotly and fred api", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FED/FED_Visualize_Inflation_Rate.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FED/FED_Visualize_Inflation_Rate.ipynb", "imports": ["naas", "pandas", "plotly.express", "fredapi.Fred", "fredapi.Fred"], "image_url": ""}, {"objectID": "3bf073466b39d2c379ef627157f0279dece8ae6a7edb3238fc59b4282a76417a", "tool": "FTP", "notebook": "S Connect", "action": "", "tags": ["#ftp", "#ftps", "#file", "#naas_drivers", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook provides a guide to setting up an FTP connection to securely transfer files between two computers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FTP/FTPS_Connect.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FTP/FTPS_Connect.ipynb", "imports": ["naas_drivers.ftp"], "image_url": ""}, {"objectID": "69af686c106175459bb5ebbe8514346705fe801d27fdfd2f8ce9956d411fc755", "tool": "FTP", "notebook": "Connect", "action": "", "tags": ["#ftp", "#file", "#naas_drivers", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook provides instructions on how to connect to an FTP server.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FTP/FTP_Connect.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FTP/FTP_Connect.ipynb", "imports": ["naas_drivers.ftp"], "image_url": ""}, {"objectID": "b17b56d2b058f53c97a81c8cd360ad2fcc3a6f08d49c9a493fa8a6fd92127173", "tool": "FTP", "notebook": "Get file", "action": "", "tags": ["#ftp", "#file", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook retrieves a file from an FTP server.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FTP/FTP_Get_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FTP/FTP_Get_file.ipynb", "imports": ["naas_drivers.ftp"], "image_url": ""}, {"objectID": "a228c9862a9e8eb6ff9cad6f815931ec3d02927ee30a1123dfe647d9836b2b05", "tool": "FTP", "notebook": "Send file", "action": "", "tags": ["#ftp", "#file", "#naas_drivers", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook allows users to securely transfer files to a remote server using the File Transfer Protocol (FTP).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FTP/FTP_Send_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FTP/FTP_Send_file.ipynb", "imports": ["naas_drivers.ftp"], "image_url": ""}, {"objectID": "d81834f3139bb9d206b4f2e2248280d5de152a4eff80dd9c2012832b7080367f", "tool": "Faker", "notebook": "Anonymize Address from dataframe", "action": "", "tags": ["#faker", "#operations", "#snippet", "#database", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-09", "description": "This notebook provides a way to anonymize address data from a dataframe using the Faker library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Faker/Faker_Anonymize_Address_from_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Faker/Faker_Anonymize_Address_from_dataframe.ipynb", "imports": ["faker.Faker", "faker.Faker", "pandas"], "image_url": ""}, {"objectID": "58a9c428e21814107d47582ef149ba3f79b5f26652ec3e6540d894662f3dd956", "tool": "Faker", "notebook": "Anonymize Personal Names from dataframe", "action": "", "tags": ["#faker", "#operations", "#snippet", "#database", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-09", "description": "This notebook provides a way to anonymize personal names from a dataframe using the Faker library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Faker/Faker_Anonymize_Personal_Names_from_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Faker/Faker_Anonymize_Personal_Names_from_dataframe.ipynb", "imports": ["faker.Faker", "faker.Faker", "pandas"], "image_url": ""}, {"objectID": "4580c539c8dc22fe627c347782220eb1211d51d3ac534c0074061911c83afbab", "tool": "Folium", "notebook": "Add markers on map", "action": "", "tags": ["#folium", "#map", "#markers", "#snippet"], "author": "Florent Ravenel", "author_url": "www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook demonstrates how to add markers on a map using `folium`.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Folium/Folium_Add_markers_on_map.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Folium/Folium_Add_markers_on_map.ipynb", "imports": ["folium", "folium"], "image_url": ""}, {"objectID": "cccf6467c3889278ee01c94fc28e2e0c58a81c12959ef887209eb2206a85971c", "tool": "Folium", "notebook": "Build route maps", "action": "", "tags": ["#folium", "#maps", "#routes", "#python", "#visualization", "#data"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will show how to use Folium to build route maps.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Folium/Folium_Build_route_maps.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Folium/Folium_Build_route_maps.ipynb", "imports": ["folium", "folium"], "image_url": ""}, {"objectID": "0b4cee6175ae01bdba70e486dae08388db62860db483724d3feb06a0fbe59a94", "tool": "Folium", "notebook": "Create map", "action": "", "tags": ["#folium", "#map", "#leaflet", "#snippet"], "author": "Florent Ravenel", "author_url": "www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook creates a map with Folium and Leaflet.js.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Folium/Folium_Create_map.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Folium/Folium_Create_map.ipynb", "imports": ["folium", "folium"], "image_url": ""}, {"objectID": "92843af029dccefb840512cc32f2146422288d20bf883643c3012da6da46c604", "tool": "Forecast", "notebook": "List all assignments", "action": "", "tags": ["#forecast", "#assignments", "#api", "#list", "#python", "#get"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-08", "created_at": "2023-08-08", "description": "This notebook will list all assignments from the forecast API. Forecast is a service that connects to harvest and allows you to plan for allocations to harvest projects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Forecast/Forecast_List_all_assignments.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Forecast/Forecast_List_all_assignments.ipynb", "imports": ["requests", "pandas", "naas", "datetime"], "image_url": ""}, {"objectID": "ec42b7671812e53369957d3aed72789a828f597c008d8b93070df4e423e92c8c", "tool": "Forecast", "notebook": "List all clients", "action": "", "tags": ["#forecast", "#clients", "#api", "#list", "#python", "#get"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-08", "created_at": "2023-08-08", "description": "This notebook will list all clients from the forecast API. Forecast is a service that connects to harvest and allows you to plan for allocations to harvest projects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Forecast/Forecast_List_all_clients.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Forecast/Forecast_List_all_clients.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "1e3981cbb25a39575b8a02a7f99ced455da1778da4ea90bffc9e80a5fc67ae76", "tool": "Forecast", "notebook": "List all people", "action": "", "tags": ["#forecast", "#people", "#api", "#list", "#python", "#get"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-07", "created_at": "2023-08-07", "description": "This notebook will list all people from the forecast API. Forecast is a service that connects to harvest and allows you to plan for allocations to harvest projects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Forecast/Forecast_List_all_people.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Forecast/Forecast_List_all_people.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "f0fba9e2e8ab797314e1454cd85c86759be2856b0c0fffa55a916148ae49d9b3", "tool": "Forecast", "notebook": "List all projects", "action": "", "tags": ["#forecast", "#projects", "#api", "#list", "#python", "#get"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-08", "created_at": "2023-08-08", "description": "This notebook will list all projects from the forecast API. Forecast is a service that connects to harvest and allows you to plan for allocations to harvest projects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Forecast/Forecast_List_all_projects.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Forecast/Forecast_List_all_projects.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "25c79c072793ed9689fec890977052fa9dd7977df1e8fb6e9832aa77df17f10f", "tool": "Formant", "notebook": "Query Device Network", "action": "", "tags": ["#formant", "#matplotlib", "#notification", "#email", "#image"], "author": "Nicolas Binford", "author_url": "https://www.linkedin.com/in/nicolasbinford", "updated_at": "2023-05-25", "created_at": "2023-05-25", "description": "This notebook queries network data over a period of time from a Formant device, graphs it, and emails the images.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Formant/Formant_Query_Device_Network.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Formant/Formant_Query_Device_Network.ipynb", "imports": ["datetime.datetime, timedelta", "dateutil.parser", "numpy", "matplotlib.pyplot", "os", "naas", "formant.sdk.cloud.v2.Client", "formant.sdk.cloud.v2.formant_admin_api_client.models.device_query.(", "formant.sdk.cloud.v2.formant_admin_api_client.models.event_query.(", "formant.sdk.cloud.v2.formant_admin_api_client.models.event_list_response.(", "formant.sdk.cloud.v2.formant_query_api_client.models.query.Query"], "image_url": ""}, {"objectID": "afb1d171e3d6d01f64e538e5218cb05bcb151bbf7b3bdc4aede393413b6795d8", "tool": "Geopy", "notebook": "Calculate distance between two locations in kilometers", "action": "", "tags": ["#geopy", "#distance", "#navigation", "#snippet"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to calculate distance between two locations in kilometers using `geopy`.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Calculate_distance_between_two_locations_in_km.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Calculate_distance_between_two_locations_in_km.ipynb", "imports": ["geopy.geocoders.Nominatim", "geopy.distance.geodesic"], "image_url": ""}, {"objectID": "63101b2ad458f9d789b07b0da6879d15330e9333534fcf1bfa68256633388959", "tool": "Geopy", "notebook": "Calculate distance between two locations in miles", "action": "", "tags": ["#geopy", "#distance", "#navigation", "#snippet"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to calculate distance between two locations in miles using `geopy`.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Calculate_distance_between_two_locations_in_miles.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Calculate_distance_between_two_locations_in_miles.ipynb", "imports": ["geopy.geocoders.Nominatim", "geopy.distance.geodesic"], "image_url": ""}, {"objectID": "993ce0d908ba89f3ea2afcdec012b379878997c9398eb0fd49ef9cfb39647805", "tool": "Geopy", "notebook": "Display markers on map from addresses", "action": "", "tags": ["#geopy", "#folium", "#operations", "#navigation"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to display markers on a map from addresses using `geopy` and `folium`.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Display_markers_on_map.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Display_markers_on_map.ipynb", "imports": ["geopy.geocoders.Nominatim", "folium", "folium"], "image_url": ""}, {"objectID": "1c652e1306432bebf00b0ff980057b2b61e37ea66a9f78d36593e441fadda873", "tool": "Geopy", "notebook": "Display route itinerary between two locations", "action": "", "tags": ["#geopy", "#folium", "#polyline", "#googlemaps", "#itinerary", "#navigation"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to display a route initnerary between two locations using `geopy`, `folium`, `polyline` and Google Maps API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Display_route_itinerary_between_two_locations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Display_route_itinerary_between_two_locations.ipynb", "imports": ["geopy.geocoders.Nominatim", "polyline", "folium", "naas", "requests"], "image_url": ""}, {"objectID": "63fd46f3d47b86684983e648b8ce1b52533ad5e25df8521927f614d42973c09e", "tool": "Geopy", "notebook": "Get address from coordinates", "action": "", "tags": ["#geopy", "#coordinates", "#address", "#navigation", "#snippet"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to utilize Geopy to convert a location(latitude and longitude) to its corresponding address.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Get_address_from_coordinates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Get_address_from_coordinates.ipynb", "imports": ["geopy.geocoders.Nominatim"], "image_url": ""}, {"objectID": "e58363280d4ff558e10c90bb9294d8ad7f0467db115d5dca1be059dc911939f5", "tool": "Geopy", "notebook": "Get coordinates from address", "action": "", "tags": ["#geopy", "#coordinates", "#address", "#navigation", "#snippet"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to utilize Geopy to the coordinates(longitude and latitude) of a given address.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Get_coordinates_from_address.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Get_coordinates_from_address.ipynb", "imports": ["geopy.geocoders.Nominatim"], "image_url": ""}, {"objectID": "b8a92a0e4b6e40db304564f999566443fb35e93df716ab4be5021aabba8230ee", "tool": "GitHub", "notebook": "Add new issues as page in Notion database", "action": "", "tags": ["#github", "#notion", "#operations", "#automation"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-05-12", "description": "This notebook allows users to add new GitHub issues as pages in a Notion database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Add_new_issues_as_page_in_Notion_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Add_new_issues_as_page_in_Notion_database.ipynb", "imports": ["naas", "naas_drivers.notion, github"], "image_url": ""}, {"objectID": "bcda82e2ccc375448f59bfea7ab1cc6a9c5e3388650e69034914e132319a5924", "tool": "GitHub", "notebook": "Add new member to team", "action": "", "tags": ["#github", "#teams", "#snippet", "#operations", "#invitations"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-05-07", "description": "This notebook provides instructions on how to add a new member to a GitHub team.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Add_new_member_to_team.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Add_new_member_to_team.ipynb", "imports": ["requests", "naas_drivers.github", "pandas", "naas"], "image_url": ""}, {"objectID": "10bd58b431807c01460f0309cd7ee2b2a7e2a61e38cbabc60c0fc2b439b9d309", "tool": "GitHub", "notebook": "Add or update team membership for a user", "action": "", "tags": ["#github", "#teams", "#members", "#api", "#rest", "#python"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-26", "created_at": "2023-04-18", "description": "This notebook add or update team membership for a user.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Add_or_update_team_membership_for_a_user.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Add_or_update_team_membership_for_a_user.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "b8cc352b30977a358e1bb8128a3462f0e6385185fe45c76b5b5a83a702223d3f", "tool": "GitHub", "notebook": "Clone open branches from repository on my local", "action": "", "tags": ["#github", "#snippet", "#operations", "#repository", "#efficiency"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook streamlines your workflow by cloning open branches from a GitHub repository to your local machine, renaming the repository to match the branch name, and switching to the respective branch. This approach enhances efficiency by enabling you to work on multiple branches simultaneously without the need to constantly switch, thus avoiding conflicts. Before using this on Naas, ensure your SSH is properly configured (you can use the Naas_Configure_SSH.ipynb template for this).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Clone_open_branches_from_repository_on_my_local.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Clone_open_branches_from_repository_on_my_local.ipynb", "imports": ["os", "naas", "pandas", "requests"], "image_url": ""}, {"objectID": "9a285091900a306e1d94106e8130989f033c65589f2bc28dc7515436d73a5af4", "tool": "GitHub", "notebook": "Clone repository", "action": "", "tags": ["#github", "#snippet", "#operations", "#repository"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-09", "created_at": "2022-12-07", "description": "**References:**\n- [GitHub Documentation - Cloning a repository](https://docs.github.com/en/github/creating-cloning-and-archiving-repositories/cloning-a-repository)", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Clone_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Clone_repository.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "ff694fb2b2ebce38feccd3e1bef21019cdb9994ae3cf4f6fdc0ab7e317c15f22", "tool": "GitHub", "notebook": "Clone repository and switch branch", "action": "", "tags": ["#github", "#clone", "#repository", "#branch", "#switch", "#git"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-09", "created_at": "2023-05-09", "description": "This notebook clones a branche from a GitHub repository to your local machine, rename the repository with the branch name, and switch to it to the designated branch. This approach enhances efficiency by enabling you to work on multiple branches simultaneously without the need to constantly switch, thus avoiding conflicts. Before using this on Naas, ensure your SSH is properly configured (you can use the Naas_Configure_SSH.ipynb template for this).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Clone_repository_and_switch_branch.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Clone_repository_and_switch_branch.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "6bba57317ecb03136235cc932153d2657c0ddffeb2ea0290584824b427ae4d76", "tool": "GitHub", "notebook": "Close issue", "action": "", "tags": ["#github", "#issues", "#update", "#rest", "#api", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2022-03-18", "description": "This notebook explains how to close an issue on GitHub using the REST API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Close_issue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Close_issue.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "243aca01f02c1bd1deb2c0157c3fce1ea04ac03c9e2f8df73d9cd04128dafc90", "tool": "GitHub", "notebook": "Create Repo", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet"], "author": "Kanishk Pareek", "author_url": "https://in.linkedin.com/in/kanishkpareek/", "updated_at": "2023-04-12", "created_at": "2023-02-28", "description": "This notebook provides instructions on how to create a repository on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_Repo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_Repo.ipynb", "imports": ["requests", "json"], "image_url": ""}, {"objectID": "cffce74b26b67e98eceee05e167b0db356b2dd610bd6e82d7a8e28e2c50398a9", "tool": "GitHub", "notebook": "Create an issue comment", "action": "", "tags": ["#github", "#issue", "#comment", "#api", "#python", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2023-05-26", "description": "This notebook shows how to add a comment to an issue on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_an_issue_comment.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_an_issue_comment.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "d735705c15fc17370b8e6a4cb688184c65210cbb249e2466dfa2b754b47b07b9", "tool": "GitHub", "notebook": "Create issue", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides instructions on how to create an issue on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_issue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_issue.ipynb", "imports": ["github.Github"], "image_url": ""}, {"objectID": "58d4c2b5a700d444c161aa052156ca47ffb7642a2e44c771125cac9a6fe04edc", "tool": "GitHub", "notebook": "Create leaderboard of contributors", "action": "", "tags": ["#github", "#repos", "#commits", "#stats", "#naas_drivers", "#leaderboard", "#commitsPoints"], "author": "Suhas B", "author_url": "https://www.linkedin.com/in/suhasbrao/", "updated_at": "2023-04-12", "created_at": "2023-02-01", "description": "## Input", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_leaderboard_of_contributors.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_leaderboard_of_contributors.ipynb", "imports": ["pandas", "plotly.express", "naas_drivers.github", "naas", "requests", "urllib.parse.urlencode"], "image_url": ""}, {"objectID": "8ae2c7c1e9a984b87050a86432e0e8d09f71f62e51e2bb84533b97ad4494e04d", "tool": "GitHub", "notebook": "Create newsletter based on repository activity", "action": "", "tags": ["#tool", "#naas_drivers", "#naas", "#scheduler", "#asset", "#snippet", "#automation", "#ai", "#newsletter"], "author": "Suhas B", "author_url": "https://www.linkedin.com/in/suhasbrao/", "updated_at": "2023-04-12", "created_at": "2023-02-28", "description": "This notebook allows users to create newsletters based on their repository activity on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_newsletter_based_on_repository_activity.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_newsletter_based_on_repository_activity.ipynb", "imports": ["naas_drivers.github", "naas", "markdown2", "IPython.core.display.display, HTML", "datetime", "pandas", "requests", "urllib.parse.urlencode"], "image_url": ""}, {"objectID": "13d50e7c0ca00c6a1963a5a2180ad159bd9cd0db2fd8143fbe18ca655d99dc4a", "tool": "GitHub", "notebook": "Create pull request", "action": "", "tags": ["#github", "#pygithub", "#pullrequest", "#create", "#assign", "#issue"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook creates a pull request using pygithub library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_pull_request.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_pull_request.ipynb", "imports": ["github", "github", "naas"], "image_url": ""}, {"objectID": "45e3c14a696be711aaa32ba00141daa87f830e1d23755fa0a4974ebf66cc81ef", "tool": "GitHub", "notebook": "Create repository on personal account", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet"], "author": "Kanishk Pareek", "author_url": "https://in.linkedin.com/in/kanishkpareek/", "updated_at": "2023-04-12", "created_at": "2022-10-04", "description": "This notebook provides instructions on how to create a repository on a personal GitHub account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_repository_on_personal_account.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_repository_on_personal_account.ipynb", "imports": ["requests", "json"], "image_url": ""}, {"objectID": "7c337804978be615c8e4cf519d6575a8e16fe0b28e5c250c52393e3a5588e4d5", "tool": "GitHub", "notebook": "Delete an issue comment", "action": "", "tags": ["#github", "#issue", "#comment", "#api", "#python", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2023-05-26", "description": "This notebook shows how to delete a comment to an issue on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Delete_an_issue_comment.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Delete_an_issue_comment.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "dbff6f5f2fa8547e5d0a19beb2643be87b924ee91e01121e3d37985bac070cd8", "tool": "GitHub", "notebook": "Download Excel file from URL", "action": "", "tags": ["#github", "#excel", "#download", "#url", "#file", "#python"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook explains how to download an Excel file stored on a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Download_Excel_file_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Download_Excel_file_from_URL.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "328cf85beb39894413fcc4034f6c1a7deb5729e38b294307534bf49013c42ba5", "tool": "GitHub", "notebook": "Download file from url", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-24", "created_at": "2022-03-18", "description": "This notebook provides instructions on how to download a file from a URL using GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Download_file_from_url.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Download_file_from_url.ipynb", "imports": ["requests", "naas", "uuid", "urllib.parse"], "image_url": ""}, {"objectID": "1002d8195ec68aad7c2c4d45777ae51f859a5f5aaac8f2e7596fbf46203b65ff", "tool": "GitHub", "notebook": "Download repository from URL", "action": "", "tags": ["#github", "#download", "#repository", "#url", "#api", "#zip"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-10", "description": "This notebook explains how to download a repository from a URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Download_repository_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Download_repository_from_URL.ipynb", "imports": ["requests", "urllib", "os", "zipfile"], "image_url": ""}, {"objectID": "ac33d518bc759838d5a1b8a6392baae861e48fdde87d5d10539c3e8768ea2346", "tool": "GitHub", "notebook": "Follow stargazers trend", "action": "", "tags": ["#github", "#stars", "#stargazers", "#naas_drivers", "#operations", "#analytics", "#html", "#plotly", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook creates a linechart to follow the trend of stars received on a specific repository. A csv, html and png files will be created as output with the possibility to be shared with a naas asset link.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Follow_stargazers_trend.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Follow_stargazers_trend.ipynb", "imports": ["pandas", "datetime.datetime", "plotly.graph_objects", "naas_drivers.github", "naas"], "image_url": ""}, {"objectID": "320908ffbe4931be40be2e749cd53cef0ae7448e70673b5b014314e7535adf59", "tool": "GitHub", "notebook": "Get DataFrame with issue estimate from project view", "action": "", "tags": ["#github", "#dataframe", "#beautifulsoup", "#projectview", "#scraping", "#python"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook demonstrates how to retrieve a dataframe containing issue estimates from the project view using BeautifulSoup. Since GitHub's API doesn't offer a way to fetch issue estimates directly, this method allows us to obtain these estimates and generate statistics by assignee and iteration. To use this template, you must create a view with columns in the following order:\n- Issue Title\n- Assginees\n- Estimate\n- LinkedIn pull request", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_DataFrame_with_issue_estimate_from_project_view.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_DataFrame_with_issue_estimate_from_project_view.ipynb", "imports": ["requests", "bs4.BeautifulSoup", "pandas", "IPython.display.display"], "image_url": ""}, {"objectID": "2d6e1a35712e37dcf78b873d165069cce01361f5c3800ddca0f1455a215c6bfd", "tool": "GitHub", "notebook": "Get Traffic Clones on repository", "action": "", "tags": ["#github", "#api", "#traffic", "#clones", "#plotly", "#linechart"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-08", "description": "This notebook will show how to get traffic clones on a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_Traffic_Clones_on_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_Traffic_Clones_on_repository.ipynb", "imports": ["requests", "naas", "pprint.pprint", "pandas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "f9bebb30e5a9beff438ea68ecfd4766b58d80a7990a9a745ed628ab82c295b14", "tool": "GitHub", "notebook": "Get Traffic Views on repository", "action": "", "tags": ["#github", "#api", "#traffic", "#views", "#plotly", "#linechart", "#analytics"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-16", "description": "This notebook will show how to get traffic views on a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_Traffic_Views_on_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_Traffic_Views_on_repository.ipynb", "imports": ["requests", "naas", "pprint.pprint", "pandas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "c8a8977c13770d7cc1a9709d463a6c9b394b327ba768a497ede1e05dda40b7d7", "tool": "GitHub", "notebook": "Get a repository", "action": "", "tags": ["#github", "#pygithub", "#repository", "#get", "#rest", "#api"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-05", "description": "This notebook will show how to get a repository using pygithub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_a_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_a_repository.ipynb", "imports": ["naas", "github"], "image_url": ""}, {"objectID": "1626bc2443cb5ef3c6ac18d27f82fe1dfcdbc8845c38d45ca30b4f7eeaf7dbf2", "tool": "GitHub", "notebook": "Get active projects", "action": "", "tags": ["#github", "#projects", "#operations", "#snippet", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides an overview of active projects on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_active_projects.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_active_projects.ipynb", "imports": ["naas_drivers.github"], "image_url": ""}, {"objectID": "f89b6e0c45286c0029ace95a4357a4d498a9b31f5c1625082e26eb2ff82e1bf7", "tool": "GitHub", "notebook": "Get commits from repository", "action": "", "tags": ["#github", "#repos", "#commits", "#stats", "#naas_drivers", "#plotly", "#linechart", "#operations", "#analytics", "#dataframe", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-09", "description": "This notebook provides a tutorial on how to retrieve a list of commits for a specific repository on GitHub using the GitHub API. It covers how to set up a personal access token for accessing the API, how to get commits using naas_drivers.github. The output returned is a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_commits_from_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_commits_from_repository.ipynb", "imports": ["naas_drivers.github", "datetime.datetime", "naas"], "image_url": ""}, {"objectID": "4f2312393c84b6863a931e5e5af8c99bd0ea48b34dfeda84093855cca17b510e", "tool": "GitHub", "notebook": "List commits history from file path", "action": "", "tags": ["#github", "#commits", "#history", "#snippet", "#operations", "#tracking"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-03", "created_at": "2023-07-03", "description": "This notebook demonstrateshow to retrieve a list of commits containing a file path that exists in master branch.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_commits_history_from_file_path.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_commits_history_from_file_path.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "19d43ffdcf1cb2f75a558259f7cfc3eed25577effd5690eb7a64e81cfacc9da9", "tool": "GitHub", "notebook": "Get commits ranking from repository", "action": "", "tags": ["#github", "#repos", "#commits", "#stats", "#naas_drivers", "#plotly", "#linechart", "#operations", "#analytics", "#dataframe", "#html"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a way to view the commit rankings of a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_commits_ranking_from_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_commits_ranking_from_repository.ipynb", "imports": ["pandas", "plotly.express", "naas_drivers.github", "naas"], "image_url": ""}, {"objectID": "1128f006266221999d8fbaa49d9e373c698e9b5c08a0ecefbe8eaa41795d69ee", "tool": "GitHub", "notebook": "Get files added on pull request", "action": "", "tags": ["#github", "#pullrequest", "#files", "#merge", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-13", "description": "This notebook get the files added on a pull request using the GitHub API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_files_added_on_pull_request.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_files_added_on_pull_request.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "c8b1218b10d5fedf3def66d9c7037ad6ee1b3b7f9bdb949ea73cce5d41dcf544", "tool": "GitHub", "notebook": "Get files changed on pull request", "action": "", "tags": ["#github", "#pullrequest", "#files", "#api", "#python", "#git"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook get the list of files changed on a pull request using the GitHub API. Files changed could be 'added', 'renamed' or 'removed'.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_files_changed_on_pull_request.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_files_changed_on_pull_request.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "bb644c3ac7177413c1f9b04a3a8d8d2f6d337072807baf2ec8dbe0af0192458c", "tool": "GitHub", "notebook": "Get issues from repo", "action": "", "tags": ["#github", "#repos", "#issues", "#operations", "#analytics", "#dataframe", "#html", "#plotly"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows users to retrieve issues from a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_issues_from_repo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_issues_from_repo.ipynb", "imports": ["naas_drivers.github"], "image_url": ""}, {"objectID": "f8b2a5b06ad0b1bc4d25de7e3aa1130a926d75e334885b7f4ad7abe3b774087d", "tool": "GitHub", "notebook": "Get most starred repos", "action": "", "tags": ["#github", "#repos", "#stars", "#snippet"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190", "updated_at": "2023-04-12", "created_at": "2022-06-06", "description": "This notebook provides a list of the most popular GitHub repositories based on the number of stars they have received.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_most_starred_repos.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_most_starred_repos.ipynb", "imports": ["requests", "pandas", "plotly.express", "naas"], "image_url": ""}, {"objectID": "bd51601dc7146cccf78e53232a470ddde08272706420c31e7494698e0fe8b38e", "tool": "GitHub", "notebook": "Get open pull requests", "action": "", "tags": ["#github", "#repos", "#pulls", "#PR", "#operations", "#analytics", "#plotly", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook retrieves pull requests from a repository URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_open_pull_requests.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_open_pull_requests.ipynb", "imports": ["naas_drivers.github", "naas"], "image_url": ""}, {"objectID": "567fd994f272de8dda30cabbcd7b893fea10b7cd949e94decd11cfa77224af3e", "tool": "GitHub", "notebook": "Get profile from user", "action": "", "tags": ["#github", "#user", "#profile", "#operations", "#snippet", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a way to retrieve a user's profile information from GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_profile_from_user.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_profile_from_user.ipynb", "imports": ["naas_drivers.github"], "image_url": ""}, {"objectID": "131faef4977e217b5cc7c313edb1d08a280bd20881389b14ed6a925bc25a3bab", "tool": "GitHub", "notebook": "Get profiles from teams", "action": "", "tags": ["#github", "#team", "#operations", "#snippet", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows users to retrieve profiles from teams on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_profiles_from_teams.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_profiles_from_teams.ipynb", "imports": ["naas_drivers.github"], "image_url": ""}, {"objectID": "cff3ad5e2da30b6e823aef6421cf3d08a71a70e60c8fde077ba9952f06c9624e", "tool": "GitHub", "notebook": "Get team membership for a user", "action": "", "tags": ["#github", "#teams", "#members", "#rest", "#api", "#python", "#snippet"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-26", "created_at": "2023-04-18", "description": "This notebook get team membership for a user. It will return a dictionary with the state, role and url of the membership.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_team_membership_for_a_user.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_team_membership_for_a_user.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "8a639940269e34df28bbdefbea42c889370febabbb161f8d5d31cc5772689c93", "tool": "GitHub", "notebook": "Get weekly commits from repository", "action": "", "tags": ["#github", "#repos", "#commits", "#stats", "#naas_drivers", "#plotly", "#linechart", "#operations", "#analytics", "#dataframe", "#html"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a weekly summary of commits made to a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_weekly_commits_from_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_weekly_commits_from_repository.ipynb", "imports": ["pandas", "plotly.express", "naas_drivers.github", "naas"], "image_url": ""}, {"objectID": "5494d12097ff82773cb0889f21a3f00dc84f32169f334038fc77493d818710ef", "tool": "GitHub", "notebook": "List all pull requests", "action": "", "tags": ["#github", "#pygithub", "#repo", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook list all pull requests from a repository name using pygithub library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_all_pull_requests.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_all_pull_requests.ipynb", "imports": ["os", "json", "github.Github", "naas"], "image_url": ""}, {"objectID": "9c502c94394240a77a6261022e61b720843f587f1694bc5067f24e85ca04b1cf", "tool": "GitHub", "notebook": "List branches", "action": "", "tags": ["#github", "#branches", "#list", "#api", "#rest", "#python"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-26", "created_at": "2023-06-20", "description": "This notebook will list all branches from a given GitHub repository;", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_branches.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_branches.ipynb", "imports": ["naas", "pandas", "github.Github", "github.Github", "pprint.pprint"], "image_url": ""}, {"objectID": "8f69f5fa373908c7173719e4b762a4944449492ad6b68e4fff8be0a5650d9fe2", "tool": "GitHub", "notebook": "List branches with open PR", "action": "", "tags": ["#github", "#branches", "#list", "#api", "#rest", "#python", "#active"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-26", "created_at": "2023-06-26", "description": "This notebook will list branches with open PR from a given GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_branches_with_open_PR.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_branches_with_open_PR.ipynb", "imports": ["naas", "pandas", "requests", "pprint.pprint"], "image_url": ""}, {"objectID": "087ed8be214fa3812d0506587434b69b44b3c162378979f98d3ac937c1609f9d", "tool": "GitHub", "notebook": "List closed pull requests", "action": "", "tags": ["#github", "#pygithub", "#closedpr", "#repo", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook list closed pull requests from a repository name using pygithub library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_closed_pull_requests.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_closed_pull_requests.ipynb", "imports": ["os", "json", "github.Github", "naas"], "image_url": ""}, {"objectID": "0acd7acb64f20d87ed237d4c909f9743978f067f9d98836c6ff364c577fa8d3b", "tool": "GitHub", "notebook": "List issue comments", "action": "", "tags": ["#github", "#issue", "#comment", "#api", "#python", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2023-05-26", "description": "This notebook shows how to list comments from an issue on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_issue_comments.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_issue_comments.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "09d2ca4100cec4201ff843f1c383df5e6e7f88a4dc162fc65c8bf0d33675bd6e", "tool": "GitHub", "notebook": "List open pull requests", "action": "", "tags": ["#github", "#pygithub", "#repo", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook list open pull requests from a repository name using pygithub library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_open_pull_requests.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_open_pull_requests.ipynb", "imports": ["os", "json", "github.Github", "naas"], "image_url": ""}, {"objectID": "91d4843ef8544aef83848c962ab6e38be11682c7ef728a1a9e2f10abd65cae9e", "tool": "GitHub", "notebook": "List organization repositories", "action": "", "tags": ["#github", "#pygithub", "#list", "#organization", "#repositories"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-05", "description": "This notebook will show how to list organization repositories using pygithub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_organization_repositories.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_organization_repositories.ipynb", "imports": ["naas", "github"], "image_url": ""}, {"objectID": "9402c5818d40c9a1056603298a6ece7b054a8313e93aa96e3a08670d775334b7", "tool": "GitHub", "notebook": "List pending team invitations", "action": "", "tags": ["#github", "#teams", "#invitations", "#rest", "#api", "#list", "#snippet"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-19", "created_at": "2023-04-18", "description": "This notebook will show how to list pending team invitations using the GitHub REST API and will create a DataFrame as output. It can be used by organizations with multiple teams on GitHub to keep track of pending team invitations, ensuring that all team members are added to the appropriate teams and can collaborate effectively. It helps in managing team membership and permissions for efficient collaboration within the organization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_pending_team_invitations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_pending_team_invitations.ipynb", "imports": ["requests", "naas", "pandas", "pprint.pprint"], "image_url": ""}, {"objectID": "2afff9452829305d478206c7df493312ed90cc027380628a2fa35705dc1246a0", "tool": "GitHub", "notebook": "List stargazers from repository", "action": "", "tags": ["#github", "#stars", "#stargazers", "#naas_drivers", "#operations", "#analytics", "#html", "#plotly", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook provides a way to retrieve the list of users who have starred a given GitHub repository and save it into a csv file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_stargazers_from_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_stargazers_from_repository.ipynb", "imports": ["naas_drivers.github", "naas"], "image_url": ""}, {"objectID": "cbb03445c11c8235ed502fd4031d9c94f68d15a70486cc4eae08329f546df285", "tool": "GitHub", "notebook": "List team members", "action": "", "tags": ["#github", "#teams", "#members", "#rest", "#api", "#list", "#snippet"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-19", "created_at": "2023-04-18", "description": "This notebook will demonstrate how to list team members using the GitHub REST API and will create a DataFrame as output. It can be used by organizations or repository owners to manage their teams on GitHub by listing the current team members. It helps in keeping track of team members, their roles, and permissions, enabling organizations to efficiently manage their teams and ensure that the right users have the appropriate access.\n\nDataFrame returned:\n- login': Represents the username or login name of the GitHub user.\n- 'id': Represents the unique identifier assigned to the GitHub user.\n- 'node_id': Represents the unique identifier for the GitHub user's profile as a node in the GitHub GraphQL API.\n- 'avatar_url': Represents the URL of the avatar (profile picture) of the GitHub user.\n- 'gravatar_id': Represents the unique identifier associated with the GitHub user's Gravatar profile.\n- 'url': Represents the URL of the GitHub user's profile.\n- 'html_url': Represents the HTML URL of the GitHub user's profile.\n- 'followers_url': Represents the URL for retrieving the list of followers of the GitHub user.\n- 'following_url': Represents the URL for retrieving the list of users that the GitHub user is following.\n- 'gists_url': Represents the URL for retrieving the list of gists created by the GitHub user.\n- 'starred_url': Represents the URL for retrieving the list of repositories starred by the GitHub user.\n- 'subscriptions_url': Represents the URL for retrieving the list of repositories subscribed to by the GitHub user.\n- 'organizations_url': Represents the URL for retrieving the list of organizations the GitHub user is a member of.\n- 'repos_url': Represents the URL for retrieving the list of repositories owned by the GitHub user.\n- 'events_url': Represents the URL for retrieving the list of events related to the GitHub user's activity.\n- 'received_events_url': Represents the URL for retrieving the list of events received by the GitHub user.\n- 'type': Represents the type of GitHub user, which can be 'User' or 'Organization'.\n- 'site_admin': Represents a boolean value indicating if the GitHub user has administrative privileges (true) or not (false) in the associated organization or repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_team_members.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_team_members.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "8591114911bf4f214706b00f87ba2c2ac8b8ac4af35a244bee65923f75841c03", "tool": "GitHub", "notebook": "Peform basic actions", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides instructions on how to use GitHub to perform basic tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Peform_basic_actions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Peform_basic_actions.ipynb", "imports": ["git_lib.Git"], "image_url": ""}, {"objectID": "cd80d6b09a931a9e136faa98ec7db9b739b3d2f198222dc8b96f947b56d9cadc", "tool": "GitHub", "notebook": "Read issue", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides instructions on how to read and understand issues on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Read_issue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Read_issue.ipynb", "imports": ["github.Github", "pandas"], "image_url": ""}, {"objectID": "1d105e6fd6ce6afd43b108739842b18b3af440c768cd23db3fa62d9ddf6521e3", "tool": "GitHub", "notebook": "Remove directories with branches closed on my local", "action": "", "tags": ["#github", "#branches", "#list", "#api", "#rest", "#python", "#active"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook facilitates the removal of directories associated with branches on your local machine. If you need to clone and create directories based on active branches, you can use either of the following notebooks: GitHub_Clone_open_branches_from_repository_on_my_local or GitHub_Clone_repository_and_switch_branch.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Remove_directories_with_branches_closed_on_my_local.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Remove_directories_with_branches_closed_on_my_local.ipynb", "imports": ["naas", "pandas", "requests", "shutil", "os", "datetime.datetime, timedelta"], "image_url": ""}, {"objectID": "332448e5948d4198f461223f9937a1ce1cd7912fa7df229fa71a2f3121d80949", "tool": "GitHub", "notebook": "Remove member from team", "action": "", "tags": ["#github", "#teams", "#snippet", "#operations"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-05-07", "description": "This notebook provides instructions on how to remove a member from a GitHub team.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Remove_member_from_team.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Remove_member_from_team.ipynb", "imports": ["requests", "naas_drivers.github"], "image_url": ""}, {"objectID": "fdcbabe75aaf3e5fb4fdd20389fa8f467d45d1bdb07f1bdd792b851b3747da63", "tool": "GitHub", "notebook": "Remove team membership for a user", "action": "", "tags": ["#github", "#teams", "#members", "#remove", "#api", "#rest"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-26", "created_at": "2023-04-19", "description": "This notebook explains how to remove team membership for a user. It is usefull for organizations that need to manage their team memberships.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Remove_team_membership_for_a_user.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Remove_team_membership_for_a_user.ipynb", "imports": ["requests", "json"], "image_url": ""}, {"objectID": "34d8e5474a94719c1703516d66d3e99cbaaada2b84c29f116ea81516710e5783", "tool": "GitHub", "notebook": "Reopen issue", "action": "", "tags": ["#github", "#issues", "#update", "#rest", "#api", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2023-05-26", "description": "This notebook explains how to reopened an issue on GitHub using the REST API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Reopen_issue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Reopen_issue.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "3d075044a53de36f530c33cdb1aec8ba83ab4108b44d2584062e37c5344cb45e", "tool": "GitHub", "notebook": "Send contributor activity on slack", "action": "", "tags": ["#github", "#activity", "#update", "#api", "#snippet", "#operations", "#slack"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-28", "created_at": "2023-06-16", "description": "This notebook demonstrates how to send GitHub activity of a contributor of awesome notebook templates to Slack. It includes the sections below:\n- \u2705 **Templates created:** the total number of templates created (overall, by month, by week).\n- \ud83d\udc40 **In review:** the number of PRs ready reviewed. Make sure you made a comment with **\"Ready to review\"** inside the PR.\n- \ud83c\udfd7 **In progress:** the current PRs you are working on.\n- \ud83d\udccb **Backlog:** the issues you are assigned to with no PRs opened.\n\n*NB: Execution time may takes between 2 to 5 min.*", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Send_contributor_activity_on_slack.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Send_contributor_activity_on_slack.ipynb", "imports": ["os", "json", "datetime.datetime", "github.Github", "naas", "pandas", "requests", "naas_drivers.slack", "warnings"], "image_url": ""}, {"objectID": "9c57f872a50f25acbb10c6400142ac1e874a1c4b7d26c38e6efc0c4b819bb16f", "tool": "GitHub", "notebook": "Send stargazers to Google Sheets", "action": "", "tags": ["#github", "#stars", "#stargazers", "#googlesheets", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-23", "description": "This notebook will show how to send GitHub stargazers from a given repository to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Send_stargazers_to_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Send_stargazers_to_Google_Sheets.ipynb", "imports": ["naas_drivers.github, gsheet", "naas"], "image_url": ""}, {"objectID": "c10a991b52bbeb12828cfcc922d3d1126bc807071ecf6038d593adbe94fbc6e8", "tool": "GitHub", "notebook": "Send template maintainer monthly report", "action": "", "tags": ["#github", "#issues", "#merged", "#rest", "#api", "#snippet", "#operations", "#email", "#awesomenotebooks", "#maintainer"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook retrieves data to ascertain the sponsorships provided by Naas for template maintainers and dispatches a notification on every 7th day of the month, as well as the last three days. It incorporates the monthly count of issue closed with estimates, and the number of Pull Requests reviewed within the month.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Send_template_maintainer_monthly_report.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Send_template_maintainer_monthly_report.ipynb", "imports": ["pandas", "github.Github", "datetime.datetime, timezone", "requests", "bs4.BeautifulSoup", "IPython.display.display, HTML", "numpy", "datetime.datetime", "naas", "naas_drivers.naasauth, emailbuilder", "warnings"], "image_url": ""}, {"objectID": "7b2207634faad3e18e2a4179115d4b835a53bed640a16cccc0c7e8d740a7970f", "tool": "GitHub", "notebook": "Send templates created on a notebooks to Slack channel", "action": "", "tags": ["#github", "#templates", "#created", "#rest", "#api", "#snippet", "#operations", "#slack"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-11", "created_at": "2023-07-11", "description": "This notebook demonstrates how to send the templates created on GitHub to a specific Slack channel. It includes the sections below:\n\n- \u2705 **Templates created:** the total number of templates created (overall, by month, by week).\n- \ud83d\udcca **Bar chart:** a barchart of the templates created the last 8 weeks\n\n*NB: Execution time may takes between 1 to 4 min.*", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Send_templates_created_on_a_notebooks_to_Slack_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Send_templates_created_on_a_notebooks_to_Slack_channel.ipynb", "imports": ["github.Github", "naas", "pandas", "naas_drivers.slack", "plotly.graph_objects", "datetime.datetime, timedelta, date", "warnings"], "image_url": ""}, {"objectID": "7afaaedd1fb202006ad3861d87fc8671e703e8ab3af059d97fd4c95fc4e61601", "tool": "GitHub", "notebook": "Track issues on projects", "action": "", "tags": ["#github", "#repos", "#issues", "#operations", "#analytics", "#csv", "#plotly"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-04-12", "description": "This notebook allows users to track and manage issues related to their projects on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Track_issues_on_projects.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Track_issues_on_projects.ipynb", "imports": ["plotly.express", "naas_drivers.github"], "image_url": ""}, {"objectID": "e6462e6eaca51db7dbf96bbd6be22be706fa160145a35d73671984ccb506f093", "tool": "GitHub", "notebook": "Track notebooks created over time", "action": "", "tags": ["#github", "#repos", "#commits", "#notebooks", "#operations", "#analytics", "#html", "#plotly", "#csv", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows users to track changes to their notebooks over time using GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Track_notebooks_created_over_time.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Track_notebooks_created_over_time.ipynb", "imports": ["pandas", "requests", "os", "naas_drivers.github", "plotly.graph_objects", "pydash", "urllib.parse.urlencode", "datetime.datetime, timedelta", "naas"], "image_url": ""}, {"objectID": "e188766003d17aa7cd99e2ba165f5eee5b6fabb6336e759d7a1271f0f99dbefd", "tool": "GitHub", "notebook": "Update issue", "action": "", "tags": ["#github", "#issues", "#update", "#rest", "#api", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2023-05-26", "description": "This notebook explains how to update an issue on GitHub using the REST API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Update_issue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Update_issue.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "fa79dae352658caaec4422cf9d3df4cb3f10675a6b3d3f8323ec98354f5504af", "tool": "Gmail", "notebook": "Automate response from keywords in mailbox", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Sanjay Sabu", "author_url": "https://www.linkedin.com/in/sanjay-sabu-4205/", "updated_at": "2023-05-18", "created_at": "2021-04-20", "description": "This notebook automates the process of responding to emails in Gmail based on keywords found in the mailbox.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Automate_response_from_keywords_in_mailbox.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Automate_response_from_keywords_in_mailbox.ipynb", "imports": ["naas", "naas_drivers.email", "re.search"], "image_url": ""}, {"objectID": "2b5e18eec609ef0127f4d6d9be1802a2283fec60a598d654b98535b6bcd321ce", "tool": "Gmail", "notebook": "Clean mailbox", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#automation", "#scheduler"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-12", "created_at": "2021-04-14", "description": "This notebook helps you quickly and easily organize your Gmail inbox by removing unwanted emails.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Clean_mailbox.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Clean_mailbox.ipynb", "imports": ["naas", "naas_drivers.email", "pandas", "numpy", "plotly.express"], "image_url": ""}, {"objectID": "78ce50f9ba2a77f6308dbeb62b15c57fd5db2e92ecb652d13658246a50ead748", "tool": "Gmail", "notebook": "Create GitHub issue on specific email", "action": "", "tags": ["#gmail", "#github", "#email", "#issue", "#create", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-18", "created_at": "2023-05-17", "description": "This notebook will show how to create a GitHub issue from a specific email using Gmail and Python. It is usefull for organizations that need to track emails and create issues from them.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Create_GitHub_issue_on_specific_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Create_GitHub_issue_on_specific_email.ipynb", "imports": ["naas", "naas_drivers.email", "re.search", "pandas", "requests"], "image_url": ""}, {"objectID": "4eeb57ee19493997c46d04f94059ef5c2bd3f809491461cfe8c8c065d7d75921", "tool": "Gmail", "notebook": "Create draft email", "action": "", "tags": ["#gmail", "#email", "#draft", "#create", "#python", "#library"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-05-19", "created_at": "2023-05-16", "description": "This notebook will show how to create a draft email using the Gmail API. It is usefull for organizations that need to automate the creation of emails.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Create_draft_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Create_draft_email.ipynb", "imports": ["naas", "googleapiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "google.auth.transport.requests.Request", "pickle", "datetime", "os.path", "base64", "email.mime.text.MIMEText", "email.mime.multipart.MIMEMultipart"], "image_url": ""}, {"objectID": "cf0d71ca4f2f41fa0272cbf9fbe3b1e890e7c4968b3a9f57478f8d65e40f60e8", "tool": "Gmail", "notebook": "Delete email from mailbox", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows you to update an email status in your Gmail inbox.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Delete_email_from_mailbox.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Delete_email_from_mailbox.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "c2c64b6f6dd2e5281a3730230214ff3d877fea2309eb0b74ddeae27e331cac8a", "tool": "Gmail", "notebook": "Get emails by date", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#automation", "#analytics", "#plotly"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-07", "created_at": "2023-07-07", "description": "This notebook provides an example of how to retrieve emails based on a specified date or filter them by 'before' or 'after' a given date. It demonstrates the process of fetching emails using date-based criteria for more targeted email retrieval.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_emails_by_date.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_emails_by_date.ipynb", "imports": ["naas", "naas_drivers.email", "pandas", "numpy", "plotly.express", "datetime.date"], "image_url": ""}, {"objectID": "9d0515a1c77f00567dfb9833c75af19c3c9b24efd7b7a6e0a6d53ef0de00fcd0", "tool": "Gmail", "notebook": "Get emails stats by sender", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#automation", "#analytics", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows users to get stats from their emailbox by sender.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_emails_stats_by_sender.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_emails_stats_by_sender.ipynb", "imports": ["naas", "naas_drivers.email", "pandas", "numpy", "plotly.express"], "image_url": ""}, {"objectID": "3cc6c378e11b85f9191dac73c7c0f5f5118c8f9f96af0926e9d688849b470db8", "tool": "Gmail", "notebook": "Get most common senders", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#automation", "#analytics", "#plotly"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-19", "created_at": "2023-07-19", "description": "This notebook analyses users' inbox, identifies a list of the most common senders depending on the emails for the set period of time, and outputs the list of most common senders.\nThis notebook aims to identify unwanted subscriptions or emails that Gmail didn't successfully filter as \"Spam.\"", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_most_common_senders.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_most_common_senders.ipynb", "imports": ["datetime", "os", "imapclient.IMAPClient", "naas", "collections.Counter", "quopri", "email.header"], "image_url": ""}, {"objectID": "714810e2c13b0614a2e4dcca2ea5dade6fb7472a230e20e2bada4b75a1882fee", "tool": "Gmail", "notebook": "Get most important unseen emails", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#automation", "#analytics", "#plotly"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-19", "created_at": "2023-07-19", "description": "This notebook retrieves all emails for a set period of time and calculates the user's reply rate to each sender. By identifying the important senders with a higher reply rate, the code helps prioritize the user's responses and ensures timely communication. The code then outputs the list of unseen emails from these important senders, providing a focused view of the most relevant and pending email conversations.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_most_important_unseen_emails.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_most_important_unseen_emails.ipynb", "imports": ["datetime", "os", "imapclient.IMAPClient", "imapclient.IMAPClient", "naas", "collections.Counter", "quopri", "email.header"], "image_url": ""}, {"objectID": "e8855875aba10e1d9817664191d5f2ae82c89b8addef409700da4edb5c174f1c", "tool": "Gmail", "notebook": "Get seen emails", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows you to read your Gmail inbox and get the seen emails. It returns a dataframe as follow:\n- uid: This column represents the unique identifier associated with each row or email in the dataframe.\n- subject: The subject column contains the subject line or title of the email.\n- from: The \"from\" column contains information about the sender of the email. It includes the email address and name of the sender.\n- to: The \"to\" column contains information about the primary recipients of the email. It includes the email addresses and names of the recipients.\n- cc: The \"cc\" column represents the carbon copy recipients of the email. It contains a list of email addresses and names of the cc'd recipients.\n- bcc: The \"bcc\" column contains the blind carbon copy recipients of the email. Similar to the \"cc\" column, it includes a list of email addresses and names.\n- reply_to: This column contains the email addresses and names that should be used when replying to the email.\n- date: The \"date\" column indicates the date and time when the email was sent.\n- text: The \"text\" column contains the plain text content of the email.\n- html: The \"html\" column includes the HTML-formatted content of the email.\n- flags: The \"flags\" column represents any flags or indicators associated with the email, such as important, starred, etc.\n- headers: This column contains additional headers of the email, such as the \"delivered-to,\" \"received,\" and \"X-Google-Smtp-Source\" headers.\n- size_rfc822: The \"size_rfc822\" column indicates the size of the email in RFC822 format.\n- size: The \"size\" column represents the size of the email in bytes.\n- obj: The \"obj\" column contains the object representation of the email.\n- attachments: This column includes any attachments associated with the email, such as files, images, etc.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_seen_emails.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_seen_emails.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "c05ec3727f7f634fa76664cc32f3de7e7cae8ef27a4b8abf2f2eb444406359dc", "tool": "Gmail", "notebook": "Get unseen emails", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows you to read your Gmail inbox and get the unseen emails. It returns a dataframe as follow:\n- uid: This column represents the unique identifier associated with each row or email in the dataframe.\n- subject: The subject column contains the subject line or title of the email.\n- from: The \"from\" column contains information about the sender of the email. It includes the email address and name of the sender.\n- to: The \"to\" column contains information about the primary recipients of the email. It includes the email addresses and names of the recipients.\n- cc: The \"cc\" column represents the carbon copy recipients of the email. It contains a list of email addresses and names of the cc'd recipients.\n- bcc: The \"bcc\" column contains the blind carbon copy recipients of the email. Similar to the \"cc\" column, it includes a list of email addresses and names.\n- reply_to: This column contains the email addresses and names that should be used when replying to the email.\n- date: The \"date\" column indicates the date and time when the email was sent.\n- text: The \"text\" column contains the plain text content of the email.\n- html: The \"html\" column includes the HTML-formatted content of the email.\n- flags: The \"flags\" column represents any flags or indicators associated with the email, such as important, starred, etc.\n- headers: This column contains additional headers of the email, such as the \"delivered-to,\" \"received,\" and \"X-Google-Smtp-Source\" headers.\n- size_rfc822: The \"size_rfc822\" column indicates the size of the email in RFC822 format.\n- size: The \"size\" column represents the size of the email in bytes.\n- obj: The \"obj\" column contains the object representation of the email.\n- attachments: This column includes any attachments associated with the email, such as files, images, etc.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_unseen_emails.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_unseen_emails.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "a2209f3b3f09d821c3270ef170323d3ab2583d4a1c9eb628e3862e887382d6c0", "tool": "Gmail", "notebook": "Mark emails as seen by dates", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook goes through the emails within the date range set by the user and marks them all as seen.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Mark_emails_as_seen_by_dates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Mark_emails_as_seen_by_dates.ipynb", "imports": ["naas", "imaplib", "email", "datetime.date", "imapclient.IMAPClient", "imapclient.IMAPClient"], "image_url": ""}, {"objectID": "271cd524edb23b21e977fab95d1defea1649ae0caa2dc08f666f1c6e25d6b020", "tool": "Gmail", "notebook": "Read mailbox", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu", "updated_at": "2023-05-12", "created_at": "2021-04-15", "description": "This notebook allows you to read your Gmail inbox and returns a dataframe:\n- uid: This column represents the unique identifier associated with each row or email in the dataframe.\n- subject: The subject column contains the subject line or title of the email.\n- from: The \"from\" column contains information about the sender of the email. It includes the email address and name of the sender.\n- to: The \"to\" column contains information about the primary recipients of the email. It includes the email addresses and names of the recipients.\n- cc: The \"cc\" column represents the carbon copy recipients of the email. It contains a list of email addresses and names of the cc'd recipients.\n- bcc: The \"bcc\" column contains the blind carbon copy recipients of the email. Similar to the \"cc\" column, it includes a list of email addresses and names.\n- reply_to: This column contains the email addresses and names that should be used when replying to the email.\n- date: The \"date\" column indicates the date and time when the email was sent.\n- text: The \"text\" column contains the plain text content of the email.\n- html: The \"html\" column includes the HTML-formatted content of the email.\n- flags: The \"flags\" column represents any flags or indicators associated with the email, such as important, starred, etc. Possible value for flag: 'SEEN', 'ANSWERED', 'FLAGGED', 'DELETED', 'DRAFT', 'RECENT'\n- headers: This column contains additional headers of the email, such as the \"delivered-to,\" \"received,\" and \"X-Google-Smtp-Source\" headers.\n- size_rfc822: The \"size_rfc822\" column indicates the size of the email in RFC822 format.\n- size: The \"size\" column represents the size of the email in bytes.\n- obj: The \"obj\" column contains the object representation of the email.\n- attachments: This column includes any attachments associated with the email, such as files, images, etc.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Read_mailbox.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Read_mailbox.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "8f12ba6e2beed9a59f7b18f42a101ad2d7336041f95eb7e5bd50bb09f6052184", "tool": "Gmail", "notebook": "Send email", "action": "", "tags": ["#gmail", "#email", "#send", "#python", "#library", "#smtplib"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook will show how to send an email using naas_drivers. It is usefull for organizations that need to send emails from their Gmail account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Send_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Send_email.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "d292b17e6643b9537f5b4f295149979d2c5b081a8e0ab0f0d3ab78bb5c1bfddd", "tool": "Gmail", "notebook": "Update email flag", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows you to update an email flag in your Gmail inbox.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Update_email_flag.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Update_email_flag.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "104108f1cfc4292347929774d2c5e72f8691076a4e1576cd5d3e52a752c9520c", "tool": "Google Analytics", "notebook": "Follow average session duration daily", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-04-22", "description": "This notebook provides a daily overview of the average session duration for a website tracked with Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_average_session_duration_daily.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_average_session_duration_daily.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "9c612681622da896898b8d2e1234a00856e1515c326db064afae2d84fa7eb702", "tool": "Google Analytics", "notebook": "Follow number of new visitors daily", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-04-22", "description": "This notebook tracks the daily number of new visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_daily.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_daily.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "3fe7b4b211e6b581b521cf3dc9a9ed7c4a9a81e4c89f957444b5d04ec985ca33", "tool": "Google Analytics", "notebook": "Follow number of new visitors hourly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the hourly number of new visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_hourly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_hourly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "b8a4989937c8ebbec020312fc8d1e7bd427af1ca3f45a9afb9b5c83c55abc1c3", "tool": "Google Analytics", "notebook": "Follow number of new visitors monthly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the monthly number of new visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_monthly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "5b7788ab05dab3b644afdcb2d321dbf68370269934b6d4d53e02331b0d6b8bd1", "tool": "Google Analytics", "notebook": "Follow number of new visitors weekly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the weekly number of new visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_weekly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "c936eb78a90ad7c2a2baf26fe6ccd941e1ae7d29b5853b89fbbd4d0bb3235ee0", "tool": "Google Analytics", "notebook": "Follow number of sessions daily", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-04-22", "description": "This notebook provides a daily overview of the number of sessions tracked by Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_daily.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_daily.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "32df9d633cd4afefc4274cc22048edf92136f7e26c238ec4aa6d593868d90017", "tool": "Google Analytics", "notebook": "Follow number of sessions hourly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the number of sessions on Google Analytics over the course of an hour.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_hourly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_hourly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "3bdd912e77792584482b7d2b4f975959046378c261b29f97a4b2b65255b1475c", "tool": "Google Analytics", "notebook": "Follow number of sessions monthly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the monthly number of sessions on Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_monthly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "da843f31021b75f4fec31cc2deb7f06f955056d68c2045cf540597f6dd769591", "tool": "Google Analytics", "notebook": "Follow number of sessions weekly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the number of sessions on Google Analytics on a weekly basis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_weekly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "47b2f1e75d1576ff8090e484fd541f2fe88c07fd94a3ff71e1ab30bb29a426eb", "tool": "Google Analytics", "notebook": "Follow number of visitors daily", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-04-22", "description": "This notebook tracks the daily number of visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_daily.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_daily.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "56bd24cb31d186f8cef0bddcfae15554b4f2212fabaf28ef9f232c37acaf5d9f", "tool": "Google Analytics", "notebook": "Follow number of visitors hourly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the hourly number of visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_hourly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_hourly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "99e8d32201a65a79018137233c5e2b545ad46814a6de7617ea91a2c53cf918ff", "tool": "Google Analytics", "notebook": "Follow number of visitors monthly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the monthly number of visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_monthly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "05f3277c0413c03585c01a7b0f7a97cff58554756a85a014fa6ecd61fe5f0d6e", "tool": "Google Analytics", "notebook": "Follow number of visitors weekly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the weekly number of visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_weekly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "9efbf241b3610e5a74d4d6c0a06e1364d12516ab32d4dd06960d4af38f317dbb", "tool": "Google Analytics", "notebook": "Get bounce rate", "action": "", "tags": ["#googleanalytics", "#bouncerate", "#plotly", "#linechart", "#naas_drivers", "#scheduler", "#asset", "#naas", "#marketing", "#analytics", "#automation", "#image", "#csv", "#html"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides an analysis of the bounce rate of a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_bounce_rate.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_bounce_rate.ipynb", "imports": ["pandas", "plotly.graph_objects", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "fd0747c320e63718180faefdcd4021fd259514b20ba255a20a00aae4fc81a00c", "tool": "Google Analytics", "notebook": "Get pageview ranking", "action": "", "tags": ["#googleanalytics", "#pageviews", "#plotly", "#horizontalbarchart", "#naas_drivers", "#scheduler", "#asset", "#naas", "#marketing", "#analytics", "#automation", "#image", "#csv", "#html"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides a ranking of pageviews for a website using Google Analytics data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_pageview_ranking.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_pageview_ranking.ipynb", "imports": ["pandas", "plotly.graph_objects", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "eb4c394db4b8712ba495abae2c5eef6becfd0cfc413bf2463e82ab76f8c9b973", "tool": "Google Analytics", "notebook": "Get stats per country", "action": "", "tags": ["#googleanalytics", "#statspercountry", "#marketing", "#analytics", "#automation", "#image", "#csv", "#html", "#plotly"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides a comprehensive analysis of website traffic by country using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_stats_per_country.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_stats_per_country.ipynb", "imports": ["pycountry", "pycountry", "plotly.graph_objects", "plotly.express", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "b432939ab2679ed5875c113d75531e92776d116566343b19908714fa461a20c5", "tool": "Google Analytics", "notebook": "Get time on landing page", "action": "", "tags": ["#googleanalytics", "#timeonlanding", "#marketing", "#analytics", "#automation", "#image", "#csv", "#html", "#plotly"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides an analysis of the amount of time visitors spend on a landing page using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_time_on_landing_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_time_on_landing_page.ipynb", "imports": ["datetime.timedelta", "pandas", "plotly.graph_objects", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "d07d75e8dd6ee9ce1a85c6a5909028184fd0a04a3030164ac5c6430a5f7e7b56", "tool": "Google Analytics", "notebook": "Get unique visitors", "action": "", "tags": ["#googleanalytics", "#getuniquevisitors", "#plotly", "#barchart", "#naas_drivers", "#scheduler", "#asset", "#naas", "#marketing", "#analytics", "#automation", "#image", "#csv", "#html"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides an analysis of unique visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_unique_visitors.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_unique_visitors.ipynb", "imports": ["pandas", "plotly.graph_objects", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "afb36fe72b75ccd000b3c821eabec5037797e3ea1064bce8e088ba44b82ed1d8", "tool": "Google Analytics", "notebook": "Get unique visitors by country", "action": "", "tags": ["#googleanalytics", "#statspercountry", "#analytics", "#marketing", "#dataframe"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides a breakdown of unique visitors to a website by country using Google Analytics data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_unique_visitors_by_country.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_unique_visitors_by_country.ipynb", "imports": ["plotly.graph_objects", "plotly.express", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "bf81d9bdc059f8647005c3dc6132525ff6c4e7be3881311851324030a9be3eb2", "tool": "Google Analytics", "notebook": "Send visitors traffic graph and trends prediction to Slack channel", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#dataframe"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maxime-jublou", "updated_at": "2023-04-12", "created_at": "2022-05-16", "description": "This notebook allows users to send Google Analytics visitor traffic graphs and trends predictions to a Slack channel.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Send_visitors_traffic_graph_and_trends_prediction_to_Slack_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Send_visitors_traffic_graph_and_trends_prediction_to_Slack_channel.ipynb", "imports": ["naas", "naas_drivers.googleanalytics", "naas_drivers.prediction", "naas_drivers.plotly", "naas_drivers.slack", "plotly.graph_objects", "pandas", "datetime.datetime", "json"], "image_url": ""}, {"objectID": "f28cb2cc683e6496c50f1a68829a0c527ee8e5af9091132ec5c0b87769aba753", "tool": "Google Calendar", "notebook": "Get calendar", "action": "", "tags": ["#googlecalendar", "#calendar", "#get", "#api", "#reference", "#v3"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will demonstrate how to use the Google Calendar API to get metadata for a calendar.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Calendar/Google_Calendar_Get_calendar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Calendar/Google_Calendar_Get_calendar.ipynb", "imports": ["pprint.pprint", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow"], "image_url": ""}, {"objectID": "7513483959a8c033cb93018a8f4a9eb29cbfbfcbef8eacd5d2f2b9f5dd48ef1c", "tool": "Google Calendar", "notebook": "List calendars", "action": "", "tags": ["#googlecalendar", "#calendarlist", "#list", "#api", "#python", "#reference"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will demonstrate how to use the Google Calendar API to list the calendars on the user's calendar list.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Calendar/Google_Calendar_List_calendars.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Calendar/Google_Calendar_List_calendars.ipynb", "imports": ["pprint.pprint", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow"], "image_url": ""}, {"objectID": "a2db899b2d3b4a8407d9734bb11c66eb169b4a0a55b53fe65902049471de9fc7", "tool": "Google Calendar", "notebook": "List events from calendar", "action": "", "tags": ["#googlecalendar", "#calendar", "#events", "#list", "#api", "#python"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will demonstrate how to use the Google Calendar API to list events from a calendar.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Calendar/Google_Calendar_List_events_from_calendar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Calendar/Google_Calendar_List_events_from_calendar.ipynb", "imports": ["pprint.pprint", "datetime.datetime", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow"], "image_url": ""}, {"objectID": "4d62505c0b27fe497af44172fffb4bd8ca5ed2bcfcd1945d9434f00347ac442d", "tool": "Google Drive", "notebook": "Download file", "action": "", "tags": ["#googledrive", "#snippet", "#operations", "#naas"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows users to download files from their Google Drive account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Drive/Google_Drive_Download_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Drive/Google_Drive_Download_file.ipynb", "imports": ["gdown", "gdown"], "image_url": ""}, {"objectID": "7e5630a4f5744470a9195a186592bb24d9e9900acefba7d9a6ea179bedf905c7", "tool": "Google Maps", "notebook": "Calculate travel costs between two addresses", "action": "", "tags": ["#googlemaps", "#productivity", "#operations", "#automation", "#jupyternotebooks"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-26", "created_at": "2023-07-25", "description": "This notebook calculates the travel costs between two addresses using Google Maps API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Maps/Google_Maps_Calculate_travel_costs_between_two_addresses.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Maps/Google_Maps_Calculate_travel_costs_between_two_addresses.ipynb", "imports": ["os", "requests", "naas"], "image_url": ""}, {"objectID": "54859e1650428404cec4471aa488e37169ff7612eafb140d2ec610458085d181", "tool": "Google Maps", "notebook": "Connect to Routes API", "action": "", "tags": ["#googlemaps", "#productivity", "#operations", "#automation", "#jupyternotebooks"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook is designed to perform several functions. Firstly, it acquires the necessary credentials that are required for API access. Then, it proceeds to configure the API endpoint URL. After setting up the URL, it establishes a secure connection between the client and the API. Finally, it validates the user's identity and permissions for interactions with the API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Maps/Google_Maps_Connect_to_Routes_API.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Maps/Google_Maps_Connect_to_Routes_API.ipynb", "imports": ["os", "requests", "naas"], "image_url": ""}, {"objectID": "d41f3d68b8aab7d650b71042b444c5e5ebb1d8b4d3ca1487383f3c3aab62dc85", "tool": "Google Maps", "notebook": "Create and display distance matrix", "action": "", "tags": ["#googlemaps", "#productivity", "#operations", "#automation", "#jupyternotebooks"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-08-08", "created_at": "2023-08-08", "description": "This notebook shows how to use the Google Maps Distance Matrix API to determine distances and trip durations between a number of different origins and destinations, giving accurate and efficient geospatial data. Furthermore, it provides a visual representation of the created matrix.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Maps/Google_Maps_Create_and_display_distance_matrix.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Maps/Google_Maps_Create_and_display_distance_matrix.ipynb", "imports": ["os", "requests", "naas", "folium", "googlemaps", "polyline", "geopy.geocoders.Nominatim"], "image_url": ""}, {"objectID": "cad8fb307d05f4ec0dcf9a7567bc7e5c2fc50a8ec0f9537ac26299130df2987a", "tool": "Google Maps", "notebook": "Create itinerary optimisation on differents waypoints", "action": "", "tags": ["#googlemaps", "#optimization", "#data", "#naas_drivers", "#operations", "#snippet", "#dataframe", "#google_maps_api", "#directions_api"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-08-08", "created_at": "2023-08-08", "description": "This template analyses a given set of waypoints, optimizes the order of visiting them, and outputs a list with the correct order. Thus, making it useful for travelers, who want to visit multiple locations most efficiently.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Maps/Google_Maps_Create_itinerary_optimisation_on_differents_waypoints.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Maps/Google_Maps_Create_itinerary_optimisation_on_differents_waypoints.ipynb", "imports": ["naas", "folium", "polyline", "polyline", "geopy.geocoders.Nominatim", "itertools.permutations", "googlemaps", "googlemaps"], "image_url": ""}, {"objectID": "863199793a97917978b0681eac7e59c3615a9e454525435b9a1eb6845f701d40", "tool": "Google Maps", "notebook": "Get coordinates from address", "action": "", "tags": ["#googlemaps", "#productivity", "#operations", "#automation", "#jupyternotebooks"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-26", "created_at": "2023-07-25", "description": "This notebook get coordinates from a given address using Google Maps API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Maps/Google_Maps_Get_coordinates_from_address.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Maps/Google_Maps_Get_coordinates_from_address.ipynb", "imports": ["os", "requests", "naas"], "image_url": ""}, {"objectID": "4524ee41a55c75df72f6dc0d75ada96d8305d81e20b3626f7a785d6be7431b9d", "tool": "Google Search", "notebook": "Get LinkedIn company url from name", "action": "", "tags": ["#googlesearch", "#snippet", "#operations", "#url"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "This notebook provides a method to quickly obtain the LinkedIn URL of a company from its name using Google Search.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Search/Google_Search_Get_LinkedIn_company_url_from_name.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Search/Google_Search_Get_LinkedIn_company_url_from_name.ipynb", "imports": ["googlesearch.search", "googlesearch.search", "re"], "image_url": ""}, {"objectID": "d1c949fe9e214226b7df5584548da212d42692f254b3325a5b9a03b14993b5be", "tool": "Google Search", "notebook": "Get LinkedIn profile url from name", "action": "", "tags": ["#googlesearch", "#snippet", "#operations", "#url"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "This notebook provides a method to quickly and easily obtain a LinkedIn profile URL from a given name using Google Search.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Search/Google_Search_Get_LinkedIn_profile_url_from_name.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Search/Google_Search_Get_LinkedIn_profile_url_from_name.ipynb", "imports": ["googlesearch.search", "googlesearch.search", "re"], "image_url": ""}, {"objectID": "2064667ee2f72eea060b675451e0aa7ce39cae50c52fce3ddd817440bfba9e21", "tool": "Google Search", "notebook": "Perform search", "action": "", "tags": ["#googlesearch", "#snippet", "#operations", "#url"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows users to perform Google searches quickly and easily.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Search/Google_Search_Perform_search.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Search/Google_Search_Perform_search.ipynb", "imports": ["googlesearch.search", "googlesearch.search"], "image_url": ""}, {"objectID": "a3806d0e8beb6df74a694e543ef83a8bf1058b7cc2dd05636cdeb22dde4ed654", "tool": "Google Sheets", "notebook": "Add items to Notion databases from new rows in", "action": "", "tags": ["#googlesheets", "#productivity", "#operations", "#automation", "#notion"], "author": "Pooja Srivastava", "author_url": "https://www.linkedin.com/in/pooja-srivastava-bb037649/", "updated_at": "2023-04-12", "created_at": "2022-03-29", "description": "This notebook does the following tasks: \n- Schedule the notebook to run every 15 minutes\n- Connect with Gsheet and get all rows using the gsheet driver's get method\n- Connect with NotionDB and get all pages using the Notion Databases driver's get method\n- Compare the list of pages from notion db with the rows returned from gsheet and add non matching rows to a list\n- Create new pages in Notion db for each row in the non matching list using the Notion Pages driver's create method\n- For each created page, add the properties and values from gsheet and update in notion using the Notion Pages driver's update methods", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Add_items_to_Notion_databases_from_new_rows_in_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Add_items_to_Notion_databases_from_new_rows_in_Google_Sheets.ipynb", "imports": ["pandas", "naas", "naas_drivers.notion, gsheet"], "image_url": ""}, {"objectID": "17edc5fdc7b63b3e6d04eb4faf8645977e854302a90026ec9fd88d666632fc59", "tool": "Google Sheets", "notebook": "Add new github member to team from spreadsheet", "action": "", "tags": ["#github", "#teams", "#automation", "#googlesheets", "#operations"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-05-20", "description": "This notebook demonstrates how to use Google Sheets to add a new GitHub member to a team from a spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Add_new_github_member_to_team_from_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Add_new_github_member_to_team_from_spreadsheet.ipynb", "imports": ["requests", "naas_drivers.github, gsheet", "naas", "pandas"], "image_url": ""}, {"objectID": "b04ee5b4b37c8b2317bef0807a60465579484e42bc08e2d5ccc93e264b98f84d", "tool": "Google Sheets", "notebook": "Calculate distance and price", "action": "", "tags": ["#googlesheets", "#gsheet", "#data", "#naas_drivers", "#operations", "#snippet", "#dataframe", "#google_maps_api", "#routes_api"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This template determines the cost and distance between location extracted from a Google Sheet. It uses the Routes API to estimate the price depending on the distance between sites and outputs the updated Google Sheet with distances and prices.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Calculate_Distance_and_Price.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Calculate_Distance_and_Price.ipynb", "imports": ["naas", "naas_drivers.gsheet", "requests"], "image_url": ""}, {"objectID": "ba4899765b01f9b5812cccd925895c501d58721780bc932b6fc4ff040e190f30", "tool": "Google Sheets", "notebook": "Get data", "action": "", "tags": ["#googlesheets", "#gsheet", "#data", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook demonstrates how to get data from a Google Sheets spreadsheet and return a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Get_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Get_data.ipynb", "imports": ["naas_drivers.gsheet"], "image_url": ""}, {"objectID": "05789b41ffcc541325fae77c8579bb900c997f4f995f9e1d4c65a690d6016683", "tool": "Google Sheets", "notebook": "Send LinkedIn invitations from spreadsheet", "action": "", "tags": ["#googlesheets", "#invitation", "#automation", "#content", "#notification", "#email", "#linkedin"], "author": "Valentin Goulet", "author_url": "https://www.linkedin.com/in/valentin-goulet-3a3070152/", "updated_at": "2023-04-12", "created_at": "2022-04-07", "description": "This notebook allows users to quickly and easily send LinkedIn invitations to contacts stored in a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Send_LinkedIn_invitations_from_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Send_LinkedIn_invitations_from_spreadsheet.ipynb", "imports": ["naas", "naas_drivers.linkedin, gsheet"], "image_url": ""}, {"objectID": "cf32ecf61a1d6fdcae3273e7e70026564087776ace44ace0a939c08a2085586f", "tool": "Google Sheets", "notebook": "Send data", "action": "", "tags": ["#googlesheets", "#gsheet", "#data", "#naas_drivers", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook allows to send data to Google Sheets to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Send_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Send_data.ipynb", "imports": ["naas_drivers.gsheet", "pandas"], "image_url": ""}, {"objectID": "209d34f8faf5b05652f9cb4b3fe1045566401b2257c9e18947473dbb1785b092", "tool": "Google Sheets", "notebook": "Send data to MongoDB", "action": "", "tags": ["#googlesheets", "#mongodb", "#nosql", "#operations", "#automation"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-04-12", "created_at": "2022-03-21", "description": "This notebook will help you send data from your spreadsheet to your MongoDB database collection", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Send_data_to_MongoDB.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Send_data_to_MongoDB.ipynb", "imports": ["naas_drivers.mongo, gsheet", "pandas", "naas"], "image_url": ""}, {"objectID": "1dc4e7406a9def845c9736a3dba795b33642a578d2f4c4b1fca74ca2c075892b", "tool": "Google Sheets", "notebook": "Send emails from sheet", "action": "", "tags": ["#googlesheets", "#gsheet", "#data", "#naas_drivers", "#operations", "#snippet", "#email"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook allows users to send emails directly from a Google Sheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Send_emails_from_sheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Send_emails_from_sheet.ipynb", "imports": ["naas_drivers.gsheet", "naas_drivers.email"], "image_url": ""}, {"objectID": "ce8167442d31886b2f8cd299da0d39fd5c26e646f8a734d91fc21a0d3372f5ff", "tool": "Google Slides", "notebook": "Create a Slide", "action": "", "tags": ["#googleslides", "#slides", "#create", "#api", "#developers", "#guides"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-20", "description": "This notebook describes how to insert a blank slide to an existing Google Slides presentation establishing a seamless connection using OAuth consent.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Slides/Google_Slides_Create_a_Slide.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Slides/Google_Slides_Create_a_Slide.ipynb", "imports": ["apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "uuid"], "image_url": ""}, {"objectID": "c18cd5159f738d52c6c4c7b6c95f1cf6bbc69b830505f91e9e82c9d2b99382ee", "tool": "Google Slides", "notebook": "Create a blank presentation", "action": "", "tags": ["#google", "#slides", "#presentation", "#create", "#blank", "#api"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-20", "description": "This notebook creates a blank presentation with a specified title using Google Slides API while connecting with oauth consent.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Slides/Google_Slides_Create_a_blank_presentation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Slides/Google_Slides_Create_a_blank_presentation.ipynb", "imports": ["apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow"], "image_url": ""}, {"objectID": "a397cec39c6fdad00f731f42c05d051037f4b2f52822c0818359408002f7c450", "tool": "Google Slides", "notebook": "Duplicate slide", "action": "", "tags": ["#googleslides", "#slides", "#duplicate", "#copy", "#presentation", "#slideshow"], "author": "Florent Ravenel", "author_url": "https://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-24", "description": "This notebook explains how to duplicate a slide in Google Slides establishing a seamless connection using OAuth consent. It is usefull for organizations that need to quickly create a presentation with similar slides.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Slides/Google_Slides_Duplicate_slide.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Slides/Google_Slides_Duplicate_slide.ipynb", "imports": ["apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "uuid"], "image_url": ""}, {"objectID": "4310bd0e9d59bba6ee8d36901c9519799e4753bb99624ef7f21272d14bc967ac", "tool": "Google Slides", "notebook": "List slides in presentation", "action": "", "tags": ["#googleslides", "#presentation", "#list", "#slides", "#python", "#api"], "author": "Florent Ravenel", "author_url": "https://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-24", "description": "This notebook will list all the slides in a Google Slides presentation and is usefull for organizations that need to quickly access the content of a presentation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Slides/Google_Slides_List_slides_in_presentation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Slides/Google_Slides_List_slides_in_presentation.ipynb", "imports": ["apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow"], "image_url": ""}, {"objectID": "5ee4be70aada8b886738cac583ed13df2be5a8597fa7dc4f811f5a8a12861f36", "tool": "Google Slides", "notebook": "Replace text within a shape", "action": "", "tags": ["#googleslides", "#text", "#shape", "#replace", "#api", "#slides"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-25", "created_at": "2023-04-21", "description": "This notebook explains how to use the Slides API to modify the text content of a shape establishing a seamless connection using OAuth consent.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Slides/Google_Slides_Replace_text_within_a_shape.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Slides/Google_Slides_Replace_text_within_a_shape.ipynb", "imports": ["apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "googleapiclient.errors.HttpError", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "googleapiclient.errors.HttpError"], "image_url": ""}, {"objectID": "fcfade8d33f639cee874b1956980bbf1c446054e191bec6e66d7ba12f1e1621d", "tool": "HTML", "notebook": "Create a website", "action": "", "tags": ["#html", "#css", "#website", "#page", "#landing", "#custom", "#snippet", "#marketing"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-10-03", "description": "The objective of this notebook is to create an end-to-end website in 5min.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HTML/HTML_Create_a_website.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HTML/HTML_Create_a_website.ipynb", "imports": ["urllib.request.urlopen", "IPython.display.IFrame", "naas"], "image_url": ""}, {"objectID": "dbd059d8bc4a12b38bd1d41128de9f4b6610c0048c178f8d96b57bb1d852f5b0", "tool": "Harvest", "notebook": "Get Filtered List of Time Entries", "action": "", "tags": ["#harvest", "#timeentries", "#api", "#list", "#python", "#get", "#filter"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-01", "created_at": "2023-08-01", "description": "This notebook will create a filtered list of time entries from the Harvest API v2. It is usefull for organizations to quickly access and display time entries based on a specific filter, such as by time period or project.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Harvest/Harvest_Filtered_time_entries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Harvest/Harvest_Filtered_time_entries.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "8a1dc783cc49a4f89c466a896cc8ec97d86bf1efd9a5f1b945cf97a3d73c3e27", "tool": "Harvest", "notebook": "List all clients", "action": "", "tags": ["#harvest", "#clients", "#api", "#list", "#python", "#get"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-16", "created_at": "2023-06-13", "description": "This notebook will list all clients from Harvest API and is usefull for organizations to get a list of their clients.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Harvest/Harvest_List_all_clients.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Harvest/Harvest_List_all_clients.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "084fd7fb8f4258a75ef4d470a395f3f4012a8b6663332d19546b8940ade827f4", "tool": "Harvest", "notebook": "List all time entries", "action": "", "tags": ["#harvest", "#timeentries", "#api", "#list", "#python", "#v2"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-13", "created_at": "2023-06-13", "description": "This notebook will list all time entries from the Harvest API v2. It is usefull for organizations to quickly access and display time entries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Harvest/Harvest_List_all_time_entries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Harvest/Harvest_List_all_time_entries.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "a4f6376cc053d445a9a1d10372766aeefa9588c710352decfd1af2a049a09310", "tool": "Harvest", "notebook": "List all users", "action": "", "tags": ["#harvest", "#users", "#api", "#list", "#python", "#get"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-03", "created_at": "2023-08-03", "description": "This notebook will list all users from the Harvest API v2. This is helpful as it allows organizations to quickly display all of their users on Harvest.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Harvest/Harvest_List_all_users.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Harvest/Harvest_List_all_users.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "7b4313cc79bea4a013f6abcc10f65b57072015ef0036a00f2ec9eb5002243581", "tool": "Healthchecks", "notebook": "Perfom basic actions", "action": "", "tags": ["#healthchecks", "#snippet", "#operations"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "This notebook provides a set of basic actions to help monitor and maintain the health of a system.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Healthchecks/Healthchecks_Perfom_basic_actions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Healthchecks/Healthchecks_Perfom_basic_actions.ipynb", "imports": ["naas_drivers.healthcheck"], "image_url": ""}, {"objectID": "995754444ddb900c81983085697f28649f333866641490313e567b1e0a3c9396", "tool": "HubSpot", "notebook": "Add LinkedIn message to contact", "action": "", "tags": ["#hubspot", "#communications", "#linkedin", "#snippet", "#contact", "#association"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook demonstrates how to add a LinkedIn message to a given contact in HubSpot. It uses the communication endpoint in HubSpot. It could be useful to create integration directly from your LinkedIn messages.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Add_LinkedIn_message_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Add_LinkedIn_message_to_contact.ipynb", "imports": ["requests", "naas", "datetime.datetime, date, timezone", "pprint.pprint"], "image_url": ""}, {"objectID": "84696ceb69fada2dae72389c3da1f4cb0d8ed06cce7d33bf3f1e5772859e4c04", "tool": "HubSpot", "notebook": "Add SMS message to contact", "action": "", "tags": ["#hubspot", "#communications", "#SMS", "#snippet", "#contact", "#association"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook demonstrates how to add SMS message to a given contact in HubSpot. It uses the communication endpoint in HubSpot. It could be useful to integrate with tools like Twilio.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Add_SMS_message_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Add_SMS_message_to_contact.ipynb", "imports": ["requests", "naas", "datetime.datetime, date, timezone", "pprint.pprint"], "image_url": ""}, {"objectID": "09a2fdd2c66a2ffb4736afbf1c4347feac6703273eccc90780482835a14a7760", "tool": "HubSpot", "notebook": "Add WhatsApp message to contact", "action": "", "tags": ["#hubspot", "#communications", "#whatsapp", "#snippet", "#contact", "#association"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook demonstrates how to add WhatsApp message to a given contact in HubSpot. It uses the communication endpoint in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Add_WhatsApp_message_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Add_WhatsApp_message_to_contact.ipynb", "imports": ["requests", "naas", "datetime.datetime, date, timezone", "pprint.pprint"], "image_url": ""}, {"objectID": "fffe7caf1ac0d096638c4e57e74ede411114700e1924b295ad76e864a1104f36", "tool": "HubSpot", "notebook": "Add note to contact", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#notes", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2023-08-29", "description": "This notebook demonstrates how to add a note to one a several contacts in HubSpot using their contact ID. This can be particularly useful for recording details about a contact's engagement with your published content or their usage of your product.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Add_note_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Add_note_to_contact.ipynb", "imports": ["requests", "naas", "datetime.datetime, date, timezone"], "image_url": ""}, {"objectID": "4f9aab526231f9a50b619d844a1e874debbbc1d6aaefc90759cf32850a66a802", "tool": "HubSpot", "notebook": "Associate contact to deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#contact", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook associates a contact to a deal in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Associate_contact_to_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Associate_contact_to_deal.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "a72923734c2d899bdf89bd2d41220b71d265ebd1628d1ec9c7d2df3dc46cae26", "tool": "HubSpot", "notebook": "Chat about a contact", "action": "", "tags": ["#hubspot", "#contact", "#activity", "#notes", "#emails", "#communications", "#meetings", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-21", "description": "This notebook demonstrates how to retrieve all activities from a contact URL in HuSpot in use it in Naas Chat.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Chat_about_a_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Chat_about_a_contact.ipynb", "imports": ["requests", "naas", "naas_drivers.hubspot, naas_chat_plugin", "pandas"], "image_url": ""}, {"objectID": "d5aef083b682b39a162f90c833fb5c6104fe72e3c839a9008e799212f82a8c80", "tool": "HubSpot", "notebook": "Chat about a deal", "action": "", "tags": ["#hubspot", "#chat", "#deals", "#last", "#discussion", "#conversation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-25", "created_at": "2023-09-25", "description": "This notebook assists you in discussing a deal on HubSpot by providing essential insights about the deal and its recent activities. This information will enable you to plan your next steps effectively.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Chat_about_a_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Chat_about_a_deal.ipynb", "imports": ["requests", "naas", "naas_drivers.hubspot, naas_chat_plugin", "pandas", "os"], "image_url": ""}, {"objectID": "21c2ec4f17d5dfd788890b76d6a094c3a8fa3ddd8246a849bd11b1f41f778019", "tool": "HubSpot", "notebook": "Create Task", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#task", "#snippet"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-02-24", "description": "This template will create a task in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_Task.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_Task.ipynb", "imports": ["datetime.datetime, timedelta", "requests", "json", "naas"], "image_url": ""}, {"objectID": "220bf21fcc2f41498798ec5655cdbf42fe612dc4b6d93e9fc11424e48f985b63", "tool": "HubSpot", "notebook": "Create company", "action": "", "tags": ["#hubspot", "#company", "#create", "#crm", "#business", "#management"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-25", "created_at": "2023-09-25", "description": "This notebook will show how to create a company in HubSpot and how it is useful for organizations.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_company.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "41a54dd1b30076c3f50da00bf2b549912f8c38f2209b3752b0c22bd5c465df00", "tool": "HubSpot", "notebook": "Create contact", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#create"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2022-02-21", "description": "This notebook demonstrates how to create a contact in HubSpot using HubSpot default properties.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_contact.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "a10c1080b82d40f568861bec9c4fb24ff42d65d11b78ddc719282e46a2afffaf", "tool": "HubSpot", "notebook": "Create contact from LinkedIn profile", "action": "", "tags": ["#hubspot", "#linkedin", "#profile", "#naas_drivers", "#snippet", "#sales"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-10-13", "description": "This notebook creates a contact in HubSpot from a LinkedIn profile URL with:\n- email\n- linkedinbio\n- phone and mobilephone\n- website\n- twitterhandle\n- firstname\n- lastname\n- info\n- jobtitle\n- industry\n- city\n- state\n- country\n- job_function\n- company\n- field_of_study", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_contact_from_LinkedIn_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_contact_from_LinkedIn_profile.ipynb", "imports": ["naas", "naas_drivers.hubspot, linkedin", "os.path, mkdir"], "image_url": ""}, {"objectID": "e8235f2c41e1848e65b08daadbc4a2c07bb88ad792e876174c4924d1b2a11f3d", "tool": "HubSpot", "notebook": "Create contact using custom properties", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#create"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2023-08-29", "description": "This notebook demonstrates how to create a contact in HubSpot using HubSpot default or custom properties.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_contact_with_custom_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_contact_with_custom_properties.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "d11c4d245d38c72a488cf4ef73f193f8c1c6618dc2aeedd06e3aee9ce8b807ac", "tool": "HubSpot", "notebook": "Create contacts from linkedin post likes", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#linkedin", "#post", "#contact", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook create new contacts based on LinkedIn post likes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_contacts_from_linkedin_post_likes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_contacts_from_linkedin_post_likes.ipynb", "imports": ["naas_drivers.linkedin, hubspot", "naas", "requests"], "image_url": ""}, {"objectID": "e4a548d7f36bef053fe0cb094f83c4eaca4a721fd4b7112548bbce0f8f3b102a", "tool": "HubSpot", "notebook": "Create deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook allows users to create deals in HubSpot, helping them to manage their sales pipeline.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_deal.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "0eafe8fc3415fe94e8707349db0bb4b27d516ecb3850492a06be7d4a0086f2ef", "tool": "HubSpot", "notebook": "Delete Task", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#task", "#snippet"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-03-12", "description": "This template will delete a task in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_Task.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_Task.ipynb", "imports": ["datetime.datetime, timedelta", "requests, math", "json", "naas"], "image_url": ""}, {"objectID": "18ba61523d3000719630fd0b6bc6b478568078713221a8163f89e7eadeb10dee", "tool": "HubSpot", "notebook": "Delete communication", "action": "", "tags": ["#hubspot", "#communications", "#snippet", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook demonstrates how to delete a communication using its ID using HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_communication.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_communication.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "c3a6736f70c48fb0c868fcc904e64f39fe1621cf5cf416d13654970ce52cafa6", "tool": "HubSpot", "notebook": "Delete a company", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#company", "#naas_drivers", "#snippet", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-09-25", "created_at": "2023-09-25", "description": "This notebook demonstrates how to delete a given company in HubSpot using its HubSpot ID.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_company.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "758eceb0755d55869262781c0fdbf0ae8897488501d0c5a019bb29f299889448", "tool": "HubSpot", "notebook": "Delete contact", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2022-02-21", "description": "This notebook demonstrates how to delete a given contact in HubSpot using its HubSpot ID.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_contact.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "297e616568c4e2565a8f512dd5e4db0a922305d4a2d09e26c6a0b22d5c90472e", "tool": "HubSpot", "notebook": "Delete deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook allows users to delete deals from their HubSpot account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_deal.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "42f6566a97e75f9a5683b1536e893e1088ec249bafe87e1601eb982be842a384", "tool": "HubSpot", "notebook": "Delete note", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#note", "#snippet", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2023-08-29", "description": "This notebook demonstrates how to delete a note using its ID using HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_note.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_note.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "dca97b52f36c302df5c197d00895c621c69829e47a41bc1869b310a2795d7deb", "tool": "HubSpot", "notebook": "Get Task", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#task", "#snippet", "#json"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-03-12", "description": "This template will get a task in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_Task.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_Task.ipynb", "imports": ["datetime.datetime, timedelta", "requests, math", "json", "naas"], "image_url": ""}, {"objectID": "06b11cf336c1e0d493eb89898cd3a39adcb000113e2f74b4d12d64c5e7f04932", "tool": "HubSpot", "notebook": "Get activities from contact", "action": "", "tags": ["#hubspot", "#contact", "#activity", "#notes", "#emails", "#communications", "#meetings", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-21", "description": "This notebook demonstrates how to retrieve all activities from a contact URL by combining various HubSpot API endpoints.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_activities_from_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_activities_from_contact.ipynb", "imports": ["requests", "naas", "naas_drivers.hubspot", "pandas"], "image_url": ""}, {"objectID": "c2c189b600c06f1e994fed0b3cfc63d3ea79a7df196d4bd011f46f91ea147905", "tool": "HubSpot", "notebook": "Get all companies", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#companies", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-23", "created_at": "2023-08-23", "description": "This notebook will get all companies from HubSpot CRM using the API and will be usefull to get a list of all companies in the CRM.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_all_companies.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_all_companies.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "2cc7be1f4752e97f41db9463ad356b8ae5c6497c16c15317610dc16372f975a1", "tool": "HubSpot", "notebook": "Get all contacts", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-23", "created_at": "2022-02-21", "description": "This notebook allows you to retrieve all contacts from HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_all_contacts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_all_contacts.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "5e8948b2a218d67932167e52f1709186e5a2d6d230316857c687794715b0db73", "tool": "HubSpot", "notebook": "Get all deals", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook provides a comprehensive overview of all deals in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_all_deals.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_all_deals.ipynb", "imports": ["naas_drivers.hubspot"], "image_url": ""}, {"objectID": "f085c6a0dfb61b23a506b44cb0181599a5bfb15014e5c592e594735aff488582", "tool": "HubSpot", "notebook": "Get all pipelines and dealstages", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#pipelines", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-10", "created_at": "2022-02-21", "description": "This notebook get all your pipelines and dealstages.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_all_pipelines_and_dealstages.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_all_pipelines_and_dealstages.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "29282cfa4a016e0aa6518f975cf5cd5e4fe644c0a94c7073549cea7aaf3676bd", "tool": "HubSpot", "notebook": "Get communications associated to contact", "action": "", "tags": ["#hubspot", "#api", "#contact", "#communications", "#linkedin", "#whatsapp", "#sms", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook demonstrates how to retrieve all communications associated to a contact in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_communications_associated_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_communications_associated_to_contact.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "e8f3175084d60841c26849c105eb3499543dd9b44adb851a790b5a470c44d851", "tool": "HubSpot", "notebook": "Get a company", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#company", "#naas_drivers", "#snippet", "#get"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-09-25", "created_at": "2023-09-25", "description": "This notebook demonstrates how to get a given company in using its hubspot ID.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_company.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "084ee054bd3721c966e8c3bc06217a3c5c7154efef048933eaa4ab0f55a3e84e", "tool": "HubSpot", "notebook": "Get contact brief", "action": "", "tags": ["#hubspot", "#contact", "#activity", "#notes", "#emails", "#communications", "#meetings", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-22", "created_at": "2023-09-22", "description": "This notebook illustrates the process of obtaining a contact brief in HubSpot. It fetches detailed contact information, along with all related activities between you and your sales team. These activities may include emails, notes, meetings, and communications via LinkedIn, WhatsApp, and SMS. The output is conveniently delivered as a text file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_contact_brief.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_contact_brief.ipynb", "imports": ["requests", "naas", "naas_drivers.hubspot, naas_chat_plugin", "pandas", "os"], "image_url": ""}, {"objectID": "9056bb1dcba589051252c2df8a24c91b9109e99293b11c1fe9d0b5d6fbb08197", "tool": "HubSpot", "notebook": "Get contact details from URL", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-21", "created_at": "2022-05-31", "description": "This notebook provides a method to retrieve contact details from a HubSpot contact URL using the HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_contact_details_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_contact_details_from_URL.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "6f72d8f451dccc72ecffed406a64ceab0e710237b87052e324d258e0153a6a3e", "tool": "HubSpot", "notebook": "Get contact details from email", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-21", "created_at": "2022-05-31", "description": "This notebook provides a method to retrieve contact details from a HubSpot contact email using the HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_contact_details_from_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_contact_details_from_email.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "ca0c0d07420d67bbdde9dff74791dd0bcef463a82a10315049cefef33713a892", "tool": "HubSpot", "notebook": "Get contact details from contact id", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-21", "created_at": "2022-05-31", "description": "This notebook provides a method to retrieve contact details from a HubSpot contact ID using the HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_contact_details_from_id.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_contact_details_from_id.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "57e771994762f2f1daf87e33bf4ee92ea4b096811bc09043847d120a66dded70", "tool": "HubSpot", "notebook": "Get contacts associated to deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#contact", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook get association between contacts and deals.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_contacts_associated_to_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_contacts_associated_to_deal.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "c3a9b9d1e98c629b1cb002d88a40903dc4d592e24e830e00c9b484c2bfa25b4a", "tool": "HubSpot", "notebook": "Get deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook provides a comprehensive overview of the HubSpot platform and its features to help you get the best deals.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_deal.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "90427433669e0a447b5aa778552086cdcad6418e1e5a81c0cf6d7a333a430b3f", "tool": "HubSpot", "notebook": "Get deal brief", "action": "", "tags": ["#hubspot", "#deal", "#activity", "#notes", "#emails", "#communications", "#meetings", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-22", "created_at": "2023-09-22", "description": "This notebook illustrates the process of obtaining a deal brief in HubSpot. It fetches detailed detail information, along with all related activities between you and your sales team. These activities may include emails, notes, meetings, and communications via LinkedIn, WhatsApp, and SMS. The output is conveniently delivered as a text file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_deal_brief.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_deal_brief.ipynb", "imports": ["requests", "naas", "naas_drivers.hubspot", "pandas", "os"], "image_url": ""}, {"objectID": "871e457a336ded192521c203bce981c5664048760631a9acb48df8ddca1cf81e", "tool": "HubSpot", "notebook": "Get meetings associated to contact", "action": "", "tags": ["#hubspot", "#api", "#meetings", "#retrieve", "#requests", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-11", "created_at": "2023-08-07", "description": "This notebook demonstrates how to retrieve meetings ID associated with a contact in HubSpot using the HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_meetings_associated_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_meetings_associated_to_contact.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "c79e3c28a55e8062cd77c414c2edb9668bd1840467f3586806e81547276cecb5", "tool": "HubSpot", "notebook": "Get notes associated to contact", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#notes", "#snippet", "#json", "#contacts"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2023-08-29", "description": "This notebook demonstrates how to retrieve all notes associated to a contact in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_notes_associated_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_notes_associated_to_contact.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "d468de85f83026e5f3c404ed798b1a95bbbc7def17fc67c2a1f376d5fd7a35e4", "tool": "HubSpot", "notebook": "Get sales emails associated to contact", "action": "", "tags": ["#hubspot", "#api", "#contact", "#sales", "#emails", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-17", "description": "This notebook demonstrates how to retrieve all sales emails associated to a contact in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_sales_emails_associated_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_sales_emails_associated_to_contact.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "6f16b41d94a94ed30a6a592a36584708965f8a7bde0007c3723d973b49c01984", "tool": "HubSpot", "notebook": "List communication properties", "action": "", "tags": ["#hubspot", "#properties", "#communications", "#linkedin", "#whatsapp", "#sms", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook list all communications properties available in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_communication_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_communication_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "8431d65494aca14c3551905b84b6590708ed3d2f57c34243e368fd2cda8bc818", "tool": "HubSpot", "notebook": "List company properties", "action": "", "tags": ["#hubspot", "#properties", "#company", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-23", "created_at": "2023-08-23", "description": "This notebook list company properties in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_company_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_company_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "1cbde3b04095cadc48040885b0752305f813749b15590ff2c287874e3b3fa1a7", "tool": "HubSpot", "notebook": "List contact properties", "action": "", "tags": ["#hubspot", "#properties", "#contact", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-21", "description": "This notebook list the contact properties in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_contact_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_contact_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "e7ec070fd87d2ff5eb89ca90bbbd98c379e5224d217a3c1ceed6cd39a857e1a6", "tool": "HubSpot", "notebook": "List meeting properties", "action": "", "tags": ["#hubspot", "#api", "#meetings", "#retrieve", "#requests", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-11", "created_at": "2023-08-07", "description": "This notebook provides access to the list of meeting properties in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_meeting_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_meeting_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "97f11b70c0c60e6b95fc17a5fadd5030c37c2f97a3e2568cd31238ea6fb5ad34", "tool": "HubSpot", "notebook": "List notes properties", "action": "", "tags": ["#hubspot", "#properties", "#notes", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-21", "description": "This notebook list the notes properties in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_notes_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_notes_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "3c0890cc3cd13e3c6d72bc4ace0a28073c60c6bf770c0d1d68d6119ec12c4fd2", "tool": "HubSpot", "notebook": "List sales emails properties", "action": "", "tags": ["#hubspot", "#api", "#sales", "#emails", "#retrieve", "#requests", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-11", "created_at": "2023-08-07", "description": "This notebook provides access to the list of sales emails properties in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_sales_emails_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_sales_emails_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "addc66ec405ac0fc7ad20e0d1e0fa3a85fbf06f6aac030dd8f2b4da355d35b1d", "tool": "HubSpot", "notebook": "Retrieve communication details", "action": "", "tags": ["#hubspot", "#get", "#read", "#communication", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook fetches detailed information for a specific communication (Linkedin, SMS or WhatsApp message). It can be helpful in obtaining further details from a communication ID, which can be acquired by extraction from a contact.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Retrieve_communication_details.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Retrieve_communication_details.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "05d1f96265b1e2aecae868c680041a298e4813049fab9f79887b6304fa8fcb40", "tool": "HubSpot", "notebook": "Retrieve meetings", "action": "", "tags": ["#hubspot", "#api", "#meetings", "#retrieve", "#requests", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-07", "created_at": "2023-08-07", "description": "This notebook uses requests to retrieve meetings from HubSpot API. It is usefull for organizations to get information about their meetings.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Retrieve_meetings.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Retrieve_meetings.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "000268b50a5a3408219513347b6002498b5f3680bb09035bc7ea4bdd502916a3", "tool": "HubSpot", "notebook": "Retrieve note details", "action": "", "tags": ["#hubspot", "#get", "#read", "#communication", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook fetches detailed information for a specific note. It can be helpful in obtaining further details from a note ID, which can be acquired by extraction from a contact.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Retrieve_note.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Retrieve_note.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "9ca3ba5eae3a47b868a366803ceedd42514a9836b08a41e8e753b1d9f2bfe6cb", "tool": "HubSpot", "notebook": "Score contact from notes", "action": "", "tags": ["#hubspot", "#contact", "#activity", "#notes", "#emails", "#communications", "#meetings", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-21", "description": "This notebook illustrates the process of scoring a contact in HubSpot based on the count of their notes, which correspond to LinkedIn interactions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Score_contact_from_notes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Score_contact_from_notes.ipynb", "imports": ["naas", "naas_drivers.hubspot", "requests", "pandas"], "image_url": ""}, {"objectID": "c3086aff9615d012c42b6cb7ccc977193b8092d7fdf6b1e49084fa7b519cef76", "tool": "HubSpot", "notebook": "Send LinkedIn invitations from contacts", "action": "", "tags": ["#hubspot", "#invitation", "#automation", "#sales", "#linkedin"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-04", "description": "This notebook send LinkedIn invitation to your HubSpot contacts.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_LinkedIn_invitations_from_contacts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_LinkedIn_invitations_from_contacts.ipynb", "imports": ["naas", "naas_drivers.hubspot, linkedin", "pandas", "os"], "image_url": ""}, {"objectID": "e34b8e2c2e86d41d5ff8cf46f34b81878c899d3c389c43d81261fa1b9f64d7e6", "tool": "HubSpot", "notebook": "Send closed deals weekly", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#scheduler", "#asset", "#html", "#png", "#csv", "#naas_drivers", "#naas", "#analytics", "#automation", "#image", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-11-23", "description": "This notebook send a weekly email based on your deals closed.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_closed_deals_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_closed_deals_weekly.ipynb", "imports": ["naas_drivers.hubspot", "datetime.datetime, timedelta", "pandas", "plotly.graph_objects", "plotly.subplots.make_subplots", "naas"], "image_url": ""}, {"objectID": "4063affa21ca76b463fb3696bcd1993679d6e2c91d8614b9e1d0f84d57aec6ef", "tool": "HubSpot", "notebook": "Send contacts to gsheet", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#gsheet", "#snippet", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook allows you to send HubSpot contacts to a Google Sheet for easy tracking and organization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_contacts_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_contacts_to_gsheet.ipynb", "imports": ["naas_drivers.hubspot, gsheet", "naas"], "image_url": ""}, {"objectID": "76a862a59d2f61ce3a6d17fb726390ff287a4c8ab26b8281a7f8e1fa0857de4c", "tool": "HubSpot", "notebook": "Send deals to gsheet", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#gsheet", "#snippet", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook allows you to send HubSpot deals to a Google Sheet for easy tracking and analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_deals_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_deals_to_gsheet.ipynb", "imports": ["naas_drivers.hubspot, gsheet", "naas"], "image_url": ""}, {"objectID": "fb271b446d3f68d5c35323574a36baba6d1c855598494a8807a73829a9641327", "tool": "HubSpot", "notebook": "Send new deals created weekly", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#scheduler", "#asset", "#html", "#png", "#csv", "#naas_drivers", "#naas", "#analytics", "#automation", "#image", "#plotly", "#notification", "#email"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-11-23", "description": "This notebook send a weekly email based on your deals created.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_new_deals_created_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_new_deals_created_weekly.ipynb", "imports": ["naas_drivers.hubspot, emailbuilder", "datetime.datetime, timedelta", "pandas", "plotly.graph_objects", "plotly.subplots.make_subplots", "naas"], "image_url": ""}, {"objectID": "a82cec3af17c939d191f8ce0883159014a63484fd77e1ec01c92c4d6358c90aa", "tool": "HubSpot", "notebook": "Send sales brief", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#notification", "#asset", "#emailbuilder", "#scheduler", "#naas", "#analytics", "#automation", "#email", "#text", "#plotly", "#html", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook send a sales brief based on your HubSpot activity.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_sales_brief.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_sales_brief.ipynb", "imports": ["naas_drivers.emailbuilder, hubspot", "naas", "pandas", "datetime.datetime", "naas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "d49ac09de4eaf9bef7efdf56581a4f54891f80799d0746bfff20181ac130cdf5", "tool": "HubSpot", "notebook": "Send sales pipeline to Notion", "action": "", "tags": ["#hubspot", "#notion", "#sales", "#pipeline", "#automation", "#integration"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-10", "created_at": "2023-04-26", "description": "This notebook automates the process of sending a sales pipeline from HubSpot to Notion. It is useful for organizations that need to keep track of their sales pipeline in both HubSpot and Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_sales_pipeline_to_Notion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_sales_pipeline_to_Notion.ipynb", "imports": ["naas", "naas_drivers.hubspot, notion", "pandas", "datetime.datetime", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "a0410dbd5e2e886db5230942a8dd104d62fb9101565a66fba5ea54f12ae0a64e", "tool": "HubSpot", "notebook": "Update Task", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#task", "#snippet"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-03-12", "description": "This template will update a task in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_Task.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_Task.ipynb", "imports": ["datetime.datetime, timedelta", "naas_drivers.hubspot", "requests, math", "json", "naas"], "image_url": ""}, {"objectID": "0cde49d174c0baa2b8fdf7be78e7cde303d9bc3e2ea9a4076ba7e01894d316df", "tool": "HubSpot", "notebook": "Update a company using custom properties", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#company", "#naas_drivers", "#snippet", "#update", "#patch"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-09-25", "created_at": "2023-09-25", "description": "This notebook demonstrates how to update a given company in HubSpot using HubSpot default or custom properties.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_company.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "8a175a5d458b09dfe5dbc8c5e40f3a0bbd41192e6a77aa6f922960b017c043e1", "tool": "HubSpot", "notebook": "Update contact", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#update"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2022-02-21", "description": "This notebook allows users to update contact information in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_contact.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "1a66fd4eb09d5f34d95b8451ca85989c9743a9060a6540d11d2c19a559a516bb", "tool": "HubSpot", "notebook": "Update contact using custom properties", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#update", "#patch"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2023-08-29", "description": "This notebook demonstrates how to update a given contact in HubSpot using HubSpot default or custom properties.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_contact_using_custom_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_contact_using_custom_properties.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "fc58ab67c6bf65de49ba644a4fe56839a4aab81c0c594fbfad7fd64ff672f030", "tool": "HubSpot", "notebook": "Update deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook allows users to update deals in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_deal.ipynb", "imports": ["naas_drivers.hubspot"], "image_url": ""}, {"objectID": "308ffca5968aaa53ed2e5beaf26fc4270f3ff740e04278f9f51bcaa5b6008cee", "tool": "HubSpot", "notebook": "Update followers from linkedin", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#linkedin", "#network", "#scheduler", "#naas", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook update the LinkedIn followers count for a contact in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_followers_from_linkedin.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_followers_from_linkedin.ipynb", "imports": ["naas_drivers.hubspot, linkedin", "naas", "pandas"], "image_url": ""}, {"objectID": "69dc47c6359ecfdc7f0345ae2afa727bbd0bdea6bd96d614a1d49028f5e87679", "tool": "HubSpot", "notebook": "Update jobtitle country industry from linkedin", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#linkedin", "#identity", "#scheduler", "#naas", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook update the jobtitle, country and industry for a contact in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_jobtitle_country_industry_from_linkedin.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_jobtitle_country_industry_from_linkedin.ipynb", "imports": ["naas_drivers.hubspot, linkedin", "naas", "pandas"], "image_url": ""}, {"objectID": "73b8a92ef19787ace73fd804dc9fffc4cd440670a11edf54097e734a3151e145", "tool": "HubSpot", "notebook": "Update linkedinbio from google", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#googlesearch", "#scheduler", "#naas", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook update HubSpot linkedin URL based on Google Search with firstname and lastname.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_linkedinbio_from_google.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_linkedinbio_from_google.ipynb", "imports": ["naas_drivers.hubspot", "naas", "pandas", "googlesearch.search", "time", "re"], "image_url": ""}, {"objectID": "f86b412a2bb0447988f91dbda5fc2dd925f5d6ec01dc474ecbd1f3be6999ba96", "tool": "Hugging Face", "notebook": "Ask boolean question to T5", "action": "", "tags": ["#huggingface", "#ml", "#sales", "#ai", "#text"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-08", "description": "## T5-base finetuned on BoolQ (superglue task)\nThis notebook is for demonstrating the training and use of the text-to-text-transfer-transformer (better known as T5) on boolean questions (BoolQ). The example use case is a validator indicating if an idea is environmentally friendly. Nearly any question can be passed into the `query` function (see below) as long as a context to a question is given.\n\nAuthor: Maximilian Frank ([script4all.com](//script4all.com)) - Copyleft license\n\nNotes:\n- The model from [huggingface.co/mrm8488/t5-base-finetuned-boolq](//huggingface.co/mrm8488/t5-base-finetuned-boolq) is used in this example as it is an already trained t5-base model on boolean questions (BoolQ task of superglue).\n- Documentation references on [huggingface.co/transformers/model_doc/t5.html#training](//huggingface.co/transformers/model_doc/t5.html#training), template script on [programming-review.com/machine-learning/t5](//programming-review.com/machine-learning/t5)\n- The greater the model, the higher the accuracy on BoolQ (see [arxiv.org/pdf/1910.10683.pdf](//arxiv.org/pdf/1910.10683.pdf)):\n t5-small|t5-base|t5-large|t5-3B|t5-11B\n -|-|-|-|-\n 76.4%|81.4%|85.4%|89.9%|91.2%", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Hugging%20Face/Hugging_Face_Ask_boolean_question_to_T5.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Hugging%20Face/Hugging_Face_Ask_boolean_question_to_T5.ipynb", "imports": ["json", "torch", "operator.itemgetter", "distutils.util.strtobool", "transformers.AutoTokenizer, AutoModelForSeq2SeqLM", "goods.\", # should be false"], "image_url": ""}, {"objectID": "5968f81ee8ac7fab47f97e24e666efeee74dd873bb1c1444a24459ea0fa9cabf", "tool": "Hugging Face", "notebook": "Naas drivers integration", "action": "", "tags": ["#huggingface", "#nlp", "#huggingface", "#api", "#models", "#transformers", "#sales", "#ai", "#text"], "author": "Gagan Bhatia", "author_url": "https://www.linkedin.com/in/gbhatia30/", "updated_at": "2023-04-12", "created_at": "2021-08-31", "description": "In this notebook, you will be able to explore the Hugging Face transformers package with minimal technical knowledge thanks to Naas low-code drivers.
\nHugging Face is an immensely popular Python library providing pretrained models that are extraordinarily useful for a variety of natural language processing (NLP) tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Hugging%20Face/Hugging_Face_Naas_drivers_integration.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Hugging%20Face/Hugging_Face_Naas_drivers_integration.ipynb", "imports": ["naas_drivers.huggingface", "ant thing in your life right now?\""], "image_url": ""}, {"objectID": "6ae02ceb527a779c1815a5254e6a3b1292f024034c61fa1c62c4dfcb88905990", "tool": "Hugging Face", "notebook": "Question Answering from PDF", "action": "", "tags": ["#huggingface", "#ml", "#question_answer", "#ai", "#text"], "author": "Muhammad Talha Khan", "author_url": "https://www.linkedin.com/in/muhtalhakhan/", "updated_at": "2023-04-12", "created_at": "2022-11-02", "description": "This notebook provides a way to answer questions from PDF documents using Hugging Face's natural language processing capabilities.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Hugging%20Face/Hugging_Face_Question_Answering_from_PDF.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Hugging%20Face/Hugging_Face_Question_Answering_from_PDF.ipynb", "imports": ["transformers.pipeline", "urllib.request", "PyPDF2", "io"], "image_url": ""}, {"objectID": "d7b25ccb94399a05e017b4dbcc1175264b9d63a0846fe91c6e98ae73e7464ce5", "tool": "IFTTT", "notebook": "Post on Twitter", "action": "", "tags": ["#ifttt", "#nocode", "#snippet", "#marketing", "#twitter"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows you to post messages to Twitter using IFTTT.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IFTTT/IFTTT_Post_on_Twitter.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IFTTT/IFTTT_Post_on_Twitter.ipynb", "imports": ["naas_drivers.ifttt"], "image_url": ""}, {"objectID": "c2217c4b3eafedeb845aa615041292cacf60fd6aa3366a80e4d85ab17ac0d9a6", "tool": "IFTTT", "notebook": "Trigger workflow", "action": "", "tags": ["#ifttt", "#nocode", "#snippet", "#marketing"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows users to create automated workflows based on triggers from IFTTT.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IFTTT/IFTTT_Trigger_workflow.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IFTTT/IFTTT_Trigger_workflow.ipynb", "imports": ["naas_drivers.ifttt"], "image_url": ""}, {"objectID": "d6489bb4d5adeb7d00bb71c99521b750528eb0d76f94b0007a217d5902623f0e", "tool": "IMDB", "notebook": "Top Movie", "action": "", "tags": ["#imdb", "#python", "#webscraping", "#imdb", "#analytics", "#operations", "#csv"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-04-12", "created_at": "2021-11-23", "description": "This notebook provides a list of the top-rated movies according to IMDB ratings.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IMDB/Top_IMDB_Movie.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IMDB/Top_IMDB_Movie.ipynb", "imports": ["scrapy", "scrapy", "scrapy.crawler.CrawlerProcess", "scrapy.crawler.CrawlerRunner", "crochet.setup, wait_for", "crochet.setup, wait_for"], "image_url": ""}, {"objectID": "9e77de3cd0e1966b9245a077a2cee42c80084a9a388822b57d33a68f0acb6526", "tool": "INPI", "notebook": "Download PDF recap", "action": "", "tags": ["#inpi", "#pdf", "#snippet", "#url", "#naas", "#societe", "#opendata"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-05-04", "description": "This notebook downloads a PDF summary of INPI (Instituto Nacional da Propriedade Industrial) data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/INPI/INPI_Download_PDF_recap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/INPI/INPI_Download_PDF_recap.ipynb", "imports": ["urllib"], "image_url": ""}, {"objectID": "2802ff736a7d9f625d7bb08a6e63f44d451728998bc8eacf923f17faedb940f7", "tool": "IPyWidgets", "notebook": "Create button", "action": "", "tags": ["#ipywidgets", "#naas", "#secret", "#snippet", "#operation", "#button"], "author": "Ismail CHIHAB", "author_url": "https://www.linkedin.com/in/ismail-chihab-4b0a04202/", "updated_at": "2023-04-12", "created_at": "2022-08-05", "description": "This notebook demonstrates how to use IPyWidgets to create an interactive button.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IPyWidgets/IPyWidgets_Create_button.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IPyWidgets/IPyWidgets_Create_button.ipynb", "imports": ["IPython.display.display, clear_output", "ipywidgets.widgets"], "image_url": ""}, {"objectID": "f810583e80c41aba6409ca9a2f9c0af3b653ab7a0d807b424564d03f1fd6a773", "tool": "IPyWidgets", "notebook": "Create input text and submit button", "action": "", "tags": ["#ipywidgets", "#naas", "#secret", "#snippet", "#operation", "#button", "#text"], "author": "Ismail CHIHAB", "author_url": "https://www.linkedin.com/in/ismail-chihab-4b0a04202/", "updated_at": "2023-04-12", "created_at": "2022-08-05", "description": "This notebook demonstrates how to use IPyWidgets to create an interactive input text box and submit button.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IPyWidgets/IPyWidgets_Create_input_text_and_submit_button.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IPyWidgets/IPyWidgets_Create_input_text_and_submit_button.ipynb", "imports": ["IPython.display.display, clear_output", "ipywidgets.widgets"], "image_url": ""}, {"objectID": "a68d46a0afb9b7c23e894afa2019cc7a7a9f4ee51ebf45ca51289f28af308652", "tool": "IPyWidgets", "notebook": "Setup naas secret", "action": "", "tags": ["#ipywidgets", "#naas", "#secret", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-05", "description": "This notebook provides instructions for setting up a secure connection to a NaaS (Network-as-a-Service) using IPyWidgets.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IPyWidgets/IPyWidgets_Setup_naas_secret.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IPyWidgets/IPyWidgets_Setup_naas_secret.ipynb", "imports": ["IPython.display.display, clear_output", "ipywidgets.widgets", "naas"], "image_url": ""}, {"objectID": "5700cab9e7293ba8a0b3a8c5a05507f0e397b5a649dbab6e1c46d4cad7c7ee1a", "tool": "IPython", "notebook": "Display dynamic link in Jupyter Lab", "action": "# IPython - Display dynamic link in Jupyter Lab", "tags": ["#ipython", "#jupyterlab", "#markdown", "#dynamic", "#link"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-27", "created_at": "2023-09-27", "description": "This notebook shows how to display a link in Jupyter Lab using Markdown syntax.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IPython/IPython_Display_dynamic_link_in_Jupyter_Lab.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IPython/IPython_Display_dynamic_link_in_Jupyter_Lab.ipynb", "imports": ["IPython.display.Markdown"], "image_url": ""}, {"objectID": "2b6a8399ba0ec449ff89d9613b7c9dbefa5e8eb4c3baf8b472fdbdb7847e2b43", "tool": "IUCN", "notebook": "Extinct species", "action": "", "tags": ["#iucn", "#opendata", "#extinctspecies", "#analytics", "#plotly"], "author": "Martin Delasalle", "author_url": "https://github.com/delasalle-sio-martin", "updated_at": "2023-04-12", "created_at": "2021-05-28", "description": "Source : https://www.iucnredlist.org/statistics", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IUCN/IUCN_Extinct_species.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IUCN/IUCN_Extinct_species.ipynb", "imports": ["pandas", "plotly.express"], "image_url": ""}, {"objectID": "63e5f68d32da97478d275e24f56052d1b338bc9447562f7df52aca764f0405cf", "tool": "Insee", "notebook": "Download PDF recap", "action": "", "tags": ["#insee", "#pdf", "#snippet", "#url", "#naas", "#societe", "#opendata"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-05-04", "description": "This notebook downloads PDF summaries of data from the French National Institute of Statistics and Economic Studies (INSEE).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Insee/Insee_Download_PDF_recap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Insee/Insee_Download_PDF_recap.ipynb", "imports": ["urllib"], "image_url": ""}, {"objectID": "8c1d59ba9fc141ddf76ab615ec70620884b5be94f4cde842bd75126ac862db52", "tool": "Instagram", "notebook": "Get stats from posts", "action": "", "tags": ["#instagram", "#snippet", "#dataframe", "#content"], "author": "Mohamed Abidi", "author_url": "https://www.linkedin.com/in/mohamed-abidi-919505192/", "updated_at": "2023-04-12", "created_at": "2022-02-11", "description": "This notebook provides an easy way to analyze Instagram posts and gain insights into their performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Instagram/Instagram_Get_stats_from_posts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Instagram/Instagram_Get_stats_from_posts.ipynb", "imports": ["requests", "json", "datetime", "pandas"], "image_url": ""}, {"objectID": "38c44121d518d242dcfd1209fca1b300a11475f5836b8ae8f214c0b4524816a9", "tool": "Instagram", "notebook": "Post image and caption", "action": "", "tags": ["#instagram", "#snippet", "#content"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows users to post images and captions to their Instagram account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Instagram/Instagram_Post_image_and_caption.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Instagram/Instagram_Post_image_and_caption.ipynb", "imports": ["instabot.Bot", "instabot.Bot", "naas"], "image_url": ""}, {"objectID": "ea1fbba772a47f2a2f57b1c76935f62728ba2bb7749c0edd2edb475b43a35037", "tool": "Integromat", "notebook": "Trigger workflow", "action": "", "tags": ["#integromat", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-23", "description": "This notebook allows you to create automated workflows that are triggered by specific events.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Integromat/Integromat_Trigger_workflow.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Integromat/Integromat_Trigger_workflow.ipynb", "imports": ["naas_drivers.integromat"], "image_url": ""}, {"objectID": "9366cd2a8b5ebabc8fa6722758d297cf0a47d5b09246c09565bfe44c0f0c5350", "tool": "JSON", "notebook": "Convert Python Objects to", "action": "", "tags": ["#json", "#python", "#convert", "#object", "#serialize", "#deserialize"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will show how to convert Python objects to JSON and how to deserialize JSON back into Python objects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Convert_Python_Objects_to_JSON.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Convert_Python_Objects_to_JSON.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "566b67709b26f1097172c3b9c9641f132b8cf9d299ba3b314bda01fa26e3c31f", "tool": "JSON", "notebook": "Pretty print data", "action": "", "tags": ["#json", "#prettyprint", "#data", "#format", "#parse", "#string"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will show how to pretty print JSON data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Pretty_print_JSON_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Pretty_print_JSON_data.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "87d99fa50cdfeb99934671dc8dc2667c10df4a549bcea2874106f99651860146", "tool": "JSON", "notebook": "Read local file", "action": "", "tags": ["#json", "#python", "#read", "#file", "#data", "#parse"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-03-10", "description": "This notebook will demonstrate how to read a json file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Read_local_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Read_local_file.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "9cee4953ea85382e65f4d07efd0a162eb35b120f714fd0da9f0de60f6426bddb", "tool": "JSON", "notebook": "Save dataframe to file", "action": "", "tags": ["#json", "#python", "#file", "#save", "#data"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will demonstrate how to save a DataFrame to a json file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Save_dataframe_to_JSON_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Save_dataframe_to_JSON_file.ipynb", "imports": ["json", "pandas"], "image_url": ""}, {"objectID": "050391ecb5e0318f1aea99870a20423b913b3baef4dfac8b3ecd9d1c32618266", "tool": "JSON", "notebook": "Save dict to file", "action": "", "tags": ["#json", "#python", "#file", "#save", "#data"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-05-09", "created_at": "2023-03-10", "description": "This notebook will demonstrate how to save a dict to a json file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Save_dict_to_JSON_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Save_dict_to_JSON_file.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "c603c422f9e39d2ea960638448b510dbc4027f4cf6c068d0f196a82a161c3fd2", "tool": "JSON", "notebook": "Send to Google Sheets spreadsheet", "action": "", "tags": ["#json", "#gsheet", "#python", "#read", "#file", "#data", "#parse", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will demonstrate how to send a json file to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Send_to_Google_Sheets_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Send_to_Google_Sheets_spreadsheet.ipynb", "imports": ["json", "naas_drivers.gsheet", "pandas"], "image_url": ""}, {"objectID": "d9501bdba4a7b281ae7e32722e5f7f8e7ad52825702b91f62463c937b0ab9129", "tool": "Johns Hopkins", "notebook": "Covid19 Active Cases", "action": "", "tags": ["#johnshopkins", "#opendata", "#analytics", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-27", "description": "This notebook provides an interactive visualization of the active cases of Covid-19 reported by Johns Hopkins University.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Johns%20Hopkins/Johns_Hopkins_Covid19_Active_Cases.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Johns%20Hopkins/Johns_Hopkins_Covid19_Active_Cases.ipynb", "imports": ["pandas", "plotly.express", "plotly.graph_objects", "matplotlib.pyplot"], "image_url": ""}, {"objectID": "d8d061ddd919705d7ea10dbff535f312aa8690112a7689c30b77706e9b482a93", "tool": "Johns Hopkins", "notebook": "Get Covid19 data", "action": "", "tags": ["#johnshopkins", "#opendata", "#analytics", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an easy way to access and analyze Covid19 data from Johns Hopkins University.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Johns%20Hopkins/Johns_Hopkins_Get_Covid19_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Johns%20Hopkins/Johns_Hopkins_Get_Covid19_data.ipynb", "imports": ["pandas", "naas"], "image_url": ""}, {"objectID": "db5fcbb8c6b35101661e8ce19138d4b5ffe286f326252acd8c9993a4f8ea822b", "tool": "Jupyter Notebooks", "notebook": "Add cells in notebook json", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides instructions on how to add cells to a Jupyter Notebook using JSON.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Add_cells_in_notebook_json.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Add_cells_in_notebook_json.ipynb", "imports": ["json", "pprint.pprint"], "image_url": ""}, {"objectID": "6896c6a7f08c8189f132dadc917d7260fd09df359c2465592db7987056bca0c0", "tool": "Jupyter Notebooks", "notebook": "Add tags in cells", "action": "", "tags": ["#jupyternotebooks", "#jupyter", "#awesome-notebooks", "#tags", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook provides a guide to adding tags to cells in Jupyter Notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Add_tags_in_cells.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Add_tags_in_cells.ipynb", "imports": ["os", "json", "pprint.pprint"], "image_url": ""}, {"objectID": "40bc861fbc7e6401524526236bf9efeebd65f31e1cce745a877aa263ff42ac3f", "tool": "Jupyter Notebooks", "notebook": "Apply black on notebook file", "action": "", "tags": ["#jupyter", "#notebook", "#black", "#python", "#formatting", "#style"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-26", "created_at": "2023-04-26", "description": "This notebook explains how to apply the black formatting style to a Jupyter Notebook file. It is usefull for organizations that want to ensure a consistent coding style across their notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Apply_black_on_notebook_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Apply_black_on_notebook_file.ipynb", "imports": ["json", "subprocess"], "image_url": ""}, {"objectID": "831c231ab1ea59f38424b6201727c2f8c65b45b75bf6e6513944957fe8399b71", "tool": "Jupyter Notebooks", "notebook": "Count code characters", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#read", "#codecharacters", "#snippet", "#operations", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides a tool to count the number of characters in code written in Jupyter Notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Count_code_characters.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Count_code_characters.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "3b184500ce95f1ea2824f7968046188e744c2bf9c912d17b346b15a2831ef97e", "tool": "Jupyter Notebooks", "notebook": "Count code lines", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#read", "#codelines", "#snippet", "#operations", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides a tool to count the number of lines of code in a Jupyter Notebook.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Count_code_lines.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Count_code_lines.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "4a5084bb5ec4b1b23f29c6699dddb97d95fb5bd81eb9cfbbc9c5241b2575f500", "tool": "Jupyter Notebooks", "notebook": "Get installs", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#read", "#installs", "#snippet", "#operations", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides instructions for installing Jupyter Notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Get_installs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Get_installs.ipynb", "imports": ["json", "pprint.pprint"], "image_url": ""}, {"objectID": "9fbda94a4556947e1be3d9cba5532b7757857f8dc5fab92ec7ab9df63d3a2a7e", "tool": "Jupyter Notebooks", "notebook": "Get libraries", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#read", "#libraries", "#snippet", "#operations", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides instructions on how to install and use libraries in Jupyter Notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Get_libraries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Get_libraries.ipynb", "imports": ["json", "pprint.pprint", "\" in source and \".\" in source:", "\")[0]", "\")[-1]", "\" not in source and \".\" in source:", "\")[-1]"], "image_url": ""}, {"objectID": "49c918990b576442820a51fda634fe182ae747b6379542038cc96566e894c3af", "tool": "Jupyter Notebooks", "notebook": "Read file json", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#read", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides a guide to reading and manipulating JSON files using Jupyter Notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Read_file_json.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Read_file_json.ipynb", "imports": ["json", "pprint.pprint"], "image_url": ""}, {"objectID": "69cd935098a7bced50fbde048ea679fadd95403925f92771cbfb08e935f17754", "tool": "Jupyter Notebooks", "notebook": "Save file ipynb", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#save", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook allows users to save their work in an interactive, web-based format (.ipynb).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Save_file_ipynb.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Save_file_ipynb.ipynb", "imports": ["json", "pprint.pprint"], "image_url": ""}, {"objectID": "7e1066808d3b59f72af3abe06bd16360aba9c812315e7d4590b08a5ea7e4cc4a", "tool": "Jupyter", "notebook": "Get server uptime", "action": "", "tags": ["#jupyter", "#server", "#uptime", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook provides a way to check the server uptime using Jupyter.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter/Jupyter_Get_server_uptime.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter/Jupyter_Get_server_uptime.ipynb", "imports": ["naas_drivers.jupyter", "os.environ"], "image_url": ""}, {"objectID": "8b7b0d0e546ea07301fe985252766cfa1c1a046fd3771acf0dba7a1bad478638", "tool": "Jupyter", "notebook": "Get user information", "action": "", "tags": ["#jupyter", "#user", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a way to retrieve user information from Jupyter.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter/Jupyter_Get_user_information.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter/Jupyter_Get_user_information.ipynb", "imports": ["naas_drivers.jupyter", "os.environ"], "image_url": ""}, {"objectID": "8853628334515ac0c222cc72944e39192d0127dea12852762c80ced3ea104901", "tool": "Jupyter", "notebook": "Get user session", "action": "", "tags": ["#jupyter", "#user", "#session", "#kernels", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook provides a way to get information about the current user's Jupyter session.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter/Jupyter_Get_user_session.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter/Jupyter_Get_user_session.ipynb", "imports": ["naas_drivers.jupyter", "os.environ"], "image_url": ""}, {"objectID": "580e2e6eb9052fc667d90d6c2853af8778e963531368f1c22199294e3c7f9da5", "tool": "Jupyter", "notebook": "Get user terminal", "action": "", "tags": ["#jupyter", "#user", "#terminal", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook provides a user-friendly interface to access a terminal for running commands.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter/Jupyter_Get_user_terminal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter/Jupyter_Get_user_terminal.ipynb", "imports": ["naas_drivers.jupyter", "os.environ"], "image_url": ""}, {"objectID": "6c5de096a088ddb31aecdc20d57173bc5605c61ba81be7298c86cec24288d8c4", "tool": "Jupyter", "notebook": "Restart server", "action": "", "tags": ["#jupyter", "#server", "#restart", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook provides instructions on how to restart a Jupyter server.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter/Jupyter_Restart_server.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter/Jupyter_Restart_server.ipynb", "imports": ["naas_drivers.jupyter", "os.environ"], "image_url": ""}, {"objectID": "96e73cf9dc93e28d3e1d87b810d335505e2b1fb7a834579b2aa36f26df1e9f3a", "tool": "Kaggle", "notebook": "Download Data", "action": "", "tags": ["#kaggle", "#dataset", "#download", "#data", "#datascience"], "author": "Muhammad Waqar Gul", "author_url": "https://www.linkedin.com/in/waqar-gul", "updated_at": "2023-04-12", "created_at": "2022-10-11", "description": "This notebook provides instructions on how to download data from Kaggle for use in data analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Kaggle/Kaggle_Download_Data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Kaggle/Kaggle_Download_Data.ipynb", "imports": ["opendatasets", "pandas", "opendatasets", "os.path"], "image_url": ""}, {"objectID": "0c9df728db7a93e2a51b17382bce93ac3e3ac414dc2e0fffb72627a0863f4107", "tool": "Knative", "notebook": "Create command file", "action": "", "tags": ["#knative", "#operations", "#dashboards", "#dash", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-22", "description": "This notebook provides instructions on how to create a command file for Knative.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Knative/Knative_Create_command_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Knative/Knative_Create_command_file.ipynb", "imports": [], "image_url": ""}, {"objectID": "658a8244b01dfe532c4faaf8423ce808aca1020f8afdf491d99810b8e1cb4ba1", "tool": "LangChain", "notebook": "CSV Agent", "action": "", "tags": ["#csv", "#agent", "#langchain", "#questionanswering", "#toolkit", "#example"], "author": "Hamid Mukhtar", "author_url": "https://www.linkedin.com/in/mukhtar-hamid/", "updated_at": "2023-06-21", "created_at": "2023-06-01", "description": "This notebook shows how to use agents to interact with a csv. It is mostly optimized for question answering.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LangChain/LangChain_CSV_Agent.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_CSV_Agent.ipynb", "imports": ["langchain", "langchain.agents.create_csv_agent", "langchain.llms.OpenAI", "langchain.chat_models.ChatOpenAI", "langchain.agents.agent_types.AgentType", "pandas", "naas"], "image_url": ""}, {"objectID": "82653462f187b1612eabf3410fb8c69cd5f3bc64d1b6a7828d840867d3d86cfd", "tool": "LangChain", "notebook": "Gmail Toolkit", "action": "", "tags": ["#langchain", "#gmail", "#toolkit", "#api", "#email", "#connect"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook walks through connecting a LangChain email to the Gmail API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LangChain/LangChain_Gmail_Toolkit.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_Gmail_Toolkit.ipynb", "imports": ["langchain", "langchain.llms.OpenAI", "langchain.agents.agent_toolkits.GmailToolkit", "langchain.agents.initialize_agent, AgentType", "naas"], "image_url": ""}, {"objectID": "97b75457b5be4aa0267637c05db4895ccd911ef922cded10242a313ab1245dbb", "tool": "LangChain", "notebook": "JSON Agent", "action": "", "tags": ["#json", "#agent", "#langchain", "#toolkit", "#example", "#python"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook showcases an agent designed to interact with large JSON/dict objects. This is useful when you want to answer questions about a JSON blob that\u2019s too large to fit in the context window of an LLM. The agent is able to iteratively explore the blob to find what it needs to answer the user\u2019s question.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LangChain/LangChain_JSON_Agent.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_JSON_Agent.ipynb", "imports": ["langchain", "validators", "langchain.agents.agent_toolkits.JsonToolkit", "langchain.tools.json.tool.JsonSpec", "langchain.agents.create_json_agent", "langchain.llms.openai.OpenAI", "json", "urllib.request.urlopen", "validators", "naas", "pandas"], "image_url": ""}, {"objectID": "cbffbc54c632f632e483b97eefb687edc995365015f26e51df9e55644b0272ac", "tool": "LangChain", "notebook": "Pandas Dataframe Agent", "action": "", "tags": ["#langchain", "#pandas", "#dataframe", "#agent", "#python", "#toolkit"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-21", "created_at": "2023-06-01", "description": "This notebook shows how to use agents to interact with a pandas dataframe. It is mostly optimized for question answering.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LangChain/LangChain_Pandas_Dataframe_Agent.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_Pandas_Dataframe_Agent.ipynb", "imports": ["langchain", "langchain.agents.create_pandas_dataframe_agent", "langchain.llms.OpenAI", "pandas", "naas"], "image_url": ""}, {"objectID": "fe3d8478a7a0ec3a8547714e3830c73fe246cb33bbe5bafbf00d39bee94ce2e9", "tool": "LeFigaro", "notebook": "House Price analysis", "action": "", "tags": ["#lefigaro", "#investors", "#immobilier", "#markdown", "#graph", "#chart", "#analytics"], "author": "Mahanamana Andriamiharisoa", "author_url": "https://www.linkedin.com/in/mahanamana/", "updated_at": "2023-04-12", "created_at": "2022-07-08", "description": "This notebook provides an analysis of house prices in France using data from LeFigaro.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LeFigaro/LeFigaro_House_Price_analysis.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LeFigaro/LeFigaro_House_Price_analysis.ipynb", "imports": ["requests", "bs4.BeautifulSoup", "pandas", "numpy", "matplotlib.pyplot", "plotly.express", "naas"], "image_url": ""}, {"objectID": "479b87603a0cbdf9ac2a26af7a59038d199f9ac114b46261f5550b23ab40220d", "tool": "LinkedIn Sales Navigator", "notebook": "Extract Leads List from URL", "action": "", "tags": ["#linkedin", "#salesnavigator", "#extract", "#leads"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-27", "description": "This notebook will show how to extract a list of leads from a URL using LinkedIn Sales Navigator.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn%20Sales%20Navigator/LinkedIn_Sales_Navigator_Extract_Leads_List_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn%20Sales%20Navigator/LinkedIn_Sales_Navigator_Extract_Leads_List_from_URL.ipynb", "imports": ["naas_drivers.linkedin_salesnavigator", "naas"], "image_url": ""}, {"objectID": "1b0477f9d8333372b2c07f480a0d743097d611eff7c7a7600095ae3b813cbded", "tool": "LinkedIn Sales Navigator", "notebook": "Send Leads to Spreadsheet", "action": "", "tags": ["#linkedin", "#salesnavigator", "#extract", "#leads", "#gsheet", "#leadgen"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-02", "description": "This notebook send a list of leads generated by LinkedIn Sales Navigator to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn%20Sales%20Navigator/LinkedIn_Sales_Navigator_Send_Leads_to_Spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn%20Sales%20Navigator/LinkedIn_Sales_Navigator_Send_Leads_to_Spreadsheet.ipynb", "imports": ["naas_drivers.linkedin_salesnavigator", "naas_drivers.gsheet", "naas"], "image_url": ""}, {"objectID": "9f5596b26533283a108fba2a2dfd62794659f196cef87ccc1649802a6a85844d", "tool": "LinkedIn", "notebook": "Accept all invitations and send first message", "action": "", "tags": ["#linkedin", "#content", "#operations", "#automation", "#invitation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-05-29", "created_at": "2022-04-05", "description": "This notebook helps you quickly and easily accept all LinkedIn invitations and send a personalized introductory message to each new connection.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Accept_all_invitations_and_send_first_message.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Accept_all_invitations_and_send_first_message.ipynb", "imports": ["naas", "naas_drivers.linkedin", "pandas"], "image_url": ""}, {"objectID": "e45e2cd2d424c1f1399552df2148f8494e84c0aa7f98f1ab105f7d4cdd0e8a7d", "tool": "LinkedIn", "notebook": "Accept invitation received", "action": "", "tags": ["#linkedin", "#content", "#operations", "#snippet", "#invitation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-05-29", "created_at": "2022-04-05", "description": "This notebook allows you to accept invitations to connect on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Accept_invitation_received.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Accept_invitation_received.ipynb", "imports": ["naas_drivers.linkedin", "pandas"], "image_url": ""}, {"objectID": "8ba17ce043515c04a2f3081afbd6904e272b708e06388b566b4a286a2fd7d785", "tool": "LinkedIn", "notebook": "Chat about my latest profile posts", "action": "", "tags": ["#linkedin", "#profile", "#post", "#stats", "#naas_drivers", "#content", "#automation", "#csv"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-07-26", "created_at": "2023-07-24", "description": "This notebook enables you to converse inside MyChatGPT about your most recent LinkedIn posts using a CSV file stored in your Naas Lab and a JSON plugin asset. Data is updated and replaced with each run.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Chat_about_my_latest_profile_posts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Chat_about_my_latest_profile_posts.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas", "os", "json", "wordcloud.WordCloud", "wordcloud.WordCloud", "matplotlib.pyplot", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b6b615ac66034a7ebfa52b341d1849c0352ec471108d940809c2477e5fa83f15", "tool": "LinkedIn", "notebook": "Create Post", "action": "", "tags": ["#linkedin", "#create", "#api", "#post", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2023-03-20", "description": "This notebook creates a post using Linkedin API and Supabase.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Create_Post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Create_Post.ipynb", "imports": ["os", "supabase.create_client, Client", "supabase.create_client, Client", "naas", "requests", "json", "pprint.pprint"], "image_url": ""}, {"objectID": "78ec6637e7d863b7e458ba7b49172446db1057cb307c1160da7391c0fb19f54c", "tool": "LinkedIn", "notebook": "Create posts metrics dashboard", "action": "", "tags": ["#linkedin", "#dashboard", "#plotly", "#dash", "#naas", "#asset", "#automation", "#analytics"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-09-06", "description": "This notebook provides a dashboard to track the performance metrics of posts created on LinkedIn. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.
", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Create_posts_metrics_dashboard.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Create_posts_metrics_dashboard.ipynb", "imports": ["os", "os.environ", "pandas", "naas", "datetime.datetime", "plotly.graph_objects", "plotly.express", "plotly.subplots.make_subplots", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc, Input, Output, State", "dash_bootstrap_components._components.Container.Container", "dash.exceptions.PreventUpdate"], "image_url": ""}, {"objectID": "11b2c07be26f4a540e850f376dd2cfffa6b41699fbb48e33fd0a5eecd9155e20", "tool": "LinkedIn", "notebook": "Extract content world cloud", "action": "", "tags": ["#linkedin", "#worldcloud", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook provides a way to extract content from LinkedIn and visualize it in a word cloud. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Extract_content_world_cloud.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Extract_content_world_cloud.ipynb", "imports": ["wordcloud.WordCloud", "wordcloud.WordCloud", "matplotlib.pyplot", "pandas"], "image_url": ""}, {"objectID": "f16e388f3fc8807c45263b666b7844f2b411a774e745b508c92314292953a44a", "tool": "LinkedIn", "notebook": "Follow company followers", "action": "", "tags": ["#linkedin", "#company", "#followers", "#naas_drivers", "#analytics", "#automation", "#csv", "#html", "#image", "#content", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-04-22", "description": "This notebook allows you to track and follow the followers of a company on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_company_followers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_company_followers.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "7d69ccdb7722e129fb596d4ac313a428ceb333e3b508039dd77e8d57002d0530", "tool": "LinkedIn", "notebook": "Follow connections from profile", "action": "", "tags": ["#linkedin", "#network", "#connections", "#naas_drivers", "#analytics", "#csv", "#html", "#image", "#content", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-11", "description": "This notebook allows you to follow connections from a LinkedIn profile to build your network.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_connections_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_connections_from_profile.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "0c1887da9a6a5b0e6944b92de5b8d5fe6809cead583534b47781b405fc1ad407", "tool": "LinkedIn", "notebook": "Follow content comments monthly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to track and analyze the comments on your LinkedIn content each month. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_comments_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_comments_monthly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "3add0154c45189d53227375a9eb51eaf962e8d47a92e629fcfdfb5f359658c4c", "tool": "LinkedIn", "notebook": "Follow content comments weekly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to track and follow comments on content posted on LinkedIn on a weekly basis. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_comments_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_comments_weekly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "7bd1a5021d27c602388c8453a5e295b65f4ce4e34ebeb32de85ec94654b656d9", "tool": "LinkedIn", "notebook": "Follow content engagements monthly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook provides a monthly overview of content engagements on LinkedIn. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_engagements_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_engagements_monthly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "5ad7f9c5d30b05a69996fc91685fc7039d55107f55b3b76bb9a640fefdf96d05", "tool": "LinkedIn", "notebook": "Follow content engagements weekly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook helps you track and analyze your weekly content engagements on LinkedIn. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_engagements_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_engagements_weekly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "cc1b4c23ccb3f6694fab05812f8888d458df1076bb27bd5d1406a42e8865b339", "tool": "LinkedIn", "notebook": "Follow content frequency", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows users to track how often they post content on LinkedIn and follow the frequency of their posts. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_frequency.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_frequency.ipynb", "imports": ["naas_drivers.linkedin", "os.path", "naas", "pandas", "datetime.datetime", "plotly.graph_objects", "plotly.subplots.make_subplots"], "image_url": ""}, {"objectID": "86d43a87776a1959277b4f7cbfea2d6a8c9cd83dc103e7ea40196db6c68366e6", "tool": "LinkedIn", "notebook": "Follow content likes monthly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to track and follow content on LinkedIn on a monthly basis. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_likes_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_likes_monthly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "5d645f65d3876fcb8f68ec55b61551bc8fcc9dc16ce4393003cb9355d28022f7", "tool": "LinkedIn", "notebook": "Follow content likes weekly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to keep track of the content you like on LinkedIn and follow it on a weekly basis. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_likes_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_likes_weekly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "09c380b66d03f35f056daeb6875ab67d012a9c943260b272f60ced069ad5998d", "tool": "LinkedIn", "notebook": "Follow content published by weekdays by months", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-08-04", "description": "This notebook allows you to track and follow content published on LinkedIn by day of the week and month. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_published_by_weekdays_by_months.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_published_by_weekdays_by_months.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects", "pandas.tseries.offsets.MonthEnd", "calendar", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "12fcfa952a1daa79c27b82ab8f6061ca506e6b7542ebfee9a844df936c90d21d", "tool": "LinkedIn", "notebook": "Follow content published monthly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to keep track of content published on LinkedIn each month. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_published_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_published_monthly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "eac2762bc29e79db13a5652221c17ebee0b37012a8b88da0af2890c432339322", "tool": "LinkedIn", "notebook": "Follow content published weekly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to stay up-to-date with the latest content published on LinkedIn each week. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_published_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_published_weekly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "435a57172667176064f133da7888849c0f1209e8c22bf789fd0e8ab470c3952a", "tool": "LinkedIn", "notebook": "Follow content views by weekdays by hours", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-08-04", "description": "This notebook provides an analysis of the views of content on LinkedIn by day of the week and hour of the day. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_views_by_weekdays_by_hours.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_views_by_weekdays_by_hours.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects", "pandas.tseries.offsets.MonthEnd", "calendar", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "c480f026f88fcb2491576b76e6e0e861d709dcbed902fea6ab5407a3394358ac", "tool": "LinkedIn", "notebook": "Follow content views monthly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook provides a monthly overview of the content you are following on LinkedIn. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_views_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_views_monthly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "c4ef3bf53e18ed4570a193932e08ef3214f5a9ddb23e526db77550e66bc7963c", "tool": "LinkedIn", "notebook": "Follow content views weekly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to track and analyze your weekly content views on LinkedIn. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_views_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_views_weekly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "c316be559091eb40bdec9c2b23ad51baf7e859b730cd2fbf93b6b0519b3012a7", "tool": "LinkedIn", "notebook": "Follow number of connections monthly", "action": "", "tags": ["#linkedin", "#network", "#connections", "#naas_drivers", "#analytics", "#csv", "#html", "#image", "#content", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-05-17", "description": "This notebook tracks the number of connections made on LinkedIn each month.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_number_of_connections_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_number_of_connections_monthly.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas", "plotly.graph_objects", "plotly.subplots.make_subplots"], "image_url": ""}, {"objectID": "90e6b184ce0fb7a0025c4af64f6ced3cc38deae800bfed2b23bf3f696371c259", "tool": "LinkedIn", "notebook": "Generate leads from posts", "action": "", "tags": ["#linkedin", "#post", "#comments", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-05-29", "created_at": "2022-01-09", "description": "This notebook provides a guide to leveraging LinkedIn posts to generate leads for your business.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Generate_leads_from_posts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Generate_leads_from_posts.ipynb", "imports": ["naas_drivers.linkedin, hubspot", "pandas", "numpy", "naas", "datetime.datetime, timedelta", "requests", "json"], "image_url": ""}, {"objectID": "38e3a7391f8093e9d1678cb2eb88f6606c087cf81d5dabc31334567fb05b7b55", "tool": "LinkedIn", "notebook": "Get age and gender from profile picture", "action": "", "tags": ["#linkedin", "#machinelearning", "#profile", "#identity", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Nikolaj Groeneweg", "author_url": "https://www.linkedin.com/in/njgroene/", "updated_at": "2023-05-29", "created_at": "2022-06-13", "description": "This notebook estimates a person's age and gender based on their LinkedIn profile picture.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_age_and_gender_from_profile_picture.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_age_and_gender_from_profile_picture.ipynb", "imports": ["naas_drivers.linkedin", "urllib", "naas", "PIL.Image", "pandas", "numpy", "torch", "torch.nn", "torchvision", "torchvision.datasets, models, transforms", "torchvision", "torchvision.datasets, models, transforms", "torch_mtcnn.detect_faces", "torch_mtcnn.show_bboxes", "torch_mtcnn.detect_faces", "torch_mtcnn.show_bboxes"], "image_url": ""}, {"objectID": "1f9e57be7c17bbd6f7630dec0d4bf80fe2e2184897da9ef6eb74849aa2350da2", "tool": "LinkedIn", "notebook": "Get comments from post", "action": "", "tags": ["#linkedin", "#post", "#comments", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-26", "created_at": "2021-06-17", "description": "\"This notebook is designed to extract comments from a specific LinkedIn post and organize the data into a structured format. It generates a DataFrame with various details about each comment and the user who posted it.\n\nThe DataFrame includes the following columns:\n\n- `PROFILE_ID`: The unique identifier associated with the LinkedIn profile of the user who posted the comment.\n- `PROFILE_URL`: The URL leading to the LinkedIn profile of the user who posted the comment.\n- `PUBLIC_ID`: The public identifier visible in the URL of the user's LinkedIn profile.\n- `FIRSTNAME`: The first name of the user who posted the comment.\n- `LASTNAME`: The last name of the user who posted the comment.\n- `FULLNAME`: The full name of the user who posted the comment.\n- `OCCUPATION`: The professional role or job title of the user who posted the comment.\n- `PROFILE_PICTURE`: The URL of the user's LinkedIn profile picture.\n- `BACKGROUND_PICTURE`: The URL of the user's LinkedIn background picture.\n- `PROFILE_TYPE`: The type of LinkedIn profile (e.g., individual, company).\n- `TEXT`: The actual text of the comment posted by the user.\n- `CREATED_TIME`: The timestamp indicating when the comment was posted.\n- `LANGUAGE`: The language in which the comment was written.\n- `DISTANCE`: The degree of connection between the user who posted the comment and the profile viewing the post (e.g., 1st-degree connection, 2nd-degree connection).\n- `COMMENTS`: The number of comments on the user's comment.\n- `LIKES`: The number of likes on the user's comment.\n- `POST_URL`: The URL of the LinkedIn post where the comment was made.\n- `DATE_EXTRACT`: The timestamp indicating when the comment data was extracted.\n\nThe notebook is a useful tool for social media analysis and can help in understanding user engagement on LinkedIn posts.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_comments_from_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_comments_from_post.ipynb", "imports": ["naas", "naas_drivers.linkedin"], "image_url": ""}, {"objectID": "eb94b13f89163a7980a2cf632af1e207573c35271920d52121659af1d90e0aa5", "tool": "LinkedIn", "notebook": "Get company followers", "action": "", "tags": ["#linkedin", "#company", "#followers", "#naas_drivers", "#automation", "#csv", "#content"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-04-22", "description": "This templates will get all followers from your LinkedIn company and save it into a CSV.

\n**Available columns :**\n- FIRSTNAME : First name\n- LASTNAME : Last name\n- OCCUPATION : Text below the name in the profile page\n- PROFILE_PICTURE : Profile picture URL\n- PROFILE_URL : Profile URL\n- PROFILE_ID : LinkedIn profile id\n- PUBLIC_ID : LinkedIn public profile id\n- FOLLOWED_AT : Date of following company\n- DISTANCE : Distance between your profile", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_company_followers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_company_followers.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "naas"], "image_url": ""}, {"objectID": "2ed63b3d62d9a60d7600c9811fcb83034ec2ccf8fcebe4d04a0b84c93e7259bd", "tool": "LinkedIn", "notebook": "Get company posts stats", "action": "", "tags": ["#linkedin", "#company", "#post", "#stats", "#naas_drivers", "#content", "#automation", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-23", "created_at": "2022-06-30", "description": "This notebook fetches your company's post statistics from LinkedIn and stores them in a CSV file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_company_posts_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_company_posts_stats.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "0a0c8e7351a55631596ec7e7867df20d01ab86dacc006501336aeefc3b9ec15c", "tool": "LinkedIn", "notebook": "Get connections from network", "action": "", "tags": ["#linkedin", "#network", "#connections", "#naas_drivers", "#analytics", "#csv", "#html", "#image", "#content", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-26", "created_at": "2022-03-03", "description": "This notebook extracts your connections from your LinkedIn profile. It generates a dataframe that includes the following fields: the first and last name of the connection ('FIRSTNAME', 'LASTNAME'), the description present below the name on the profile page ('OCCUPATION'), the date when the connection was made ('CREATED_AT'), the URL of the profile ('PROFILE_URL'), the URL of the profile picture ('PROFILE_PICTURE'), the LinkedIn profile id of the connection ('PROFILE_ID'), and the LinkedIn public profile id of the connection ('PUBLIC_ID').\"", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_connections_from_network.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_connections_from_network.ipynb", "imports": ["naas_drivers.linkedin", "naas", "os"], "image_url": ""}, {"objectID": "3039c637364b8851d8723243b9ac3792d374d33e6e4aa17d7912f7987a3c9fdf", "tool": "LinkedIn", "notebook": "Get contact from profile", "action": "", "tags": ["#linkedin", "#profile", "#contact", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook allows you to extract contact information from LinkedIn profiles.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_contact_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_contact_from_profile.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "dba7ad6aa93d52b27f68ac38681d27ba843f3eecf2c50d6f79b56cf7a744a87d", "tool": "LinkedIn", "notebook": "Get all your conversations", "action": "", "tags": ["#linkedin", "#messaging", "#conversations", "#sales", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-22", "created_at": "2021-06-18", "description": "This notebook get all your conversations from LinkedIn with the last message sent.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_conversations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_conversations.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "ba5a15c282b5e9189b71ddc1dafa3d17bb78e85e011834fece907fad38a80576", "tool": "LinkedIn", "notebook": "Get followers from network", "action": "", "tags": ["#linkedin", "#network", "#followers", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook provides a guide to gaining followers on LinkedIn by leveraging your existing network.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_followers_from_network.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_followers_from_network.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "46d52b8081ec592286caf79ad464265e2ea170f657d869b90154afebc172fdaa", "tool": "LinkedIn", "notebook": "Get guests from event", "action": "", "tags": ["#linkedin", "#event", "#guests", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook provides a guide to using LinkedIn to connect with attendees of an event.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_guests_from_event.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_guests_from_event.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "28a47ab167568046a591d40544558a84e3385a22f3d151363bc6216f8a0b0159", "tool": "LinkedIn", "notebook": "Get identity from profile", "action": "", "tags": ["#linkedin", "#profile", "#identity", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook helps you extract identity information from LinkedIn profiles.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_identity_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_identity_from_profile.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "7e64f993d24b11cfe449c8b54a0b60cc51fdabf34ef7ecab7303e3f1cf2b46e4", "tool": "LinkedIn", "notebook": "Get info from company", "action": "", "tags": ["#linkedin", "#company", "#info", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-21", "description": "This notebook provides a way to access and analyze data from LinkedIn to gain insights about companies.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_info_from_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_info_from_company.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "e810951640a697452790d8df52dcefc6fe0b153852fdbc64b02f6d9d408908dd", "tool": "LinkedIn", "notebook": "Get invitations received", "action": "", "tags": ["#linkedin", "#content", "#operations", "#snippet", "#invitation", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-05-29", "created_at": "2022-04-05", "description": "This notebook provides an overview of invitations received on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_invitations_received.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_invitations_received.ipynb", "imports": ["naas_drivers.linkedin", "pandas"], "image_url": ""}, {"objectID": "0cb2069ad12899638d06c4e58ca80fe82859e4a8b1129cd506a0f5d9cd3f2219", "tool": "LinkedIn", "notebook": "Get invitations sent", "action": "", "tags": ["#linkedin", "#content", "#operations", "#snippet", "#invitation", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-05-29", "created_at": "2022-04-07", "description": "This notebook helps you to send invitations to connect on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_invitations_sent.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_invitations_sent.ipynb", "imports": ["naas_drivers.linkedin", "pandas"], "image_url": ""}, {"objectID": "f4b40da212ddcec161cf5ee03acc8fc0ef067e2d7a6994aac0f9baa88261a3aa", "tool": "LinkedIn", "notebook": "Get likes from post", "action": "", "tags": ["#linkedin", "#post", "#likes", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-26", "created_at": "2021-06-17", "description": "\"This notebook is engineered to compile a list of profiles that have liked a specific LinkedIn post, and it organizes the data into a structured and easily digestible format. It creates a DataFrame that encompasses the following columns:\n\n- `PROFILE_ID`: The unique identifier for each LinkedIn profile.\n- `PROFILE_URL`: The URL of the individual's LinkedIn profile.\n- `PUBLIC_ID`: The public identifier visible in the URL of the user's LinkedIn profile.\n- `FIRSTNAME`: The first name of the LinkedIn user.\n- `LASTNAME`: The last name of the LinkedIn user.\n- `FULLNAME`: The full name of the LinkedIn user.\n- `OCCUPATION`: The professional title or job role of the LinkedIn user.\n- `PROFILE_PICTURE`: The URL of the LinkedIn user's profile picture.\n- `BACKGROUND_PICTURE`: The URL of the LinkedIn user's background picture.\n- `PROFILE_TYPE`: The type of LinkedIn profile (e.g., individual, company).\n- `REACTION_TYPE`: The type of reaction (like, love, insightful, etc.) the user has given to the post.\n- `POST_URL`: The URL of the LinkedIn post that received the reaction.\n- `DATE_EXTRACT`: The timestamp of when the reaction data was extracted.\n\nThis notebook serves as a valuable tool for social media analysis, providing insights into user engagement on LinkedIn posts.\"", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_likes_from_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_likes_from_post.ipynb", "imports": ["naas", "naas_drivers.linkedin"], "image_url": ""}, {"objectID": "fcea0fc5a4922e0261e90f804fc6bfe4af88a3af23e01708e25ad9196bc4e26e", "tool": "LinkedIn", "notebook": "Get messages from conversation", "action": "", "tags": ["#linkedin", "#message", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook allows you to access all messages from a LinkedIn conversation using the conversation URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_messages_from_conversation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_messages_from_conversation.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "40b7886be679eaf7d0c1b0d2f739297554c4a26f467bd3cabe692ae7e200d492", "tool": "LinkedIn", "notebook": "Get network from profile", "action": "", "tags": ["#linkedin", "#profile", "#network", "#followers", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook helps you to quickly and easily build your professional network on LinkedIn by extracting contacts from your profile.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_network_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_network_from_profile.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "772920fe39026c5b2f7ac54cbe59920fd5190a8a331bbdca43cb6d62412e6dfc", "tool": "LinkedIn", "notebook": "Get polls from post", "action": "", "tags": ["#linkedin", "#post", "#polls", "#naas_drivers", "#content", "#analytics", "#image", "#html", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-01-27", "description": "This notebook allows users to get poll results from their LinkedIn posts.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_polls_from_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_polls_from_post.ipynb", "imports": ["naas_drivers.linkedin", "plotly.express"], "image_url": ""}, {"objectID": "c3bbc0a688cb73907fda0ee047c06ac4c28ead5e92bb3c9be20f01a199b9d9c6", "tool": "LinkedIn", "notebook": "Get posts engagements", "action": "", "tags": ["#linkedin", "#posts", "#interactions", "#metrics", "#analytics", "#automation", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-08-04", "description": "This notebook provides insights into how to increase engagement on LinkedIn posts. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_posts_engagements.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_posts_engagements.ipynb", "imports": ["naas", "pandas", "datetime.datetime"], "image_url": ""}, {"objectID": "1da4b1cd630239550bc3c7fab1f27f151766aaec25a552b97308ba1751c8ee8b", "tool": "LinkedIn", "notebook": "Get profile information", "action": "", "tags": ["#linkedin", "#profile", "#resume", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-10-06", "description": "This notebook allows you to access and analyze profile information from LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_profile_information.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_profile_information.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "ff638a6ff20341b8d9c703bd58fb5088b4bfd7df4f07be972ae77d964ad9eb84", "tool": "LinkedIn", "notebook": "Get profile posts stats", "action": "", "tags": ["#linkedin", "#profile", "#post", "#stats", "#naas_drivers", "#content", "#automation", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-23", "created_at": "2022-06-30", "description": "This notebook fetches your profile's post statistics from LinkedIn and stores them in a CSV file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_profile_posts_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_profile_posts_stats.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "8b7569435004cb9dd156456bcf7d1d807f5b4fc77c072b46ebc223f9b671ad18", "tool": "LinkedIn", "notebook": "Get resume from profile", "action": "", "tags": ["#linkedin", "#profile", "#resume", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-10-14", "description": "This notebook allows users to extract resumes from LinkedIn profiles.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_resume_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_resume_from_profile.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "14515451ee7c352417fc76bfd5acc3163dd04872ac20feb2a0a18fe0bda7db51", "tool": "LinkedIn", "notebook": "Get sentiment analysis from post comments", "action": "", "tags": ["#linkedin", "#sentimentanalysis", "#api", "#python", "#nlp", "#textanalysis"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-10", "created_at": "2023-08-10", "description": "This notebook provides a sentiment analysis of comments from LinkedIn post. This is useful to understand the sentiment of their posts and the reactions of their followers. The five adjectives that will be used to analyze comment sentiment on LinkedIn are the following:\n- \"Praise\" - This is for highly positive comments that express admiration or approval. These comments often include compliments or positive feedback.\n- \"Supportive\" - This is for positive comments that may not necessarily contain high praise but show agreement, support, or encouragement.\n- \"Neutral\" - This is for comments that are neither positive nor negative, often factual statements or questions without any clear positive or negative connotations.\n- \"Constructive\" - This is for comments that may seem negative but are intended to provide constructive feedback or suggest improvements.\n- \"Disapproving\" - This is for comments that express disagreement, criticism, or negative feedback.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_sentiment_analysis_from_post_comments.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_sentiment_analysis_from_post_comments.ipynb", "imports": ["naas_drivers.linkedin", "openai", "openai", "pandas", "datetime.datetime", "naas", "plotly.express"], "image_url": ""}, {"objectID": "484bd5a79481d84712cb9422e5af9b6dead06ecd0eb1fb6a1acc01dc13006e29", "tool": "LinkedIn", "notebook": "Get sentiment emotion irony offensiveness from comments", "action": "", "tags": ["#linkedin", "#nlp", "#transformers", "#ai", "#post", "#comments", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Nikolaj Groeneweg", "author_url": "https://www.linkedin.com/in/njgroene/", "updated_at": "2023-05-29", "created_at": "2022-06-20", "description": "This notebook gets all the comments on a LinkedIn post, and performs sentiment analysis, emotion classification and some semantic analysis on them. \nIt classifies each comment and returns the following information:\n\n- is the comment positive, negative or neutral?\n- is the comment ironic?\n- is the comment offensive?\n- does the comment express joy, optimism, anger or sadness?", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_sentiment_emotion_irony_offensiveness_from_comments.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_sentiment_emotion_irony_offensiveness_from_comments.ipynb", "imports": ["naas_drivers.linkedin", "transformers.pipeline", "transformers.AutoModelForSequenceClassification", "transformers.TFAutoModelForSequenceClassification", "transformers.AutoTokenizer", "numpy", "scipy.special.softmax", "csv", "urllib.request", "os.path", "naas"], "image_url": ""}, {"objectID": "e60798c0bb96ef5ed0f5bbc38d36550eb2ca05d7a8db31333acbb4e0829ed36d", "tool": "LinkedIn", "notebook": "Get stats from post", "action": "", "tags": ["#linkedin", "#post", "#stats", "#naas_drivers", "#snippet", "#content", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook provides a way to track and analyze the performance of posts on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_stats_from_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_stats_from_post.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "454ba60f826a23c1da2e7a14200ba258bc48c26ab0b4e2546278884c5fa1967c", "tool": "LinkedIn", "notebook": "Ignore invitation received", "action": "", "tags": ["#linkedin", "#content", "#operations", "#snippet", "#invitation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-05-29", "created_at": "2022-04-05", "description": "This notebook is for tracking invitations received on LinkedIn that have been ignored.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Ignore_invitation_received.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Ignore_invitation_received.ipynb", "imports": ["naas_drivers.linkedin", "pandas"], "image_url": ""}, {"objectID": "ffa5a37b784ef43241ffda33902293d423ba8d87869bc8b3e82b3420788da443", "tool": "LinkedIn", "notebook": "Maintain company posts stats database", "action": "", "tags": ["#linkedin", "#company", "#post", "#stats", "#naas_drivers", "#content", "#automation", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-23", "created_at": "2022-06-30", "description": "This notebook fetches your company's post statistics from LinkedIn and stores them in a CSV file. It then updates a select number of entries to track the progress of your statistics over time. This method helps to minimize the number of requests made to the LinkedIn API, reducing the risk of being banned due to excessive usage. Additionally, this CSV database can be conveniently reused in other processes, such as retrieving interactions from post URLs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Maintain_company_posts_stats_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Maintain_company_posts_stats_database.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas"], "image_url": ""}, {"objectID": "987989807dcbdb028cbd911edaf7b3f3365602bccc22964ebd83fb60442bba77", "tool": "LinkedIn", "notebook": "Maintain profile posts stats database", "action": "", "tags": ["#linkedin", "#profile", "#post", "#stats", "#naas_drivers", "#content", "#automation", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-23", "created_at": "2023-08-23", "description": "This notebook fetches your profile's post statistics from LinkedIn and stores them in a CSV file. It then updates a select number of entries to track the progress of your statistics over time. This method helps to minimize the number of requests made to the LinkedIn API, reducing the risk of being banned due to excessive usage. Additionally, this CSV database can be conveniently reused in other processes, such as retrieving interactions from post URLs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Maintain_profile_posts_stats_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Maintain_profile_posts_stats_database.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas"], "image_url": ""}, {"objectID": "cf79c294525d2cb1495b9d0a19e50676f1eadac2aa2fa738fe2be626f61d807d", "tool": "LinkedIn", "notebook": "Send comments from post to gsheet", "action": "", "tags": ["#linkedin", "#post", "#comments", "#gsheet", "#naas_drivers", "#content", "#snippet", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-17", "description": "This notebook allows users to automatically send comments from a LinkedIn post to a Google Sheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_comments_from_post_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_comments_from_post_to_gsheet.ipynb", "imports": ["naas_drivers.linkedin, gsheet", "random", "time", "pandas", "datetime.datetime"], "image_url": ""}, {"objectID": "0b5da370401973d25b59a20591783fd711110252b8b455cda4e34c1c0be273c1", "tool": "LinkedIn", "notebook": "Send company followers to Google Sheets", "action": "", "tags": ["#linkedin", "#company", "#followers", "#naas_drivers", "#automation", "#googlesheets", "#content"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-04-22", "description": "This notebook allows users to export their LinkedIn company followers to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_company_followers_to_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_company_followers_to_Google_Sheets.ipynb", "imports": ["naas_drivers.linkedin, gsheet", "pandas", "naas"], "image_url": ""}, {"objectID": "197e953f50f2bd29e259cadd4568587ab0f2ee2cff1f47ed233a69253f419c4f", "tool": "LinkedIn", "notebook": "Send connections from network to gsheet", "action": "", "tags": ["#linkedin", "#network", "#connections", "#naas_drivers", "#csv", "#automation", "#content", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-17", "description": "This notebook allows users to export their LinkedIn connections to a Google Sheet for easy organization and tracking.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_connections_from_network_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_connections_from_network_to_gsheet.ipynb", "imports": ["naas_drivers.linkedin, gsheet", "naas", "pandas"], "image_url": ""}, {"objectID": "87b880ff840a772458fb40959783a6f1c58c8ade4b163685888a411f3096a25e", "tool": "LinkedIn", "notebook": "Send conversation to HubSpot communication", "action": "", "tags": ["#linkedin", "#message", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook send a LinkedIn conversation with all messages to a contact HubSpot communication.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_conversation_to_HubSpot_communication.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_conversation_to_HubSpot_communication.ipynb", "imports": ["naas_drivers.linkedin", "naas", "datetime.datetime, timezone", "requests", "pandas"], "image_url": ""}, {"objectID": "085902bb7fa3c3f0814ec7b5309206de2c60937f383c1765d58bd70581f920df", "tool": "LinkedIn", "notebook": "Send event invitations post engagements", "action": "", "tags": ["#linkedin", "#events", "#invitations", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-07-08", "description": "This notebook allows users to send event invitations and post engagements on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_event_invitations_post_engagements.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_event_invitations_post_engagements.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "naas", "requests", "time"], "image_url": ""}, {"objectID": "8f2f7ab311c3b0058af4aa3dfb216fe0e7f1a9f78d14a2f8bff4661f5f46e89c", "tool": "LinkedIn", "notebook": "Send followers demographic data to a Google Sheets spreadsheet", "action": "", "tags": ["#\"linkedin", "#googlesheets", "#gsheet", "#data", "#naas_drivers", "#demographics", "#content", "#snippet"], "author": "Asif Syed", "author_url": "https://www.linkedin.com/in/asifsyd/", "updated_at": "2023-05-29", "created_at": "2022-07-11", "description": "This notebook allows users to easily export demographic data about their LinkedIn followers to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_followers_demographic_data_to_a_Google_Sheets_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_followers_demographic_data_to_a_Google_Sheets_spreadsheet.ipynb", "imports": ["naas_drivers.gsheet", "naas_drivers.linkedin", "pandas", "numpy", "naas"], "image_url": ""}, {"objectID": "49cfbd24cd629b49f5c61b1411be50d20278f2357b7474b057e6a90ea78e77a1", "tool": "LinkedIn", "notebook": "Send interactions from post URL to HubSpot notes", "action": "", "tags": ["#linkedin", "#hubspot", "#openai", "#interactions", "#post", "#url", "#send", "#notes"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-16", "created_at": "2023-08-16", "description": "This notebook automates the process of sending people interactions (like or comment) on a LinkedIn post URL to a contact notes in HubSpot. If a person doesn't already exist in HubSpot, a new contact is created, complete with their first name, last name, occupation, and LinkedIn URL. We also use a prompt to categorize people by ICP, enriching the HubSpot contact information in the process. This tool proves invaluable for tracking and scoring targets acquired through your LinkedIn post campaigns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_interactions_from_post_URL_to_HubSpot_notes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_interactions_from_post_URL_to_HubSpot_notes.ipynb", "imports": ["naas", "naas_drivers.linkedin, hubspot", "pandas", "openai", "requests", "datetime.datetime, timezone", "difflib.SequenceMatcher"], "image_url": ""}, {"objectID": "b6b084bb3f63093ac35b2d2ddee1537e97e5aa2c5f288f5f1b68baf1871c3eae", "tool": "LinkedIn", "notebook": "Send invitation to company followers", "action": "", "tags": ["#linkedin", "#company", "#followers", "#invitations", "#naas_drivers", "#automation", "#content"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-04-22", "description": "This notebook allows users to send invitations to their company's followers on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_invitation_to_company_followers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_invitation_to_company_followers.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas", "plotly.graph_objects", "os"], "image_url": ""}, {"objectID": "37c5863ae1a3514167b091d00832094a7c8a267ed37a464de412872cb19c50a6", "tool": "LinkedIn", "notebook": "Send invitation to profile", "action": "", "tags": ["#linkedin", "#invitation", "#naas_drivers", "#content", "#snippet", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-18", "description": "This notebook allows users to send invitations to connect on LinkedIn to other profiles.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_invitation_to_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_invitation_to_profile.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "f0fba0385a33845e76e5bcd0c3a61e1c1b6574dcbec369b6f3cc81f4da639439", "tool": "LinkedIn", "notebook": "Send invitation to profile from post likes", "action": "", "tags": ["#linkedin", "#post", "#likes", "#naas_drivers", "#invitation", "#content", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-05-09", "description": "This notebook allows users to send LinkedIn invitations to profiles based on post likes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_invitation_to_profile_from_post_likes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_invitation_to_profile_from_post_likes.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "naas", "time"], "image_url": ""}, {"objectID": "65002d9da74692480adb03f4deaa5afef7d1561f0bbf6953e2d555eeb1e5837a", "tool": "LinkedIn", "notebook": "Send invitations to post commenters", "action": "", "tags": ["#linkedin", "#post", "#comments", "#invitations", "#connections", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Asif Syed", "author_url": "https://www.linkedin.com/in/asifsyd/", "updated_at": "2023-05-29", "created_at": "2022-07-17", "description": "This notebook allows users to quickly and easily send LinkedIn invitations to people who have commented on their posts.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_invitations_to_post_commenters.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_invitations_to_post_commenters.ipynb", "imports": ["naas_drivers.linkedin", "naas", "time"], "image_url": ""}, {"objectID": "e239ff8280fca693ad120ea9ada41a0df5571b5bb06a39f46f94b0e4a287fb1d", "tool": "LinkedIn", "notebook": "Send like to latest company or profile post", "action": "", "tags": ["#linkedin", "#socialmedia", "#like", "#company", "#profile", "#post", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-23", "created_at": "2023-08-23", "description": "This notebook will follow a company or a profile on LinkedIn and send like to its last posts. The post URL will be hashed using SHA and stored in a directory. This ensures that you don't engage with the same post multiple times.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_like_to_latest_company_or_profile_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_like_to_latest_company_or_profile_post.ipynb", "imports": ["naas_drivers.linkedin", "requests", "naas", "os", "hashlib", "hashlib"], "image_url": ""}, {"objectID": "c4a629732584538be3dec3d986b911d0f95f9932bdc32b9021fcc85778d0fc3a", "tool": "LinkedIn", "notebook": "Send like to latest company post", "action": "", "tags": ["#linkedin", "#socialmedia", "#like", "#company", "#post", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-23", "created_at": "2023-08-03", "description": "This notebook will follow a company on LinkedIn and send like to its last posts. The post URL will be hashed using SHA and stored in a directory. This ensures that you don't engage with the same post multiple times.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_like_to_latest_company_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_like_to_latest_company_post.ipynb", "imports": ["naas_drivers.linkedin", "requests", "naas", "os", "hashlib", "hashlib"], "image_url": ""}, {"objectID": "c85a3805e5e3536844c2b044e45753ced940951c9442c984d6704354a006eabb", "tool": "LinkedIn", "notebook": "Send like to latest profile post", "action": "", "tags": ["#linkedin", "#socialmedia", "#like", "#profile", "#post", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-03", "created_at": "2023-08-03", "description": "This notebook will follow a profile on LinkedIn and send like to its last posts. The post URL will be hashed using SHA and stored in a directory. This ensures that you don't engage with the same post multiple times.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_like_to_latest_profile_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_like_to_latest_profile_post.ipynb", "imports": ["naas_drivers.linkedin", "requests", "naas", "os", "hashlib", "hashlib"], "image_url": ""}, {"objectID": "e3eabf565c9cdb8e722c927522ecfe036376ee19a9d9b119f55a9c5440373e7e", "tool": "LinkedIn", "notebook": "Send like to post", "action": "", "tags": ["#linkedin", "#socialmedia", "#like", "#post", "#python", "#api"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-02", "created_at": "2023-08-02", "description": "This notebook will show how to send a like to a post published on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_like_to_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_like_to_post.ipynb", "imports": ["naas_drivers.linkedin", "requests", "naas"], "image_url": ""}, {"objectID": "e94667908de603647180dc81387e1c2bcfd5d0ad5397217632d78647873462cf", "tool": "LinkedIn", "notebook": "Send likes from post to gsheet", "action": "", "tags": ["#linkedin", "#post", "#likes", "#gsheet", "#naas_drivers", "#content", "#snippet", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-17", "description": "This notebook automates the process of sending likes from LinkedIn posts to a Google Sheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_likes_from_post_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_likes_from_post_to_gsheet.ipynb", "imports": ["naas_drivers.linkedin, gsheet", "random", "time", "pandas", "datetime.datetime"], "image_url": ""}, {"objectID": "dd529268f794af9c567c6b89ebda05232650474d2045ffd7ba0800fa866f0e1f", "tool": "LinkedIn", "notebook": "Send message to new connections", "action": "", "tags": ["#linkedin", "#message", "#naas_drivers", "#content", "#snippet", "#text"], "author": "Asif Syed", "author_url": "https://www.linkedin.com/in/www.linkedin.com/in/asifsyd/", "updated_at": "2023-05-29", "created_at": "2022-07-06", "description": "This notebook allows users to quickly and easily send messages to their new LinkedIn connections.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_message_to_new_connections.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_message_to_new_connections.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.date", "naas"], "image_url": ""}, {"objectID": "a3372b8ea91440ad0889bc2f287878a924198874c1e5f00d36a07ebf360a73c2", "tool": "LinkedIn", "notebook": "Send message to profile", "action": "", "tags": ["#linkedin", "#message", "#naas_drivers", "#content", "#snippet", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook allows you to send a message to a LinkedIn profile.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_message_to_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_message_to_profile.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "a6bf8dc89284ce4e8c4233f645ff59cc200717ca056b7bd1e630a1ed463e9561", "tool": "LinkedIn", "notebook": "Send message to profile from post likes", "action": "", "tags": ["#linkedin", "#post", "#likes", "#naas_drivers", "#message", "#content", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-05-09", "description": "This notebook allows users to send messages to LinkedIn profiles from posts they have liked.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_message_to_profile_from_post_likes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_message_to_profile_from_post_likes.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "naas", "time"], "image_url": ""}, {"objectID": "527096707df50d4a343fc763b05e143cd4f346da125d7cd362696fae92628e05", "tool": "LinkedIn", "notebook": "Send posts feed to gsheet", "action": "", "tags": ["#linkedin", "#profile", "#post", "#stats", "#naas_drivers", "#automation", "#content", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-17", "description": "This notebook automates the process of sending LinkedIn posts to a Google Sheet for easy tracking and analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_posts_feed_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_posts_feed_to_gsheet.ipynb", "imports": ["naas_drivers.linkedin, gsheet", "naas", "pandas"], "image_url": ""}, {"objectID": "1d4114e63bdbb69e6e961f9140c1495707caf472877acb48e79061319b7c58c9", "tool": "LinkedIn", "notebook": "Send profile followers by email", "action": "", "tags": ["#linkedin", "#network", "#followers", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-02", "description": "This notebook allows users to send emails to their LinkedIn profile followers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_profile_followers_by_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_profile_followers_by_email.ipynb", "imports": ["naas_drivers.linkedin, emailbuilder", "naas", "pandas", "datetime.datetime"], "image_url": ""}, {"objectID": "c68448105b3374452761515cae1f4839a8efd59d518fca9b53bae22b2ee6c25c", "tool": "LinkedIn", "notebook": "Send weekly post engagement metrics by email", "action": "", "tags": ["#linkedin", "#tool", "#posts", "#engagement", "#metrics", "#analytics", "#automation", "#email", "#naas", "#notification"], "author": "Nikolaj Groeneweg", "author_url": "https://www.linkedin.com/in/njgroene/", "updated_at": "2023-05-29", "created_at": "2022-05-11", "description": "This notebook automates the process of sending weekly post engagement metrics from LinkedIn via email.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_weekly_post_engagement_metrics_by_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_weekly_post_engagement_metrics_by_email.ipynb", "imports": ["naas_drivers.linkedin", "naas", "dateutil.parser.parse", "matplotlib.pyplot", "seaborn", "seaborn", "pandas", "datetime.datetime, date", "random", "time"], "image_url": ""}, {"objectID": "0826bb1d3a9f1983c0684a8cf33240c5bd6edeef1f65bbdfe89a7ced5138ee0c", "tool": "LinkedIn", "notebook": "Update metrics from company posts in Notion content calendar", "action": "", "tags": ["#linkedin", "#profile", "#post", "#feed", "#naas_drivers", "#notion", "#automation", "#analytics", "#naas", "#scheduler", "#content", "#plotly", "#html", "#csv", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-08", "description": "This notebook allows users to track the performance of their company's posts on LinkedIn by updating metrics in Notion's content calendar.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Update_metrics_from_company_posts_in_Notion_content_calendar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Update_metrics_from_company_posts_in_Notion_content_calendar.ipynb", "imports": ["naas", "naas_drivers.linkedin, notion", "datetime.datetime", "pandas", "plotly.express", "os", "requests"], "image_url": ""}, {"objectID": "e79fd40c42943142b09858493a155dd89ea2399f5fb45070b0ab28de29153c52", "tool": "LinkedIn", "notebook": "Update metrics from posts in Notion content calendar", "action": "", "tags": ["#linkedin", "#profile", "#post", "#feed", "#naas_drivers", "#notion", "#automation", "#analytics", "#naas", "#scheduler", "#content", "#plotly", "#html", "#csv", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-22", "description": "This notebook allows users to track the performance of their LinkedIn posts by automatically updating metrics from their Notion content calendar.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Update_metrics_from_posts_in_Notion_content_calendar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Update_metrics_from_posts_in_Notion_content_calendar.ipynb", "imports": ["naas", "naas_drivers.linkedin, notion, emailbuilder", "datetime.datetime", "pandas", "plotly.express", "os", "requests"], "image_url": ""}, {"objectID": "04c698d2af7423916c8813d69fb15a47ac877cb56b2f6a3f81aa8c0ebddb5eda", "tool": "LinkedIn", "notebook": "Withdraw pending profile invitations", "action": "", "tags": ["#linkedin", "#invitation", "#pending", "#naas_drivers", "#content", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-09-22", "description": "This notebook allows users to view and manage pending profile invitations sent through LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Withdraw_pending_profile_invitations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Withdraw_pending_profile_invitations.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "naas", "time", "datetime.datetime", "dateutil.relativedelta.relativedelta", "json", "requests"], "image_url": ""}, {"objectID": "c4aa64628872dabf26a9f58ad9be5a790a83a704cfcd3b791774f949ce8df046", "tool": "Matplotlib", "notebook": "Create Barchart", "action": "", "tags": ["#matplotlib", "#chart", "#barchart", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "", "updated_at": "2023-07-17", "created_at": "2023-07-17", "description": "This notebook provides instructions on how to create a barchart chart using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Barchart.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "087c2b13300d04d4048791c573da3382591f69fdbeeb3db9d872a17a9c293063", "tool": "Matplotlib", "notebook": "Create Horizontal Barchart", "action": "", "tags": ["#matplotlib", "#chart", "#horizontal barchart", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-17", "created_at": "2023-07-17", "description": "This notebook provides instructions on how to create a horizontal Bar chart using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Horizontal_barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Horizontal_barchart.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "b44c24fa0f9c6a8934b98015860672c84babcf90aabd201045cef089cac9e10b", "tool": "Matplotlib", "notebook": "Create Stacked Barchart", "action": "", "tags": ["#matplotlib", "#chart", "#stacked barchart", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-24", "created_at": "2023-07-17", "description": "This notebook provides instructions on how to create a stacked Bar chart using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Stacked_barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Stacked_barchart.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "6c294eadef488f2bffbf61bdc27d1118210c59ff5131678cf5ea3b9ffb8c8db4", "tool": "Matplotlib", "notebook": "Create Stackplots", "action": "", "tags": ["#matplotlib", "#chart", "#stackplots", "#streamgraphs", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to create stackplots using matplotlib. Stackplots draw multiple datasets as vertically stacked areas. This is useful when the individual data values and additionally their cumulative value are of interest.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Stackplot.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Stackplot.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "1f3fc35bee4b3150b9147bddd14a9ddcc1b03b43e06219f599ffbf03c0670508", "tool": "Matplotlib", "notebook": "Create Step Demo", "action": "", "tags": ["#matplotlib", "#chart", "#step demo", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-25", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to plot the coherence of two signals using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Step_Demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Step_Demo.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "9776fa7b943cf273829c127952e6b3fa77670a7f6964394f776398982b55a76e", "tool": "Matplotlib", "notebook": "Create Streamgraphs", "action": "", "tags": ["#matplotlib", "#chart", "#stackplots", "#streamgraphs", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to create using matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Streamgraphs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Streamgraphs.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "5d656a5d27e392c123ffbf464947fa2704905053ca4492c2f5d4c83b4078df64", "tool": "Matplotlib", "notebook": "Create Waterfall chart", "action": "", "tags": ["#matplotlib", "#chart", "#warterfall", "#dataviz", "#snippet", "#operations", "#image"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a Waterfall chart using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Waterfall_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Waterfall_chart.ipynb", "imports": ["numpy", "pandas", "matplotlib.pyplot", "matplotlib.ticker.FuncFormatter"], "image_url": ""}, {"objectID": "d0d75eac84da33d249e5a02389b33b1d1072ec9fa51c3714cc2d1301bce1a15e", "tool": "Matplotlib", "notebook": "Creating a timeline with lines, dates, and text", "action": "", "tags": ["#matplotlib", "#chart", "#timeline", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-25", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to create a simple timeline using Matplotlib release dates.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_timeline%20_with_lines_dates_and_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_timeline%20_with_lines_dates_and_text.ipynb", "imports": ["matplotlib.pyplot", "numpy", "matplotlib.dates", "datetime.datetime", "naas", "urllib.request", "json"], "image_url": ""}, {"objectID": "c32df804be451c266b92c3ad55937b47476ccfc6f07ce09ac434fce8e1c5f0e1", "tool": "Matplotlib", "notebook": "Errorbar Limit Selection", "action": "", "tags": ["#matplotlib", "#chart", "#errorbar", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to create illustrations of selectively drawing lower and/or upper limit symbols on errorbars using the parameters uplims, lolims of errorbar using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Errorbar_limit_selection.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Errorbar_limit_selection.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "ec9d2f3bc763b8c5dab172f1354acd3ef85d13adbcfe201601c7155547bb3429", "tool": "Matplotlib", "notebook": "Mapping marker properties to multivariate data", "action": "", "tags": ["#matplotlib", "#chart", "#stackplots", "#markers", "#dataviz", "#snippet", "#operations", "#image", "#multivariate datasets"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-25", "created_at": "2023-07-24", "description": "This notebook shows how to use different properties of markers to plot multivariate datasets using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Map_marker_properties_to_plot_multivariate_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Map_marker_properties_to_plot_multivariate_data.ipynb", "imports": ["numpy", "matplotlib.pyplot", "matplotlib.markers.MarkerStyle", "matplotlib.transforms.Affine2D", "matplotlib.text.TextPath", "naas"], "image_url": ""}, {"objectID": "42138b50edc125a7228a7a869f6566ffccf68e03ad9a7f48c4c553f3ff2f00e6", "tool": "Matplotlib", "notebook": "Plotting the Coherence of two signals", "action": "", "tags": ["#matplotlib", "#chart", "#coherence", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-25", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to plot the coherence of two signals using Matplotlib", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Plotting_the_coherence_of_two_signals.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Plotting_the_coherence_of_two_signals.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "4a4589dd47268d7b41670305c96da56350a70ae172778a99f62759ae520ca82d", "tool": "Metrics Store", "notebook": "Content creation Track connections", "action": "", "tags": ["#metricsstore", "#metrics", "#content-creation", "#connections", "#content", "#snippet", "#plotly"], "author": "Riddhi Deshpande", "author_url": "https://www.linkedin.com/in/riddhideshpande/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "This notebook allows users to track connections related to content creation for the Metrics Store.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Metrics%20Store/Content_creation_Track_connections.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Metrics%20Store/Content_creation_Track_connections.ipynb", "imports": ["naas_drivers.notion", "naas", "pandas", "plotly.express"], "image_url": ""}, {"objectID": "32ed25173bd9f466a47c983ffa60c2443f32dfa1abefdb12445840b50f37a01f", "tool": "Microsoft Teams", "notebook": "Send message", "action": "", "tags": ["#microsoftteams", "#snippet", "#operations"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows users to send messages through Microsoft Teams.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Microsoft%20Teams/Microsoft_Teams_Send_message.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Microsoft%20Teams/Microsoft_Teams_Send_message.ipynb", "imports": ["naas_drivers.teams"], "image_url": ""}, {"objectID": "b4452f1b67f4490a67006104ca10458588e76c3188b5d0da2519c9a7d24fcf43", "tool": "Microsoft Word", "notebook": "Convert to HMTL", "action": "", "tags": ["#microsoftword", "#word", "#microsoft", "#html", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows users to convert Microsoft Word documents into HTML format.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Microsoft%20Word/Microsoft_Word_Convert_to_HMTL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Microsoft%20Word/Microsoft_Word_Convert_to_HMTL.ipynb", "imports": ["mammoth", "mammoth"], "image_url": ""}, {"objectID": "a53f5b5e6b059ad365cf319b58a4a0d99fd1f954bd7c82bb61bdd9d42b9beebc", "tool": "Mixpanel", "notebook": "Get Profile Event Activity", "action": "", "tags": ["#mixpanel", "#activity", "#stream", "#query", "#api", "#reference"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-06", "created_at": "2023-07-06", "description": "This notebook returns the activity feed for specified users. It is usefull for organizations to track user activity and get insights from it.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Mixpanel/Mixpanel_Get_Profile_Event_Activity.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Mixpanel/Mixpanel_Get_Profile_Event_Activity.ipynb", "imports": ["requests", "json", "naas"], "image_url": ""}, {"objectID": "4252489d2efa2ce3fd0f5a3307c6b97db4ab6744a01716b56f718411ccb7d4a1", "tool": "MongoDB", "notebook": "Get data", "action": "", "tags": ["#mongodb", "#database", "#naas_drivers", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook provides instructions on how to retrieve data from a MongoDB database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/MongoDB/MongoDB_Get_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/MongoDB/MongoDB_Get_data.ipynb", "imports": ["naas_drivers.mongo"], "image_url": ""}, {"objectID": "ec3994d9054fd4ae36571978044ce3caca24fc1912451bb7a8d872dada0831fc", "tool": "MongoDB", "notebook": "Send data", "action": "", "tags": ["#mongodb", "#database", "#naas_drivers", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook provides instructions on how to send data to a MongoDB database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/MongoDB/MongoDB_Send_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/MongoDB/MongoDB_Send_data.ipynb", "imports": ["naas_drivers.mongo", "pandas"], "image_url": ""}, {"objectID": "d7646a98514c3189281b5bfe97b6c5c639807d7eb9b6d6c1367b0c0934d5d540", "tool": "MongoDB", "notebook": "Send data to Google Sheets", "action": "", "tags": ["#mongodb", "#googlesheets", "#nosql", "#operations", "#automation"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-04-12", "created_at": "2022-03-21", "description": "This notebook will help you send data from your MongoDB database collection to your spreadsheet", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/MongoDB/MongoDB_Send_data_to_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/MongoDB/MongoDB_Send_data_to_Google_Sheets.ipynb", "imports": ["naas_drivers.mongo, gsheet", "pandas", "naas"], "image_url": ""}, {"objectID": "47c0e6657c573a3ff0e9d41a364f948a355dee01276d4dca70e25b179bb648a1", "tool": "MoviePy", "notebook": "Convert audio file M4A to MP3", "action": "", "tags": ["#moviepy", "#audio", "#convert", "#m4a", "#mp3", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-23", "created_at": "2023-07-23", "description": "This notebook would allow you to transform an audio file from M4A to MP3. It can be further used by people who want to use their Iphone voice recording m\u00e9mos file and generate transcripts with AI.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/MoviePy/MoviePy_Convert_audio_file_M4A_to_MP3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/MoviePy/MoviePy_Convert_audio_file_M4A_to_MP3.ipynb", "imports": ["moviepy.editor.AudioFileClip", "moviepy.editor.AudioFileClip", "requests"], "image_url": ""}, {"objectID": "b8efa6e10ef17925c883986434e62e36da03dc7dd1c07b6660016b7ece44f8ba", "tool": "MySQL", "notebook": "Query database", "action": "", "tags": ["#mysql", "#database", "#snippet", "#operations", "#naas"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides an introduction to querying a MySQL database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/MySQL/MySQL_Query_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/MySQL/MySQL_Query_database.ipynb", "imports": ["os", "pymysql", "pandas"], "image_url": ""}, {"objectID": "334f731f131404dea142a3cf7464a96763daa3cd3b8ce4e28e96a6796f25824c", "tool": "NASA", "notebook": "Artic sea ice", "action": "", "tags": ["#nasa", "#naas", "#opendata", "#analytics", "#asset", "#html", "#png", "#operations", "#image", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-05-10", "description": "AVERAGE SEPTEMBER MINIMUM EXTENT
\nData source: Satellite observations. Credit: NSIDC/NASA\n\n**What is Arctic sea ice extent?**
\nSea ice extent is a measure of the surface area of the ocean covered by sea ice. Increases in air and ocean temperatures decrease sea ice extent; in turn, the resulting darker ocean surface absorbs more solar radiation and increases Arctic warming.
\nDate Range: 1979 - 2020.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/NASA/NASA_Artic_sea_ice.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/NASA/NASA_Artic_sea_ice.ipynb", "imports": ["pandas", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "8c8fa4d995ff61138dd01ab17c04bb8001b05cbb2aeb5f0eaab6a5c27c9ed6f4", "tool": "NASA", "notebook": "Display Exoplanet by Light Curves", "action": "", "tags": ["#nasa", "#naas", "#opendata", "#analytics", "#astronomy", "#html", "#png", "#operations", "#image", "#pylab"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-31", "created_at": "2023-07-05", "description": "This notebook is display Exoplanet by light curves. An exoplanet is any planet beyond our solar system. Most orbit other stars, but free-floating exoplanets, called rogue planets, orbit the galactic center and are untethered to any star.
", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/NASA/NASA_Classify_Exoplanet_by_light_curves.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/NASA/NASA_Classify_Exoplanet_by_light_curves.ipynb", "imports": ["pandas", "numpy", "naas"], "image_url": ""}, {"objectID": "1fcde93a2f4eb30a04bb469261370e4772541277ba8e30b726593dd5939d11f6", "tool": "NASA", "notebook": "Global temperature", "action": "", "tags": ["#nasa", "#opendata", "#analytics", "#plotly"], "author": "Colyn TIDMAN", "author_url": "https://www.linkedin.com/in/dylan-pichon/", "updated_at": "2023-04-12", "created_at": "2021-05-28", "description": "This graph illustrates the change in global surface temperature relative to 1951-1980 average temperatures. Nineteen of the warmest years have occurred since 2000, with the exception of 1998. The year 2020 tied with 2016 for the warmest year on record since record-keeping began in 1880 (source: NASA/GISS). This research is broadly consistent with similar constructions prepared by the Climatic Research Unit and the National Oceanic and Atmospheric Administration.\n\nThe time series below shows the five-year average variation of global surface temperatures. Dark blue indicates areas cooler than average. Dark red indicates areas warmer than average.\n\nThe \u201cGlobal Temperature\u201d figure on the home page dashboard shows global temperature change since 1880. One gets this number by subtracting the first data point in the chart from the latest data point.\n\nWebsite : https://climate.nasa.gov/vital-signs/global-temperature/", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/NASA/NASA_Global_temperature.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/NASA/NASA_Global_temperature.ipynb", "imports": ["pandas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "32201bf648e273b41b194575397810ecfb97f21cd37d9d8446341a12f96d0751", "tool": "NASA", "notebook": "Sea level", "action": "", "tags": ["#nasa", "#naas", "#opendata", "#analytics", "#plotly"], "author": "Colyn TIDMAN", "author_url": "https://www.linkedin.com/in/dylan-pichon/", "updated_at": "2023-04-12", "created_at": "2021-05-28", "description": "Sea level rise is caused primarily by two factors related to global warming: the added water from melting ice sheets and glaciers and the expansion of seawater as it warms. The first graph tracks the change in sea level since 1993 as observed by satellites.\n\nThe second graph, derived from coastal tide gauge and satellite data, shows how much sea level changed from about 1900 to 2018. Items with pluses (+) are factors that cause global mean sea level to increase, while minuses (-) are variables that cause sea levels to decrease. These items are displayed at the time they were affecting sea level.\n\nThe data shown are the latest available, with a four- to five-month lag needed for processing.\n\n* You now need to create an Earthdata account to access NASA's sea level data. Register for free by clicking on 'Get data : http'. Once logged in you will access the data.\n\nWebsite : https://climate.nasa.gov/vital-signs/sea-level/", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/NASA/NASA_Sea_level.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/NASA/NASA_Sea_level.ipynb", "imports": ["pandas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "397ec80a5d605618ddb1c746bd5ae1cf2a9cde80101da5a4d1f3b50caf56dd22", "tool": "Naas Auth", "notebook": "Bearer validate", "action": "", "tags": ["#naasauth", "#naas", "#auth", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-01-20", "description": "This notebook provides a way to validate Bearer tokens for authentication with the Naas API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Auth/Naas_Auth_bearer_validate.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Auth/Naas_Auth_bearer_validate.ipynb", "imports": ["naas_drivers.naasauth"], "image_url": ""}, {"objectID": "707ec48e296bbb6f5fcc8033d750087e362ad452a041e95f21c6d735dedfc4c8", "tool": "Naas Auth", "notebook": "Connect", "action": "", "tags": ["#naasauth", "#naas", "#auth", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-01-20", "description": "Naas Auth - Connect is a notebook that allows users to securely authenticate and connect to their Naas account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Auth/Naas_Auth_connect.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Auth/Naas_Auth_connect.ipynb", "imports": ["naas_drivers.naasauth"], "image_url": ""}, {"objectID": "a20de7e2d83d0f89de859559f5cf13c396e48b548762365f135ee5b9711a408f", "tool": "Naas Auth", "notebook": "Users me", "action": "", "tags": ["#naasauth", "#naas", "#auth", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-01-20", "description": "This notebook provides a user-friendly interface for authenticating users with Naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Auth/Naas_Auth_users_me.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Auth/Naas_Auth_users_me.ipynb", "imports": ["naas_drivers.naasauth"], "image_url": ""}, {"objectID": "0868c0a991f66c0a07b9d6f8f005dd86de34a21d6f03a692962537e3cd119dde", "tool": "Naas Dashboard", "notebook": "Financial Consolidation", "action": "", "tags": ["#naasdashboard", "#plotly", "#dash", "#naas", "#asset", "#automation", "#analytics", "#snippet", "#datavizualisation"], "author": "Meriem Si", "author_url": "https://www.linkedin.com/in/meriem-si-104236181/", "updated_at": "2023-04-12", "created_at": "2022-09-12", "description": "This notebook provides a comprehensive dashboard for financial consolidation and analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Dashboard/Naas_Dashboard_Financial_Consolidation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Dashboard/Naas_Dashboard_Financial_Consolidation.ipynb", "imports": ["dash", "dash", "dash.html, dcc, Input, Output, State", "dash_bootstrap_components", "dash_bootstrap_components", "plotly.graph_objects", "plotly.express", "os", "pandas", "naas_drivers.gsheet", "dash_bootstrap_components._components.Container.Container", "plotly.subplots.make_subplots"], "image_url": ""}, {"objectID": "b914e946e624466c61e2bc0891564eedd3c6d8fc5f59c62e5caaff62e612e88b", "tool": "Naas Dashboard", "notebook": "Revenue Cogs by Segment", "action": "", "tags": ["#naasdashboard", "#plotly", "#dash", "#naas", "#asset", "#automation", "#analytics", "#snippet", "#datavizualisation"], "author": "Fernando Chavez Osuna", "author_url": "https://www.linkedin.com/in/fernando-chavez-osuna-1a420a181", "updated_at": "2023-04-12", "created_at": "2022-09-22", "description": "This notebook provides an analysis of revenue cogs by segment for the Naas Dashboard.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Dashboard/Naas_Dashboard_Revenue_Cogs_by_Segment.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Dashboard/Naas_Dashboard_Revenue_Cogs_by_Segment.ipynb", "imports": ["dash", "dash", "dash.html, dcc, Input, Output, State", "dash_bootstrap_components", "dash_bootstrap_components", "plotly.graph_objects", "plotly.express", "os", "naas_drivers", "naas_drivers.gsheet", "dash_bootstrap_components._components.Container.Container", "pandas"], "image_url": ""}, {"objectID": "16c5518def67a82a87c39ce69fd9ab6a967b9e509c063c8e6541f593ed677b01", "tool": "Naas Dashboard", "notebook": "Social Media KPIs ScoreCard", "action": "", "tags": ["#naasdashboard", "#plotly", "#dash", "#naas", "#asset", "#automation", "#analytics", "#snippet", "#datavizualisation"], "author": "Ismail CHIHAB", "author_url": "https://www.linkedin.com/in/ismail-chihab-4b0a04202/", "updated_at": "2023-04-12", "created_at": "2022-09-12", "description": "This notebook provides a comprehensive scorecard of key performance indicators for social media platforms.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Dashboard/Naas_Dashboard_Social_Media_KPIs_ScoreCard.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Dashboard/Naas_Dashboard_Social_Media_KPIs_ScoreCard.ipynb", "imports": ["dash", "dash", "dash.html, dcc, Input, Output, State", "dash_bootstrap_components", "dash_bootstrap_components", "naas", "naas_drivers.gsheet", "dash.html, dash_table", "dash.dependencies.Input, Output, State", "dash.dcc", "pandas", "os"], "image_url": ""}, {"objectID": "49f156224d2f4ba86dc03cb514690634f99d651dd4c8f390d9471bd33666c42e", "tool": "Naas", "notebook": "Add or Update Asset", "action": "", "tags": ["#naas", "#asset", "#snipet", "#operations", "#add", "#update"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to copy in production a file as an asset and allow yourself to get it by calling the returned URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Add_or_Update_Asset.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Add_or_Update_Asset.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "a8e532c51f125b4b806b25baaa49c531492178fb58f0a6f823bf8b33833fab72", "tool": "Naas", "notebook": "Add or Update Dependency", "action": "", "tags": ["#naas", "#dependency", "#add", "#update", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to add or update a dependency in Naas. The naas dependency feature push files (script, csv) into production environment.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Add_or_Update_Dependency.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Add_or_Update_Dependency.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "6324a3458ed02970a57df320b23fe3db9e2b49b779c42a0851a2b64b47ad0948", "tool": "Naas", "notebook": "Add or Update Scheduler", "action": "", "tags": ["#naas", "#scheduler", "#snippet", "#operations", "#add", "#update"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to automate a notebook using the scheduler feature of Naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Add_or_Update_Scheduler.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Add_or_Update_Scheduler.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "9881af429a735a74f8b198299ac81dd7aa1a9f1499269d69dc4673560f47dc67", "tool": "Naas", "notebook": "Add or Update Secret", "action": "", "tags": ["#naas", "#secret", "#add", "#update", "#operation", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to add or uppdate a secret to Naas.\n\nSecrets are an important part of Naas, when you need to interact with other services, you need secret, like any other variable the temptation is big to put it straight in your notebook, but this lead to a big security breach since we replicate a lot the notebook, in the versioning system, the output and your ability to share it or send it to git! \nUse this simple feature instead to have global secure storage share with your sandbox and production.\nSecrets are local to your machine and encoded, that a big layer of security with a little effort.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Add_or_Update_Secret.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Add_or_Update_Secret.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "abd7d33c33240f853371346227a2ae5b2c4b78bec62d783f4ce06e07af02da6f", "tool": "Naas", "notebook": "Add or Update Webhook", "action": "", "tags": ["#naas", "#webhook", "#add", "#update", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to add or update a webhook in production using Naas feature. The notebook will be sent to production and you will get an URL that can be triggered.\n\nWebhooks are useful because they enable real-time communication between applications, allowing for automated notifications or data exchange when specific events occur. This eliminates the need for constant polling and manual data retrieval, making webhooks efficient and scalable for various use cases.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Add_or_Update_Webhook.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Add_or_Update_Webhook.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "a4c7e1cb7a80573d8aeee8b70bd4bb3aa1a2e3ebc220423757dc6330ac876253", "tool": "Naas", "notebook": "Asset demo", "action": "", "tags": ["#naas", "#asset", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-31", "description": "Read the doc on https://naas.gitbook.io/naas/features/asset", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Asset_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Asset_demo.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "7e51dbae8cf766d7bbe70b8e5d811776b60173220ab6eccc75086cf2480daed3", "tool": "Naas", "notebook": "Automate GitHub Auth", "action": "", "tags": ["#naas", "#asset", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-28", "description": "This notebook provides an automated way to authenticate with GitHub using Naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Automate_GitHub_Auth.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Automate_GitHub_Auth.ipynb", "imports": [], "image_url": ""}, {"objectID": "42ed86f1ce38ee92bc5c86740032d85a786e7c249673b9895f0ff3e6c5ee3944", "tool": "Naas", "notebook": "Configure Github with ssh", "action": "", "tags": ["#naas", "#git", "#github", "#jupyterlab", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-04-07", "description": "This notebook provides instructions on how to configure Github with SSH for secure access to the Naas platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Configure_Github_with_ssh.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Configure_Github_with_ssh.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "55207a267c659be8a52dab480828d899bcb20c49f124060ea6c4a6f1d890531c", "tool": "Naas", "notebook": "Create Kernel", "action": "", "tags": ["#naas", "#ipython", "#conda", "#kernel"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-01-11", "description": "This Jupyter Notebook will enable you to establish a new IPython Kernel that you can customize, allowing you to install any desired tools. This kernel, once created, can be selected to run your notebooks and can be used even in a production environment.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Create_Kernel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Create_Kernel.ipynb", "imports": [], "image_url": ""}, {"objectID": "92ddbcf7c74813cc4c906ca6b7d04cc2590230b5fb16082b396de5b9872be0cf", "tool": "Naas", "notebook": "Create Pipeline", "action": "", "tags": ["#naas", "#pipeline", "#jupyter", "#notebook", "#dataanalysis", "#workflow", "#streamline"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-01-20", "description": "This notebook is a guide that teaches you how to create a notebook pipeline using naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Create_Pipeline.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Create_Pipeline.ipynb", "imports": ["naas.pipeline.pipeline.("], "image_url": ""}, {"objectID": "a1b3a685ea98ec4477699d6993219645300070c5f79b8b8cdbedb74c82fc9f9d", "tool": "Naas", "notebook": "Create onboarding plugin using OpenAI", "action": " ", "tags": ["#onboarding", "#naas", "#openai", "#personas", "#ai", "#machinelearning", "#deeplearning", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-14", "description": "This notebook will create a onboarding plugin into Naas-MyChatGPT app using OpenAI.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Create_onboarding_plugin_using_OpenAI.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Create_onboarding_plugin_using_OpenAI.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Create_onboarding_plugin_using_OpenAI.ipynb", "imports": ["json", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "b8e8498be8e2a6e4ed47256dd6b987fc934f372db1ce9b0ba198bd19514296ca", "tool": "Naas", "notebook": "Credits Get Balance", "action": "", "tags": ["#naas", "#credits", "#snippet", "#operations"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-11-17", "description": "This notebook provides a way to view the balance of credits available for use in the Naas platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Credits_Get_Balance.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Credits_Get_Balance.ipynb", "imports": ["naas_drivers.naascredits"], "image_url": ""}, {"objectID": "faebd17e0e224ea21a9214be8a9831d2b94a5f912ab27836676b26589d608f3f", "tool": "Naas", "notebook": "Delete Asset", "action": "", "tags": ["#naas", "#asset", "#snipet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-16", "created_at": "2023-03-21", "description": "This notebook will show how to delete an asset from naas production environment.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_Asset.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_Asset.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "54d4fe233930b6fe96be9c4df3daf94f17ad0a3785c88dc9818b6c126173609f", "tool": "Naas", "notebook": "Delete Dependency", "action": "", "tags": ["#naas", "#dependency", "#snipet", "#operations", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to delete a dependency from naas production environment.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_Dependency.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_Dependency.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "e5801f9ba44fba35f2b6845fb88f7e660692550236c17ba3b6189300fdbd905b", "tool": "Naas", "notebook": "Delete Scheduler", "action": "", "tags": ["#naas", "#scheduler", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-16", "created_at": "2023-03-15", "description": "This notebook will show how to delete a naas scheduler.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_Scheduler.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_Scheduler.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "13f4b5a9bef18a2771e6e56c4ecd486c68e6b83c5b8be85e302ec59fcb4fc4ad", "tool": "Naas", "notebook": "Delete Secret", "action": "", "tags": ["#naas", "#secret", "#delete", "#api", "#python", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-27", "created_at": "2023-04-27", "description": "This notebook will show how to delete a secret in Naas.\n\nSecrets are an important part of Naas, when you need to interact with other services, you need secret, like any other variable the temptation is big to put it straight in your notebook, but this lead to a big security breach since we replicate a lot the notebook, in the versioning system, the output and your ability to share it or send it to git! \nUse this simple feature instead to have global secure storage share with your sandbox and production.\nSecrets are local to your machine and encoded, that a big layer of security with a little effort.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_Secret.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_Secret.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "27ea4180c03a08d23d80e1786c1b59542fa459be8170a2aac537979178d4bdfc", "tool": "Naas", "notebook": "Delete Webhook", "action": "", "tags": ["#naas", "#scheduler", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-24", "description": "This notebook will show how to delete a naas webhook.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_Webhook.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_Webhook.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "ad17062d674c08958e8d52d2c391a621c91ce8ce90e01be930c7fec90dc78a84", "tool": "Naas", "notebook": "Delete all assets", "action": "", "tags": ["#naas", "#assets", "#delete", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-16", "created_at": "2023-08-16", "description": "This notebook deletes all assets in Naas Lab.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_all_assets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_all_assets.ipynb", "imports": ["naas", "os"], "image_url": ""}, {"objectID": "8c929e981ea24e0ea05c39e9bb399e341431ef3b5c9533df80b4292b78269a2f", "tool": "Naas", "notebook": "Delete all schedulers", "action": "", "tags": ["#naas", "#scheduler", "#delete", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-16", "created_at": "2023-08-16", "description": "This notebook deletes all schedulers in Naas Lab.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_all_schedulers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_all_schedulers.ipynb", "imports": ["naas", "os"], "image_url": ""}, {"objectID": "2b6603209c8adc27d4663ce554cdc239d6eca437c4cbdd0a30923eeca573b888", "tool": "Naas", "notebook": "Dependency demo", "action": "", "tags": ["#naas", "#dependency", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook demonstrates how to use Naas to manage dependencies in a project.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Dependency_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Dependency_demo.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "19034fbe5e15fb13de9738e02f6a5292dd1fcd6cac4aed92315fee5c458c3f95", "tool": "Naas", "notebook": "Doc demo", "action": "", "tags": ["#naas", "#doc", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook provides a demonstration of how to use the Naas Docs API to create, update, and delete documents.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Doc_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Doc_demo.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "1f6c374e05c5935ce272c9d5dc0ae45735b9d21beb8ca9f23fef22cd9a190ff7", "tool": "Naas", "notebook": "Download Content Engine", "action": "", "tags": ["#naas", "#automation", "#linkedin", "#youtube", "#twitter", "#snapchat", "#instagram", "#facebook", "#tiktok", "#dataproduct"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-02", "description": "Naas is a content engine that enables users to easily download and manage digital content.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Download_Content_Engine.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Download_Content_Engine.ipynb", "imports": ["IPython.display.display", "ipywidgets.widgets", "naas", "os.path"], "image_url": ""}, {"objectID": "e74b8806f7d7fbcafe79c6713182bc3c7d29e00f8f2e299adb90b2388baadad0", "tool": "Naas", "notebook": "Emailbuilder demo", "action": "", "tags": ["#naas", "#emailbuilder", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-05-28", "description": "This notebook provides a demonstration of the Naas Emailbuilder, a tool for creating and managing email campaigns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Emailbuilder_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Emailbuilder_demo.ipynb", "imports": ["naas_drivers", "naas", "pandas"], "image_url": ""}, {"objectID": "1149e5c1a3d183a41ab530f754117157d2f86e1719516b99e4a263256a582065", "tool": "Naas", "notebook": "Find Asset link from path", "action": "", "tags": ["#naas", "#asset", "#path", "#link", "#find", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-04", "created_at": "2023-05-04", "description": "This notebook will help you find the asset link generated with naas from a given file path.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Find_Asset_link_from_path.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Find_Asset_link_from_path.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "5df9412ae66fd7ab475df0c83cd5f8a2f36ca695bb4292dd5433aded3dc2e890", "tool": "Naas", "notebook": "Get Transactions", "action": "", "tags": ["#naas", "#credits", "#snippet", "#operations"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-11-17", "description": "This notebook provides an easy way to access and analyze transaction data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Get_Transactions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Get_Transactions.ipynb", "imports": ["naas_drivers.naascredits", "pandas"], "image_url": ""}, {"objectID": "ff3a18474c57d0d2d83b9948b2019155f36de2170d1269c715e4bbee2be82c30", "tool": "Naas", "notebook": "Get help", "action": "", "tags": ["#naas", "#help", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook provides helpful resources and guidance for navigating the Naas platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Get_help.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Get_help.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "bafc9570d7378763e028d2cc37280a8b0358f2e1e876500ea2b2f26622c6fed4", "tool": "Naas", "notebook": "Get number of downloads naas drivers package", "action": "", "tags": ["#pypi", "#downloads", "#package", "#operations", "#analytics", "#plotly", "#html", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-27", "description": "This notebook provides a way to get the number of downloads for the Naas drivers package.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Get_number_of_downloads_naas_drivers_package.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Get_number_of_downloads_naas_drivers_package.ipynb", "imports": ["pypistats", "pypistats", "pprint.pprint", "datetime.datetime", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "a3c80e86afed6d77dcb6463c1a64986dd6506f0b0e67063d62ece0219df17ea7", "tool": "Naas", "notebook": "Get number of downloads naas package", "action": "", "tags": ["#pypi", "#downloads", "#package", "#operations", "#analytics", "#plotly", "#html", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-27", "description": "This notebook provides a way to track the number of downloads of the Naas package.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Get_number_of_downloads_naas_package.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Get_number_of_downloads_naas_package.ipynb", "imports": ["pypistats", "pypistats", "pprint.pprint", "datetime.datetime", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "cdc37edf1d19e1738a9b7d3ba99776a599632e661bce3cb24a35e684bf673089", "tool": "Naas", "notebook": "Get total downloads naas libraries", "action": "", "tags": ["#pypi", "#downloads", "#package", "#operations", "#analytics", "#plotly", "#html", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-27", "description": "This notebook provides a way to track the total number of downloads for Naas libraries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Get_total_downloads_naas_libraries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Get_total_downloads_naas_libraries.ipynb", "imports": ["pypistats", "pypistats", "pprint.pprint", "datetime.datetime", "plotly.graph_objects", "naas", "pandas"], "image_url": ""}, {"objectID": "0f98f0161ed02bf496879b2648647afefc830264ade798125d0bc1025eb23164", "tool": "Naas", "notebook": "List Assets", "action": "", "tags": ["#naas", "#asset", "#snipet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-21", "description": "This notebook will show how to list current assets in production.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Assets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Assets.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "d140789cfd7892de0efe6e8a0bc0dfe7f63e1bcca0670e3125f08ec0e453ff9e", "tool": "Naas", "notebook": "List Dependencies", "action": "", "tags": ["#naas", "#dependency", "#snipet", "#operations", "#list"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to list current dependencies in production.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Dependencies.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Dependencies.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "6739d81dea060c5e005aa5b45c062c5babcfc372f44b53065a79051c0caa932d", "tool": "Naas", "notebook": "List Schedulers", "action": "", "tags": ["#naas", "#schedulers", "#list", "#production", "#tool", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-01", "created_at": "2023-06-01", "description": "This notebook will show how to list current schedulers running in production.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Schedulers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Schedulers.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "7cf4e74bd33a75a559cc1e22ecc9bb70366bde9d0c458855d41f445cb1b8f8a4", "tool": "Naas", "notebook": "List Schedulers with all executions", "action": "", "tags": ["#naas", "#schedulers", "#list", "#production", "#tool", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-01", "created_at": "2023-06-01", "description": "This notebook will show how to list current schedulers running in production with all their executions meta data and return a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Schedulers_with_all_executions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Schedulers_with_all_executions.ipynb", "imports": ["naas", "pandas"], "image_url": ""}, {"objectID": "6e0e66eeeef53f91e97285ff107f1c3101bfa1142186dec4122d51dfda1e01e2", "tool": "Naas", "notebook": "List Schedulers with last execution", "action": "", "tags": ["#naas", "#schedulers", "#list", "#production", "#tool", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-01", "created_at": "2023-06-01", "description": "This notebook will show how to list current schedulers running in production with their last execution meta data and return a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Schedulers_with_last_execution.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Schedulers_with_last_execution.ipynb", "imports": ["naas", "pandas"], "image_url": ""}, {"objectID": "ce518a817ab35c537e18a42c72d3e128ed9c8631f2a01ae33c7371e9e2191c13", "tool": "Naas", "notebook": "List Secrets", "action": "", "tags": ["#naas", "#secret", "#list", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-27", "created_at": "2023-04-27", "description": "This notebook will show how to list of your secrets stored in Naas.\nA dataframe with the following column will be retunred:\n- \"id\"\n- \"lastUpdate\"\n- \"name\"\n- \"secret\"", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Secrets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Secrets.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "745b5079821ad22ad9dffd2bb51faa5e200ff047045a7ce416742854c85e0508", "tool": "Naas", "notebook": "List Webhooks", "action": "", "tags": ["#naas", "#asset", "#snipet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-24", "created_at": "2023-04-24", "description": "**References:**\n- [Naas Documentation](https://docs.naas.ai/)\n- [Naas Webhook Documentation](https://docs.naas.ai/features/api)", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Webhooks.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Webhooks.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "1f256fb50ad384b7ca469fca4ec3af4d9e67a7d37dee4022ea3e74246dfc01aa", "tool": "Naas", "notebook": "Manage Pipeline Errors", "action": "", "tags": ["#naas", "#pipeline", "#jupyter", "#notebook", "#dataanalysis", "#workflow", "#streamline"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-01-25", "description": "This notebook is a guide that teaches you how to manage errors on your notebook pipeline using naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Manage_Pipeline_Errors.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Manage_Pipeline_Errors.ipynb", "imports": ["naas.pipeline.pipeline.("], "image_url": ""}, {"objectID": "e26291e9d6bfb6a7d09e27a665447ed0ea75c57dde69de0957353a0ba7e6ad0c", "tool": "Naas", "notebook": "NLP Examples", "action": "", "tags": ["#naas", "#nlp", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-16", "description": "This notebook provides examples of Natural Language Processing (NLP) using the Naas framework.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_NLP_Examples.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_NLP_Examples.ipynb", "imports": ["naas_drivers.nlp", "ant thing in your life right now?\""], "image_url": ""}, {"objectID": "0262344937e5af7b41831767036ab89858af4db92075018b0924478c1fa68804", "tool": "Naas", "notebook": "Notification demo", "action": "", "tags": ["#naas", "#notification", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-31", "description": "This notebook demonstrates how to use Naas to send notifications.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Notification_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Notification_demo.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "e60642c7688856536bd0f8d94b21ef04b589583f51b99100ca685605f1a977b5", "tool": "Naas", "notebook": "Remove Pipeline Executions Outputs", "action": "", "tags": ["#naas", "#scheduler", "#automation", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2023-01-24", "description": "This notebook removes your production pipeline executions outputs automatically.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Remove_Pipeline_Executions_Outputs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Remove_Pipeline_Executions_Outputs.ipynb", "imports": ["glob", "os", "naas", "datetime.datetime", "dateutil.relativedelta.relativedelta", "shutil"], "image_url": ""}, {"objectID": "9ee266e99f40eace87c3aecf7828455a65b7bc2218e3c1420619d6f48d959a85", "tool": "Naas", "notebook": "Remove Scheduler Outputs", "action": "", "tags": ["#naas", "#scheduler", "#automation", "#operations"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-03-14", "description": "This notebook allows users to remove scheduler outputs from the Naas platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Remove_Scheduler_Outputs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Remove_Scheduler_Outputs.ipynb", "imports": ["glob", "os", "naas"], "image_url": ""}, {"objectID": "7a441dc7940c8af0eef50ca209a5b3ed87153419adf5048a7845589a86a0b2e7", "tool": "Naas", "notebook": "Reset Instance", "action": "", "tags": ["#naas", "#scheduler", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-03-14", "description": "This notebook provides a way to reset an instance of Naas, allowing users to start fresh with a clean slate.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Reset_Instance.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Reset_Instance.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "cc6f6c0bb7460dec3abd5121eacdcd5761d972c7525d7ee9ff630df5c532f576", "tool": "Naas", "notebook": "Scheduler demo", "action": "", "tags": ["#naas", "#scheduler", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-06-28", "description": "Transform all your work routines in notebooks and run them even when you sleep.
\nHere we are going to use the Notifications feature to test Scheduler.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Scheduler_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Scheduler_demo.ipynb", "imports": ["IPython.display.IFrame", "naas", "IPython.display.HTML"], "image_url": ""}, {"objectID": "73ad193419ed4c56bb0430e8bd15af0b0c998e973b50790e89b450e08cfc49ca", "tool": "Naas", "notebook": "Secret demo", "action": "", "tags": ["#naas", "#secret", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-31", "description": "Read the doc: https://naas.gitbook.io/naas/features/secret", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Secret_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Secret_demo.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "ebdd845a8c40505f123a9e8cbe5afdd1d1acbef753489ec61a74b133e7973c53", "tool": "Naas", "notebook": "Send Asset image to Notion page", "action": "", "tags": ["#naas", "#notion", "#image", "#asset", "#send", "#vizualise"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook sends an naas image asset to a Notion page. It could be usefull to push chart created in plotly to Notion. If your page is in a notion database, you will be able to vizualise the chart in Gallery (display page content). The image asset will be updated (deleted and added) to make sure the graph display is always up to date in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Send_Asset_image_to_Notion_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Send_Asset_image_to_Notion_page.ipynb", "imports": ["naas_drivers.notion", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "551be4f36d8e50ce4395892079f25ea4f86bc3f5057eb9c3b85f5664ed741aef", "tool": "Naas", "notebook": "Send notifications from Google Sheets", "action": "", "tags": ["#naas", "#productivity", "#gsheet", "#naas_drivers", "#operations", "#snippet", "#email"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows users to send emails from a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Send_notifications_from_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Send_notifications_from_Google_Sheets.ipynb", "imports": ["naas_drivers", "naas_drivers.gsheet, emailbuilder, naasauth", "naas"], "image_url": ""}, {"objectID": "a6491850e181fce4c10f4673acf7b7a3ba172aa9246dca51b7408803e66ee3dd", "tool": "Naas", "notebook": "Set timezone", "action": "", "tags": ["#naas", "#timezone", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook allows users to set the timezone for their Naas instance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Set_timezone.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Set_timezone.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "17a6818193a07da83c5d6e09deb7bc618424cfbb53e9405b8661bceabcdadd91", "tool": "Naas", "notebook": "Start data product", "action": "", "tags": ["#naas", "#dataproduct", "#automation"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-04-11", "description": "In this notebook, we'll walk you through the process of starting a data product using the Naas data product framework and integrating awesome-notebooks into your project. \n\nPlease note that this notebook can only be used while connected to your Naas account. If you'd like to perform these steps locally, please don't hesitate to contact us \u2013 we're more than happy to assist you.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Start_data_product.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Start_data_product.ipynb", "imports": ["urllib.request", "zipfile", "glob", "os", "shutil", "pandas", "re"], "image_url": ""}, {"objectID": "d9094479c5bfd3f36bf674ca012c3b174702051ba15319d9bd9213fd3454fd9f", "tool": "Naas", "notebook": "Use SSH tunnel to reach network protected resources", "action": "", "tags": ["#naas", "#ssh", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-06-01", "description": "This notebook provides instructions on how to use an SSH tunnel to securely access resources on a network that is otherwise protected.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Use_SSH_tunnel_to_reach_network_protected_resources.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Use_SSH_tunnel_to_reach_network_protected_resources.ipynb", "imports": ["sshtunnel", "sshtunnel", "psycopg2", "psycopg2"], "image_url": ""}, {"objectID": "def658c3a83d17228a73685b81bbf7979a78a6c56aba2b79ba99b414bacbc26a", "tool": "Naas", "notebook": "Webhook demo", "action": "", "tags": ["#naas", "#webhook", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-31", "description": "## Basic formulas\nRunning this command will add your this notebook to the \"\u26a1\ufe0f Production\" folder.
\nYou can then, trigger it with the generated URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Webhook_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Webhook_demo.ipynb", "imports": ["naas", "naas", "naas"], "image_url": ""}, {"objectID": "615ec6a8a79947d3ad3332806a73e9d47724fb113848dfdbff7166e70b84e367", "tool": "Neo", "notebook": "Get currencies live prices", "action": "", "tags": ["#neo", "#bank", "#snippet", "#finance", "#csv"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides live currency prices for various currencies.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Neo/Neo_Get_currencies_live_prices.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Neo/Neo_Get_currencies_live_prices.ipynb", "imports": ["pathlib.Path", "pandas", "requests"], "image_url": ""}, {"objectID": "ad988b3acb38ff32d1a21f78c88a01d3436a580add95cb262464d26b5b65eb39", "tool": "Newsapi", "notebook": "Get data", "action": "", "tags": ["#newsapi", "#news", "#snippet", "#opendata", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a guide to using the Newsapi service to access and retrieve data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Newsapi/Newsapi_Get_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Newsapi/Newsapi_Get_data.ipynb", "imports": ["naas_drivers.newsapi"], "image_url": ""}, {"objectID": "8c7a4d82d6c655fc8c32095c16c53da8d6a524084ffa01fc55f762ffe5e37c8b", "tool": "Newsapi", "notebook": "Run sentiment analysis", "action": "", "tags": ["#newsapi", "#news", "#sentimentanalysis", "#ai", "#opendata", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-10", "description": "This notebook uses Newsapi to analyze the sentiment of news articles.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Newsapi/Newsapi_Run_sentiment_analysis.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Newsapi/Newsapi_Run_sentiment_analysis.ipynb", "imports": ["naas_drivers.newsapi, sentiment"], "image_url": ""}, {"objectID": "ad3d5031c222cb811084f9a2641946b57cd17649f5b03f8a92a93e9dc8e41b09", "tool": "Newsapi", "notebook": "Send emails briefs", "action": "", "tags": ["#newsapi", "#news", "#emailbrief", "#automation", "#notification", "#opendata", "#email", "#image", "#html", "#text"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-10", "description": "This notebook allows users to send automated email briefs based on news articles from the Newsapi API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Newsapi/Newsapi_Send_emails_briefs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Newsapi/Newsapi_Send_emails_briefs.ipynb", "imports": ["naas_drivers.newsapi, emailbuilder", "naas"], "image_url": ""}, {"objectID": "4aa241b693f1246fa34f81ec73340d9e657d507c316332d862408e86fed3942b", "tool": "Notion", "notebook": "Add bulleted list in page", "action": "", "tags": ["#notion", "#list", "#page", "#organization", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-30", "created_at": "2023-04-30", "description": "This notebook explains how to add a bulleted list in a Notion page from a list object using naas_drivers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_bulleted_list_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_bulleted_list_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "788383d93e10f1f9b502ed7ff62013a2bf073f2cfeac45af26371468ddfdd8b1", "tool": "Notion", "notebook": "Add code block in page", "action": "", "tags": ["#notion", "#code", "#page", "#organization", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-30", "created_at": "2023-04-30", "description": "This notebook explains how to add a code block in a Notion page using naas_drivers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_code_block_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_code_block_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "bb1c62a68b1e8bed37eb699e857a6e8c1670d91567737b8a3840184e186ff29d", "tool": "Notion", "notebook": "Add cover image to page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook allows you to add a cover image to a page in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_cover_image_to_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_cover_image_to_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "931f3ae1a90765ff01a284401428ad56c74361da0b992df5a610e52026fd44c4", "tool": "Notion", "notebook": "Add equation in page", "action": "", "tags": ["#notion", "#equation", "#page", "#organization", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-30", "created_at": "2023-04-30", "description": "This notebook explains how to add an equation in a Notion page using naas_drivers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_equation_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_equation_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "d0f211ded04e761c43109a9fbfd6aec9e38174a7ed52fe67e1a08acf1ebdbe25", "tool": "Notion", "notebook": "Add heading in page", "action": "", "tags": ["#notion", "#heading", "#page", "#organization", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-30", "created_at": "2023-04-30", "description": "This notebook explains how to add headings in a Notion page using naas_drivers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_heading_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_heading_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "c4808da990d67ce7069e2d1f01e33141b6d6609af3c3bb90fe732ce8dc98ae8f", "tool": "Notion", "notebook": "Add icon image to page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook allows users to add an icon image to a Notion page.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_icon_image_to_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_icon_image_to_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "93987b3107b56dd9a02b79dcba1e47e3af68eaba6f0492e3eb8de9e42684400a", "tool": "Notion", "notebook": "Add new github member to team from database", "action": "", "tags": ["#github", "#teams", "#automation", "#notion", "#operations"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-05-21", "description": "This notebook allows users to add new GitHub members to their team from a database in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_new_github_member_to_team_from_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_new_github_member_to_team_from_database.ipynb", "imports": ["requests", "naas_drivers.github, notion", "naas", "pandas"], "image_url": ""}, {"objectID": "56ee3de913cfdbf390142378217d08ff30cf5c01c780d9811b8a15593e60e2a4", "tool": "Notion", "notebook": "Add numbered list in page", "action": "", "tags": ["#notion", "#list", "#page", "#organization", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-30", "created_at": "2023-04-30", "description": "This notebook explains how to add a numbered list in a Notion page from a list object using naas_drivers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_numbered_list_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_numbered_list_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "d23f9df5b983b569726995526e7659c222c8899834f4b7b5b0e5a79f7ca0bd8a", "tool": "Notion", "notebook": "Add paragraph with link in page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#block", "#paragraph", "#link", "#snippet", "#operations"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook allows you to add a paragraph with a link to a page in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_paragraph_with_link_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_paragraph_with_link_in_page.ipynb", "imports": ["naas_drivers.notion", "naas_drivers.tools.notion.Link"], "image_url": ""}, {"objectID": "a325c9e4b91d0842ed3a531aaf5e9e21c0ff0652bab97a3f95a3eb62cc3ffd1a", "tool": "Notion", "notebook": "Add to do list in page", "action": "", "tags": ["#notion", "#todo", "#page", "#snippet", "#naas_drivers"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-28", "created_at": "2023-04-28", "description": "This notebook explains how to add a to do list in a Notion page using naas_drivers from a list.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_to_do_list_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_to_do_list_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "97611fe6842bbe2afb50f53ddebbffd33454595b869913c9d6249105197b4530", "tool": "Notion", "notebook": "Automate transcript generation from recording link in page property", "action": "", "tags": ["#notion", "#aws", "#transcribe", "#S3", "#automation"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-05-12", "description": "This notebook allows users to automatically generate transcripts from audio recordings by linking the recording to a page property in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Automate_transcript_generation_from_recording_link_in_page_property.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Automate_transcript_generation_from_recording_link_in_page_property.ipynb", "imports": ["pydash", "threading, queue", "uuid", "rich.print", "rich.print", "sys", "json", "datetime", "codecs", "time", "os", "markdown", "gdown", "gdown", "boto3", "naas_drivers.notion", "naas_drivers.tools.notion.BlockTypeFactory", "naas"], "image_url": ""}, {"objectID": "7597da846b5c5a212d1fe3763deaf09315f9358b9b04523cbea93045eba467e1", "tool": "Notion", "notebook": "Create page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-09-13", "description": "Notion is a powerful tool for creating and organizing digital pages to help you stay organized and productive.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Create_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Create_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "429365440a90db93a370330df99e41a4718d24029f7a2a3e24990304ce409614", "tool": "Notion", "notebook": "Create pages in database from dataframe", "action": "", "tags": ["#notion", "#database", "#dataframe", "#python", "#create", "#pages"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-15", "description": "This notebook will show how to create pages in Notion database from a dataframe. It could be very usefull to kick start a new database in Notion with historical data stored in CSV, Excel or Google Sheets.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Create_pages_in_database_from_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Create_pages_in_database_from_dataframe.ipynb", "imports": ["naas", "pandas", "naas_drivers.notion"], "image_url": ""}, {"objectID": "bf17bd2f86490d3fbed728c4a602153d357748a2ab81f5e3385f32c116d6fd78", "tool": "Notion", "notebook": "Delete all pages from database", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#database"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-24", "description": "This notebook deletes all page from a Notion database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Delete_all_pages_from_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Delete_all_pages_from_database.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "458696751173998a5878523a07bf2866a1d97db0aae077ae663183415f6c7178", "tool": "Notion", "notebook": "Delete blocks from page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#page"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook allows users to quickly and easily delete blocks from their Notion page.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Delete_blocks_from_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Delete_blocks_from_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "4be524b722d7eabf85ecb8dcda5e06cd8559567a9c5ccb55eba8915fb982f337", "tool": "Notion", "notebook": "Delete page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#page"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook allows you to delete a page in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Delete_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Delete_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "47be8362b5f8f8d9db5c0a9dfbc4f912f4f4593f332adfb7f9ae174fceb42ce5", "tool": "Notion", "notebook": "Duplicate page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#duplicate", "#page"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-05-26", "description": "This notebook allows you to quickly and easily duplicate a page in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Duplicate_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Duplicate_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "80547ec83f52f9ee3c926af6f709f3d25b583d2d6d2f4be6d6c7a60f0106f5d5", "tool": "Notion", "notebook": "Explore API", "action": "", "tags": ["#notion", "#productivity", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-04", "description": "This notebook provides an exploration of the Notion API, allowing users to access and manipulate data from Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Explore_API.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Explore_API.ipynb", "imports": ["requests", "pandas", "json"], "image_url": ""}, {"objectID": "98ab1c462dc32c96d8a60d3f8fa617498096792f891ac48924fc03d4b059d655", "tool": "Notion", "notebook": "Generate Google Sheets rows for new items in database", "action": "", "tags": ["#notion", "#operations", "#automation", "#googlesheets"], "author": "Pooja Srivastava", "author_url": "https://www.linkedin.com/in/pooja-srivastava-in/", "updated_at": "2023-04-12", "created_at": "2022-04-05", "description": "This notebook allows users to automatically generate Google Sheets rows for new items added to a database using Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Generate_Google_Sheets_rows_for_new_items_in_Notion_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Generate_Google_Sheets_rows_for_new_items_in_Notion_database.ipynb", "imports": ["naas_drivers.notion, gsheet", "pandas"], "image_url": ""}, {"objectID": "68a8540ec1e573bbc2c31b844cc383fa99b73ec2781df0f494fdb9f41965b46a", "tool": "Notion", "notebook": "Get blocks from page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#page"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook allows users to quickly and easily add blocks from a page to their Notion workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Get_blocks_from_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Get_blocks_from_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "7c5540e6853c6605a0a64c7bd1860d3bcf4b7843ecbae96ae22a318b4f2fa5dc", "tool": "Notion", "notebook": "Get database", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-08-23", "description": "Notion is a powerful database tool that helps you organize and store your data in an intuitive and efficient way.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Get_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Get_database.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "42775adb8e2a5be84c11094169c73f67378aa924d6030d5b0e5cdbcf84e84980", "tool": "Notion", "notebook": "Get page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#page"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-08-16", "description": "This notebook allows you to quickly and easily create and organize webpages for any purpose.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Get_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Get_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "cf37eca2469767cb53d562a97383fb6cad12c0691fb3b44fabdbfc1030ec3d5d", "tool": "Notion", "notebook": "Get users", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-11-01", "description": "Notion is a powerful tool that helps users organize their thoughts, tasks, and projects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Get_users.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Get_users.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "77e598f0bed1b6807032066684a6b6aceed5057fd135e73b41791915c998bea3", "tool": "Notion", "notebook": "Send LinkedIn invitations from database", "action": "", "tags": ["#notion", "#invitation", "#automation", "#content", "#linkedin"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-04-07", "description": "This notebook allows users to quickly and easily send LinkedIn invitations to contacts stored in a database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Send_LinkedIn_invitations_from_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Send_LinkedIn_invitations_from_database.ipynb", "imports": ["naas", "naas_drivers.notion, linkedin", "pandas", "os", "datetime.datetime", "requests"], "image_url": ""}, {"objectID": "e07ad2e7f764a2bd25534ca5e6a87a54d39d7a73d4b297b21b44cc8a4e51518e", "tool": "Notion", "notebook": "Send Slack Messages For New Database Items", "action": "", "tags": ["#notion", "#slack", "#operations", "#automation"], "author": "Sanjeet Attili", "author_url": "https://api.slack.com/authentication/basics\n\n- For this use case we need to create & use user token, rather than bot token with the following permissions/scopes -> [channels: history, channels: read, chat: write, users: read]", "updated_at": "2023-04-12", "created_at": "2022-03-31", "description": "## Input", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Send_Slack_Messages_For_New_Notion_Database_Items.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Send_Slack_Messages_For_New_Notion_Database_Items.ipynb", "imports": ["naas_drivers.notion, slack", "naas"], "image_url": ""}, {"objectID": "906dd0ec9b68828a094cc58111e34dd14acf152e2491afde7116537297f31733", "tool": "Notion", "notebook": "Sent Gmail On New Item", "action": "", "tags": ["#notion", "#gsheet", "#productivity", "#naas_drivers", "#operations", "#automation", "#email"], "author": "Arun K C", "author_url": "https://www.linkedin.com/in/arun-kc/", "updated_at": "2023-04-12", "created_at": "2022-01-20", "description": "This notebook allows you to quickly send an email notification when a new item is added to Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Sent_Gmail_On_New_Item.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Sent_Gmail_On_New_Item.ipynb", "imports": ["naas", "naas_drivers.notion, gsheet", "naas_drivers.html", "pandas"], "image_url": ""}, {"objectID": "647d794df1c42fc8ef111f4ab6109a20bf4dd82da1279723111080e06d84f250", "tool": "Notion", "notebook": "Update database with GitHub repositories info", "action": "", "tags": ["#notion", "#database", "#update", "#github", "#repositories", "#automation", "#scheduler"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-13", "created_at": "2023-04-12", "description": "This notebook updates a Notion database with information from all repositories within your GitHub organization. The following data will be updated in your Notion database:\n- Name: The name of the repository.\n- GitHub URL: The URL for the repository on GitHub.\n- Description: A brief description of what the repository is for.\n- Default branch: The default branch for the repository (i.e., the branch that is checked out when someone first clones the repository).\n- Visibility: The visibility status of the repository (e.g., public, private, or internal).\n- Created date: The date when the repository was created.\n- Last updated date: The date when the repository was last updated.\n- Open Issues: The number of unresolved issues (i.e., bug reports, feature requests, or other tasks) in the repository.\n- Forks: The number of times the repository has been forked (i.e., copied to another GitHub account).\n- Stargazers: The number of GitHub users who have \"starred\" the repository (i.e., marked it as a favorite).\n- Size: The size of the repository in terms of disk space used.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_database_with_GitHub_repositories_info.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_database_with_GitHub_repositories_info.ipynb", "imports": ["naas", "naas_drivers.notion", "pandas", "re", "datetime.datetime", "os", "requests", "naas", "github"], "image_url": ""}, {"objectID": "3d62f956e5054214458eaa0d181bcdcf3eb6992b59688563cc9eeb75c60e0ed3", "tool": "Notion", "notebook": "Update database with LinkedIn company info", "action": "", "tags": ["#notion", "#database", "#update", "#linkedin", "#company", "#automation", "#scheduler"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-13", "created_at": "2023-04-07", "description": "This notebook streamlines the process of updating a Notion database containing company names by extracting relevant information from LinkedIn using Google search, as well as utilizing Naas_Drivers.Notion and Naas_Drivers.LinkedIn.The following data will be updated in your Notion database:\n- Name: The name of the company or organization.\n- LinkedIn: The company's LinkedIn page.\n- Website: The company's website URL.\n- Industry: The industry or industries that the company operates in.\n- Specialties: The areas of expertise or specialization for the company or its products/services.\n- Tagline: A brief statement that summarizes the purpose or mission of the company or organization.\n- City: The city or cities where the company is headquartered or operates.\n- Country: The country where the company is headquartered or operates.\n- Staff Count: The number of employees or staff members employed by the company.\n- Staff Range: The range of employee count (e.g., 1-10, 11-50, 51-200, etc.) that the company falls into.\n- Followers: The number of LinkedIn users who follow the company's page or profile.\n\nOverall, this notebook can be useful for any business or individual who needs to keep track of company information for various purposes:\n- Sales prospecting: Sales teams could use the updated database to identify potential new leads and target them with personalized outreach based on their company information.\n- Competitor analysis: Marketers could use the updated database to track changes in their competitors' company information, such as changes in leadership or expansion into new markets.\n- Industry research: Researchers could use the updated database to gather information on companies within a particular industry, such as their size, location, and areas of expertise.\n- Investor relations: Investors could use the updated database to identify potential investment opportunities and track the performance of companies they are interested in.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_database_with_LinkedIn_company_info.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_database_with_LinkedIn_company_info.ipynb", "imports": ["naas", "naas_drivers.linkedin, notion", "googlesearch.search", "googlesearch.search", "re", "datetime.datetime", "os", "requests", "pandas", "time"], "image_url": ""}, {"objectID": "1033382f0063e3cfe04100c99b1780a7eda0ca450d3e26f634e50217db5c1f0d", "tool": "Notion", "notebook": "Update database with LinkedIn profile info", "action": "", "tags": ["#notion", "#database", "#update", "#linkedin", "#company", "#automation", "#scheduler"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-13", "created_at": "2023-04-13", "description": "This notebook streamlines the process of updating a Notion database containing profile names by extracting relevant information from LinkedIn using Google search, as well as utilizing Naas_Drivers.Notion and Naas_Drivers.LinkedIn. The following data will be updated in your Notion database:\n- Name: The name of the person who owns the LinkedIn profile.\n- LinkedIn: LinkedIn unique URL\n- Occupation: The job or profession that a person is engaged in, listed on their LinkedIn profile.\n- Industry: The field or sector in which a person works, listed on their LinkedIn profile.\n- City: The specific city where a person lives or works, listed on their LinkedIn profile.\n- Region: A broader geographic area that a person's city may be located in, such as a state or province, listed on their LinkedIn profile.\n- Country: The nation where a person is located or from, listed on their LinkedIn profile.\n- Location: The overall geographic location of a person, which may include their city, region, and country, listed on their LinkedIn profile.\nAdditionally, the background picture will be refreshed as the page cover, the profile picture will serve as the page icon, and the occupation and summary will be included in the page block.\n\nOverall, this notebook can be useful for any business or individual who needs to keep track of company information for various purposes:\n- Lead generation: Sales teams could use the updated Notion database to identify potential leads based on their LinkedIn profiles, and initiate targeted outreach to convert them into customers.\n- Talent sourcing: Recruiters could use the updated Notion database to find and evaluate potential job candidates based on their LinkedIn profiles and relevant information stored in the database.\n- Social media marketing: Marketers could use the updated Notion database to build custom audiences for their social media campaigns based on the information stored in the database and on LinkedIn.\n\nDisclamer:\n\nWhen using this script to scrape profiles from LinkedIn, it's important to set a limit on the number of API calls made to avoid being temporarily banned. LinkedIn heavily monitors scraping activities, and excessive usage can result in a ban. We recommend setting a limit of no more than 5 calls per hour to minimize the risk of being banned. As the owner of the script, it's your responsibility to use it responsibly and abide by LinkedIn's terms of service. We assume no liability for any consequences resulting from your use of this script.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_database_with_LinkedIn_profile_info.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_database_with_LinkedIn_profile_info.ipynb", "imports": ["naas", "naas_drivers.linkedin, notion", "googlesearch.search", "googlesearch.search", "re", "datetime.datetime", "os", "requests", "pandas", "time"], "image_url": ""}, {"objectID": "43d0796ae3f58df0ec5a640ddf8e9f266d824f70fa69f7c5040b370b38891ce0", "tool": "Notion", "notebook": "Update page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-11-01", "description": "This page allows you to update existing content in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "235b5d348b55afe007e3513452df95b030d2cc3d20d5b5fcb660fca90b2bb5cc", "tool": "Notion", "notebook": "Update page relation", "action": "", "tags": ["#notion", "#update", "#page", "#relation", "#requests", "#api"], "author": "Florent Ravenel", "author_url": "https://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-24", "description": "This notebook will show how to update page relation using requests. It is usefull for organization to link different database in Notion and keep track of their data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_page_relation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_page_relation.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "0f1c3555b4539891a61581be2563e3fd819cdb141143895228ae433671329520", "tool": "Notion", "notebook": "Update pages from database", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-02-07", "description": "This notebook allows users to easily update Notion pages with data from a database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_pages_from_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_pages_from_database.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "f31df883dd65a1a2a6c484ade655deba402bdba6d0e39ad0c1c39134cd906e05", "tool": "Notion", "notebook": "Upload PDF in page", "action": "", "tags": ["#notion", "#upload", "#pdf", "#page", "#snippet", "#naas_drivers"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-28", "created_at": "2023-04-28", "description": "This notebook explains how to upload a PDF in a Notion page using naas_drivers. It is usefull for organizations that need to share PDFs to their Notion pages.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Upload_PDF_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Upload_PDF_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "07b01cd0416973045c2e923af3028b3a426dc84dfc193499ee839e0e47bedaba", "tool": "Notion", "notebook": "Upload image in page", "action": "", "tags": ["#notion", "#upload", "#image", "#page", "#snippet", "#naas_drivers"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-28", "created_at": "2023-04-28", "description": "This notebook explains how to upload an image in a Notion page using naas_drivers. It is usefull for organizations that need to add visuals to their Notion pages.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Upload_image_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Upload_image_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "c0cc2a6a750077e302585962ecee4b2ae5eb1195392b4b4477497044184b4bb2", "tool": "Notion", "notebook": "Upload video in page", "action": "", "tags": ["#notion", "#upload", "#video", "#page", "#snippet", "#naas_drivers"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-28", "created_at": "2023-04-28", "description": "This notebook explains how to upload a video in a Notion page using naas_drivers. It is usefull for organizations that need to add videos to their Notion pages.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Upload_video_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Upload_video_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "977ec013ec588028ac032ba6a88411db2b70ed9108e892a74d52b4bacec388ac", "tool": "OS", "notebook": "Access environment variable", "action": "", "tags": ["#python", "#environment", "#variables", "#os", "#environ", "#object", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook explains how to access a particular environment variable using the Python `os.environ` object. Environment variables are useful in several ways:\n- Portability: Environment variables are independent of the code and can be easily ported across systems. This means that you can define an environment variable once, and use it in multiple scripts, applications, or systems without having to hardcode the variable's value.\n- Security: Environment variables can be used to store sensitive information like passwords or API keys, which can be accessed by the code without exposing them in the script. This is particularly useful when you need to deploy your code to a server or share it with others.\n- Flexibility: Environment variables allow you to change the behavior of your code without modifying the code itself. This is useful when you need to modify the behavior of your code based on different scenarios, such as development, testing, or production environments.\n- Configuration: Environment variables can be used to configure your code, by providing default values for variables that can be overridden by environment variables. This makes your code more flexible and easier to customize.\n\nOverall, environment variables are a useful tool for managing configuration settings and sensitive information in your code, and can make your code more portable, secure, and flexible.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Access_environment_variable.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Access_environment_variable.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "7bb2bd353adc40ef26a95c190775b078cdc6c910196b17c68f2f8b700bcaa585", "tool": "OS", "notebook": "Add new environment variable", "action": "", "tags": ["#python", "#environment", "#variables", "#os", "#environ", "#object", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook explains how to add or update variables in environment using the Python `os.environ` object. Environment variables are useful in several ways:\n- Portability: Environment variables are independent of the code and can be easily ported across systems. This means that you can define an environment variable once, and use it in multiple scripts, applications, or systems without having to hardcode the variable's value.\n- Security: Environment variables can be used to store sensitive information like passwords or API keys, which can be accessed by the code without exposing them in the script. This is particularly useful when you need to deploy your code to a server or share it with others.\n- Flexibility: Environment variables allow you to change the behavior of your code without modifying the code itself. This is useful when you need to modify the behavior of your code based on different scenarios, such as development, testing, or production environments.\n- Configuration: Environment variables can be used to configure your code, by providing default values for variables that can be overridden by environment variables. This makes your code more flexible and easier to customize.\n\nOverall, environment variables are a useful tool for managing configuration settings and sensitive information in your code, and can make your code more portable, secure, and flexible.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Add_new_environment_variable.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Add_new_environment_variable.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "141f931922bdd2a673d198df328243e7aed56d0ecd1f1c4c83a1b08a2ba263f5", "tool": "OS", "notebook": "Check path exist", "action": "", "tags": ["#os", "#python", "#path", "#file", "#system", "#library", "#snippet", "#operations", "#check"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-08", "created_at": "2023-06-08", "description": "This notebook will show how to check a path exist using os library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Check_path_exist.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Check_path_exist.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "86ee474d174e9f2394b370c69bd4c0de68646b8b9c45c02cbce83cf4edde0a74", "tool": "OS", "notebook": "Create directory", "action": "", "tags": ["#os", "#snippet", "#python", "#operations"], "author": "Moemen Ebdelli", "author_url": "https://www.linkedin.com/in/moemen-ebdelli", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook provides instructions on how to create a directory in Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Create_directory.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Create_directory.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "2eca9945533598a7b77fba6dd42d083942103cf78ce933470cfdedc5f385d6da", "tool": "OS", "notebook": "Get access of environment variables", "action": "", "tags": ["#python", "#environment", "#variables", "#os", "#environ", "#object"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook explains how to use of `os.environ` to get access of environment variables. Environment variables are useful in several ways:\n- Portability: Environment variables are independent of the code and can be easily ported across systems. This means that you can define an environment variable once, and use it in multiple scripts, applications, or systems without having to hardcode the variable's value.\n- Security: Environment variables can be used to store sensitive information like passwords or API keys, which can be accessed by the code without exposing them in the script. This is particularly useful when you need to deploy your code to a server or share it with others.\n- Flexibility: Environment variables allow you to change the behavior of your code without modifying the code itself. This is useful when you need to modify the behavior of your code based on different scenarios, such as development, testing, or production environments.\n- Configuration: Environment variables can be used to configure your code, by providing default values for variables that can be overridden by environment variables. This makes your code more flexible and easier to customize.\n\nOverall, environment variables are a useful tool for managing configuration settings and sensitive information in your code, and can make your code more portable, secure, and flexible.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Get_access_of_environment_variables.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Get_access_of_environment_variables.ipynb", "imports": ["os", "pprint"], "image_url": ""}, {"objectID": "c7bf168e0033b04e424d24283c3804f677d20958b8a7519e60e69f4a176cddc1", "tool": "OS", "notebook": "Get current working directory", "action": "", "tags": ["#os", "#python", "#snippet", "#operations", "#operatingsystem"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook demonstrates how to get the current working directory using `os` module. The main purpose of the OS module is to interact with your operating system. The primary use I find for it is to create folders, remove folders, move folders, and sometimes change the working directory. You can also access the names of files within a file path by doing listdir(). We do not cover that in this video, but that's an option.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Get_current_working_directory.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Get_current_working_directory.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "9527abdf0d80d051bbee0006c3948f220d4254591ef205fbd310d2e5f672e8e3", "tool": "OS", "notebook": "Get folder stats", "action": "", "tags": ["#os", "#folder", "#stats", "#python", "#library", "#filesystem"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-05", "created_at": "2023-07-05", "description": "This notebook will get the stats of a folder and its content.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Get_folder_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Get_folder_stats.ipynb", "imports": ["os", "datetime.datetime"], "image_url": ""}, {"objectID": "17ab0d4319f5f16b54359cb73279a21fea85248f5b54e3e982edc251fe0735df", "tool": "OS", "notebook": "List entries in directory", "action": "", "tags": ["#os", "#listdir", "#directory", "#python", "#entries", "#list"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-13", "created_at": "2023-06-13", "description": "This notebook explains how to use the Python method listdir() to list entries in a directory. It is usefull for organizations to quickly access the content of a directory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_List_entries_in_directory.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_List_entries_in_directory.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "fa208f2a6760c8f1d61394c59eb08948b2421d0ca23668df0927b40b12a0ee11", "tool": "OS", "notebook": "Remove file", "action": "", "tags": ["#os", "#python", "#remove", "#file", "#system", "#library", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook will show how to remove file from system using os library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Remove_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Remove_file.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "41e782306e5647529deb821db88d07feef810caef4389f00189aaaf47a7207c8", "tool": "OS", "notebook": "Rename file", "action": "", "tags": ["#os", "#python", "#snippet", "#operations"], "author": "Divakar", "author_url": "https://www.linkedin.com/in/divakar-r-9b34b86b/", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook will show how to rename file using os library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Rename_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Rename_file.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "b536a539006dced496f5dee0a0054d535f4880f440631c3b26f6f8d5f626c7d6", "tool": "OWID", "notebook": "Visualize GDP per capita through the years", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's GDP per capita data. The values are calculated by taking the expenditure-side real GDP at chained PPPs and dividing by the population.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_GDP_per_capita_through_the_years.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_GDP_per_capita_through_the_years.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "6e7757204de2a51a6e8288197ddf9daa841e3eb0df0cbf09e51e26d7ed655035", "tool": "OWID", "notebook": "Visualize Human Development Index", "action": "", "tags": ["#owid", "#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-08-07", "created_at": "2023-08-07", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's HDI data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_Human_Development_Index.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_Human_Development_Index.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "efd4c086cffe158c960a2bc7ea8dc9f71663b0deca619bccc47ec7ce81729245", "tool": "OWID", "notebook": "Visualize oil consumption throughout the years", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-06-26", "created_at": "2023-06-26", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's oil consumption data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_Oil_Consumption_through_the_Years.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_Oil_Consumption_through_the_Years.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "4b06d4ef00af69ff2b94b5dd3745d5d6b9d2544014f0e2f317599a3a4174f360", "tool": "OWID", "notebook": "Visualize Population of Different Age Groups", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-08-04", "created_at": "2023-07-12", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's popultion by age group data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_Population_of_Different_Age_Groups.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_Population_of_Different_Age_Groups.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express", "naas"], "image_url": ""}, {"objectID": "7db31d10c4b5b92d0d39f1d3dc6ee14dc4e511f4718304f9cfb63394215ce6e8", "tool": "OWID", "notebook": "Visualize economic freedom through the years", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's economic freedom ranking data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_economic_freedom_through_the_years.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_economic_freedom_through_the_years.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "54dbdfd194259317e5cc940745c978c24d6b9369f598c3db583326036b883167", "tool": "OWID", "notebook": "Visualize greenhouse gas per capita", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's greenhouse gas emissions per capita data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_greenhouse_gas_per_capita.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_greenhouse_gas_per_capita.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "cc3affc15c3291bab55e3463dfad9686c656e095970dbcfdce0e1000938d1b0e", "tool": "OWID", "notebook": "Visualize Life expectancy at birth for both sexes throughout the years", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's life exepctancy data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_life_expectancy_at_birth_for_both_sexes_through_out_the_years.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_life_expectancy_at_birth_for_both_sexes_through_out_the_years.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "cdf2fb54787b4191d2516b1cc6e7000a531dfa63a2142118ccd6c91cf6435684", "tool": "OWID", "notebook": "Tourist depature per 1000", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's tourist departures per 1000 data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_tourist_departures_per_1000.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_tourist_departures_per_1000.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "304c492a6ad755b2370ccec6705ca275e6fd9dd894580e1e4f7663bb73341059", "tool": "OWID", "notebook": "Visualize wealth distribuition of certain major economic powers", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's wealth distribution data. It shows the percentage of personal wealth obtained by the top 1% and the top 10%.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_wealth_distribution.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_wealth_distribution.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "b0de207f2a64ae314c14994522d6994a3c3cbae7fc6d5b79be15da7d8e223d0e", "tool": "OWID", "notebook": "Visualize world population growth", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-08-07", "created_at": "2023-08-07", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's world population growth data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_world_population_growth.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_world_population_growth.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "dd67e8c7161225db2d49f17a8c6a4a6cc7271cedae8a67457fd0c8f93a77fe27", "tool": "OpenAI", "notebook": "Act as a AI enthusiast", "action": " ", "tags": ["#ai", "#aienthusiast", "#artificialintelligence", "#aitrends", "#aiconcepts", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as an AI enthusiast.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_AI_enthusiast.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_AI_enthusiast.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_AI_enthusiast.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "e089ce867bca0f37f131ec352c85601eff2db8edd0911052eac3475fc655090e", "tool": "OpenAI", "notebook": "Act as a Business Analyst", "action": " ", "tags": ["#ai", "#businessanalyst", "#businessdata", "#businessprocess", "#strategicrecommendations", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Business Analyst.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Business_Analyst.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Business_Analyst.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Business_Analyst.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "fd738792e7b58c349a01bc30c83d122ce30392568a232eda55191d80dc6814d9", "tool": "OpenAI", "notebook": "Act as a CEO", "action": " ", "tags": ["#ai", "#ceo", "#businessstrategy", "#leadership", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a CEO.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_CEO.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_CEO.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_CEO.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "3e28fb1c0bcee19d8c363e9e8addc7cee4ad8969a4f6c9921f2a3e8ce96b9e83", "tool": "OpenAI", "notebook": "Act as a COO", "action": " ", "tags": ["#ai", "#coo", "#operationsmanagement", "#processimprovement", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a COO.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_COO.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_COO.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_COO.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "eec5d99cbc73d38ea2e7400ca902510b35ec5ebdbe153092031f147f43267fbc", "tool": "OpenAI", "notebook": "Act as a CTO", "action": " ", "tags": ["#ai", "#cto", "#technologystrategy", "#innovation", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a CTO.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_CTO.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_CTO.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_CTO.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "65dc3f7dae157ebebe828bd8061d78213f87fc22fc9fd49d327c35513ec477cd", "tool": "OpenAI", "notebook": "Act as a Creative Writer or Artist", "action": " ", "tags": ["#ai", "#creativewriter", "#artist", "#creativity", "#artistictechniques", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Creative Writer or Artist.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Creative_Writer_or_Artist.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Creative_Writer_or_Artist.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Creative_Writer_or_Artist.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "1afec4ff0f173c25314065d105a85838b48804ff47595ce2444ccfb5ca26fcb6", "tool": "OpenAI", "notebook": "Act as a Data Analyst", "action": " ", "tags": ["#ai", "#dataanalyst", "#datadrivendecisions", "#datamining", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Data Analyst.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Data_Analyst.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Data_Analyst.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Data_Analyst.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "a6c10ae13d722f012562c528deb87b8e69e98b94554d16adbd3f38269cbe5b51", "tool": "OpenAI", "notebook": "Act as a Data Scientist", "action": " ", "tags": ["#ai", "#datascientist", "#predictivemodels", "#machinelearning", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Data Scientist.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Data_Scientist.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Data_Scientist.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Data_Scientist.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "55fd10670c15ad9320e3aa49bcb93b4c066c52f0cf509efd9fc98c280d6ddfe7", "tool": "OpenAI", "notebook": "Act as a Educator or student", "action": " ", "tags": ["#ai", "#educator", "#student", "#academictopics", "#teachingstrategies", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as an Educator or Student.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Educator_or_student.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Educator_or_student.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Educator_or_student.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "55eae5ebdc323c73316e2e081956e9eac4bbeb2a0839a125a3cfe59b862194ca", "tool": "OpenAI", "notebook": "Act as a Hobbyist", "action": " ", "tags": ["#ai", "#hobbyist", "#personalprojects", "#hobbyimprovement", "#skilllearning", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Hobbyist.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Hobbyist.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Hobbyist.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Hobbyist.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "940a2ff7ae284b98d7de3461aa5d1e39e7f81da8c48e3625eee2a2f0489a1733", "tool": "OpenAI", "notebook": "Act as a Homeowner", "action": " ", "tags": ["#ai", "#homeowner", "#homeimprovement", "#homemaintenance", "#interiordesign", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Homeowner.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Homeowner.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Homeowner.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Homeowner.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "43d678efc249da05fe4325e50508c8b2b8daa6223fbb14959a550c6266f8ae6f", "tool": "OpenAI", "notebook": "Act as a IT Professional", "action": " ", "tags": ["#ai", "#itprofessional", "#technicalsupport", "#itinfrastructure", "#ittrends", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as an IT Professional.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_IT_Professional.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_IT_Professional.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_IT_Professional.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "99f62044e567ead43fe936c1e72f88cd37d15b79a0c89cca5a9e21c00ef98a13", "tool": "OpenAI", "notebook": "Act as a Lifelong learner", "action": " ", "tags": ["#ai", "#lifelonglearner", "#knowledgeseeker", "#skilllearning", "#subjectexploration", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Lifelong Learner.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Lifelong_learner.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Lifelong_learner.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Lifelong_learner.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "f54c6d7a2daa62c82a631fa4ab51c338f914000cd3f1d19da7c969fff7d188a2", "tool": "OpenAI", "notebook": "Act as a Marketer", "action": " ", "tags": ["#ai", "#marketer", "#marketingstrategy", "#markettrends", "#brandengagement", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Marketer.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Marketer.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Marketer.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Marketer.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "084134f6feae47a6c539c638604e7d552f8893513c977ff459d76fced826328e", "tool": "OpenAI", "notebook": "Act as a Parent or Child", "action": " ", "tags": ["#ai", "#parent", "#child", "#parentingchallenges", "#schoolwork", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Parent or Child.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Parent_or_Child.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Parent_or_Child.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Parent_or_Child.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "ca91e684a5fc178a0b1dbb80ab49c3e5386ce19b51eda90c63427cb68e6b5025", "tool": "OpenAI", "notebook": "Act as a Product Manager", "action": " ", "tags": ["#ai", "#productmanager", "#productdevelopment", "#marketresearch", "#userexperience", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Product Manager.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Product_Manager.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Product_Manager.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Product_Manager.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "24bd8cd6a348ded1f22936aec33f1a0522c76226c9a996dddd8c73dad98049f3", "tool": "OpenAI", "notebook": "Act as a Project Manager", "action": " ", "tags": ["#ai", "#projectmanager", "#projectplanning", "#resourcemanagement", "#riskmanagement", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Project Manager.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Project_Manager.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Project_Manager.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Project_Manager.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "3c3958d3f040b8f3d30c0d40b70f64c1af78aa46103f47a7d10b2c2af6072c7b", "tool": "OpenAI", "notebook": "Act as a Retiree", "action": " ", "tags": ["#ai", "#retiree", "#retirementactivities", "#newskills", "#retirementmanagement", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Retiree.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Retiree.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Retiree.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Retiree.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "bca43175667c72622b34f1fb4feac25f63315fda2ec00144181e56f6620145b4", "tool": "OpenAI", "notebook": "Act as a Sales Professional", "action": " ", "tags": ["#ai", "#salesprofessional", "#salesstrategies", "#customerrelations", "#salestechniques", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Sales Professional.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Sales_Professional.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Sales_Professional.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Sales_Professional.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "12d9e1e7fe7284ba1cd450267f66313c8eb3580426bcac8b44048910f6870162", "tool": "OpenAI", "notebook": "Act as a Software Developer", "action": " ", "tags": ["#ai", "#softwaredeveloper", "#coding", "#softwaredevelopment", "#programminglanguages", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Software Developer.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Software_Developer.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Software_Developer.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Software_Developer.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "1e73b76a7ed2ddd2004c409dcfa0e5b4d768f38ba91a690233b9fe071ec97e8a", "tool": "OpenAI", "notebook": "Act as a Software Engineer", "action": " ", "tags": ["#ai", "#softwareengineer", "#softwareengineering", "#systemdesign", "#scalability", "#optimization", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Software Engineer.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Software_Engineer.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Software_Engineer.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Software_Engineer.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "f35bc89e26b1b3cffbedd7e3dee835cbd5a12a497b536b2399f7c82462ec2953", "tool": "OpenAI", "notebook": "Act as a chef", "action": " ", "tags": ["#openai", "#chef", "#cooking", "#ai", "#machinelearning", "#deeplearning", "#plugin"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-19", "created_at": "2023-05-29", "description": "This notebook will create a plugin to act as a chef and use OpenAI to create delicious recipes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_chef.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_chef.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_chef.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "2b4754fa5dd2c8e1691f721e48e3e11917c629c0fb2438ffd78503ee63e4bc57", "tool": "OpenAI", "notebook": "Brainstorm ideas", "action": "", "tags": ["#openai", "#brainstorm", "#ideas", "#ai", "#machinelearning", "#deeplearning"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will help brainstorm ideas on a specific topic using OpenAI.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Brainstorm_ideas.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Brainstorm_ideas.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "64991d5e7374c52b3e71bbb365667239daea4ce7f872425c483d7da87c59b9f0", "tool": "OpenAI", "notebook": "Count tokens with tiktoken", "action": "", "tags": ["#openai", "#tiktoken", "#count", "#token", "#tokens", "#cookbook"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-16", "created_at": "2023-06-16", "description": "This notebook shows how to count tokens used from a string with tiktoken to use OpenAI API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Count_tokens_with_tiktoken.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Count_tokens_with_tiktoken.ipynb", "imports": ["tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "af9a04ddc27f4c638f42e4ea923fc3a24aad1d38516af8f9dc4ad3b262d29647", "tool": "OpenAI", "notebook": "Create Completion", "action": "", "tags": ["#openai", "#gpt3", "#textcompletion", "#ai", "#machinelearning", "#deeplearning", "#nlp", "#datascience", "#artificialintelligence", "#tech", "#innovation", "#creativity"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-31", "created_at": "2023-02-06", "description": "This notebook guides you through the process of using OpenAI's Generative Pretrained Transformer 3 (GPT-3) model to build a text completion application. This notebook will show you how to fine-tune GPT-3 to generate text based on a given prompt, and then integrate it into a web application for easy usage. The end result will be a working text completion tool that can be used to generate new ideas, suggestions, or even entire texts with just a few inputs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Create_Completion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Create_Completion.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "ce29f2ffe243c1ea092cd43ea7e5e42e8d39d6180230ab0ab9db873d168cbb4b", "tool": "OpenAI", "notebook": "Create chat completion", "action": "", "tags": ["#openai", "#chat", "#completion", "#model", "#response", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-31", "created_at": "2023-05-12", "description": "This notebook creates a model response for the given chat conversation. It uses OpenAI's API to generate a response based on the conversation context. This is useful for organizations that need to generate automated responses to customer inquiries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Create_chat_completion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Create_chat_completion.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "80af0a91b7797150d190e1dbab405133c6fb5be12cf1043b33c2709ee7eacdaa", "tool": "OpenAI", "notebook": "Create chatbot", "action": "", "tags": ["#openai", "#chatbot", "#conversation", "#ai", "#nlp", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-31", "created_at": "2023-05-31", "description": "This notebook create a chat conversation with OpenAI based on the initial system information. To stop it, just write \"STOP\" in the user input section.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Create_chatbot.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Create_chatbot.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "c51c4610007ed74a0ecde9c8fd0a9fc269e96164e2ba4f6fe7fc971bf86943e6", "tool": "OpenAI", "notebook": "Generate_Act_as_a_x_notebook", "action": "", "tags": ["#openai", "#ai", "#machinelearning", "#deeplearning", "#notebooks", "#automation", "#gsheet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook creates \"Act as a ...\" notebooks from a Google Sheets spreadsheet using OpenAI_Act_as_a_chef.ipynb as template.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_Act_as_a_x_notebook.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_Act_as_a_x_notebook.ipynb", "imports": ["papermill.iorw.(", "naas", "naas_drivers.gsheet", "copy", "json", "subprocess"], "image_url": ""}, {"objectID": "00885f380a5e98de1dfc84407a532f4ee99e7db3944644806fe32800b7c70a17", "tool": "OpenAI", "notebook": "Generate Dialogue", "action": "", "tags": ["#openai", "#gpt", "#api", "#prompt"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-03-18", "description": "This template shows how to use the OpenAI API to generate responses to user input within a Naas notebook, allowing users to create interactive chatbots or dialogue systems.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_Dialogue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_Dialogue.ipynb", "imports": ["naas", "openai", "openai"], "image_url": ""}, {"objectID": "388967283e9e6cc7c2fb3566e6e171bf2d3a1ec9a74ee315d6751e0efe6e850c", "tool": "OpenAI", "notebook": "Generate Q&A", "action": "", "tags": ["#openai", "#q&a"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-04-12", "created_at": "2023-03-16", "description": "This notebook shows how to use the OpenAI API to generate answer to a question.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_Q%26A.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_Q%26A.ipynb", "imports": ["naas", "os", "openai", "openai"], "image_url": ""}, {"objectID": "f4334e52da15c82c96fa2ba1ebc2a7e0e769de9f92ed2b06ff6db3e4ac828cb3", "tool": "OpenAI", "notebook": "Generate README for GitHub repository", "action": "", "tags": ["#openai", "#github", "#readme", "#repository", "#generate", "#automation"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-04-11", "description": "This notebook will generate a README for a GitHub repository based on the project name and description.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_README_for_GitHub_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_README_for_GitHub_repository.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "5435d7164828670bd059f0d88f7fad45e8ccd8ed1ae0893b4685b6b3d5debbbd", "tool": "OpenAI", "notebook": "Generate Text to Speech", "action": "", "tags": ["#openai"], "author": "Sriniketh Jayasendil", "author_url": "http://linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-02-10", "description": "This notebook focusses on using OpenAI for text-to-speech generation using [gTTS](https://pypi.org/project/gTTS/)", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_Text_to_Speech.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_Text_to_Speech.ipynb", "imports": ["os", "naas", "openai", "openai", "gtts.gTTS", "gtts.gTTS"], "image_url": ""}, {"objectID": "7c89c1b529294dde50d26637c99788c03044af0f901bd4986f554996a3e2e8f3", "tool": "OpenAI", "notebook": "Generate image from text", "action": "", "tags": ["#openai", "#image", "#text", "#generation"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel", "updated_at": "2023-06-09", "created_at": "2023-06-06", "description": "This notebook shows how to use the OpenAI API to make create images from text using Dall-E.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_image_from_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_image_from_text.ipynb", "imports": ["os", "openai # OpenAI Python library to make API calls", "requests # used to download images", "os # used to access filepaths", "PIL.Image # used to print and edit images", "naas # used to generate shareable image link", "openai"], "image_url": ""}, {"objectID": "60e910eeeaabf738f5c0852cc429357d0e707b935b2cd1fbbbae96d09e0ccca6", "tool": "OpenAI", "notebook": "Generate language translations", "action": "", "tags": ["#openai", "#language", "#translation", "#ai", "#translator", "#operations", "#snippet"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2023-02-05", "description": "This notebook translates a given text to a language of choice using OpenAI.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_language_translations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_language_translations.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "5e3fa80c5c4704e4070b51b8cc7f3b4cd631b82a81621d798a826780aa00e474", "tool": "OpenAI", "notebook": "Generate text based prediction", "action": "", "tags": ["#openai", "#prediction", "#text"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-04-12", "created_at": "2023-03-08", "description": "This notebook shows how to use the OpenAI API to make predictions based on text data", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_text_based_prediction.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_text_based_prediction.ipynb", "imports": ["os", "openai", "openai"], "image_url": ""}, {"objectID": "fd2a1ab9606a02f8b8004c754a617821290a3e99ba1f9c7e610be1423d93a261", "tool": "OpenAI", "notebook": "Generate text replacements", "action": "", "tags": ["#openai", "#text_replacement"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-04-12", "created_at": "2023-03-23", "description": "This notebook shows how to use the OpenAI API to generate text replacements such as correcting grammatical errors or making text more formal.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_text_replacements.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_text_replacements.ipynb", "imports": ["naas", "os", "openai", "openai"], "image_url": ""}, {"objectID": "2961a8fa985173e1fe7bc9ecd7dded9230b4249964c082484466ef3c7e8b95d5", "tool": "OpenAI", "notebook": "Generate text summaries", "action": "", "tags": ["#openai", "#text", "#summary"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook shows how to use the OpenAI API to generate text summaries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_text_summaries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_text_summaries.ipynb", "imports": ["naas", "openai", "openai"], "image_url": ""}, {"objectID": "b9e07c5aa5d74211244f408194927ef89fa7cb5a191606fe230c798269d684f9", "tool": "OpenAI", "notebook": "Write a blog post", "action": "", "tags": ["#openai", "#blogpost", "#writing", "#ai", "#machinelearning", "#deeplearning"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will provide a step-by-step guide to writing a blog post using OpenAI.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Write_a_blog_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Write_a_blog_post.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "3afca0fde41d0b659bad065a920c3475ddfb1367a5df0fa4d2cb7a5a32143e49", "tool": "OpenAI", "notebook": "Write a job description", "action": "", "tags": ["#openai", "#jobdescription", "#writing", "#hiring", "#recruiting", "#position"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook provides a guide to write a job description for a specific position for your company.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Write_a_job_description.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Write_a_job_description.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "5b4533cb454ccc100d98e31d949ea6ba5d605e25d4f166a169bc1444facce745", "tool": "OpenAI", "notebook": "Write a press release", "action": "", "tags": ["#openai", "#pressrelease", "#writing", "#communication", "#publicrelations", "#journalism"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will provide a guide to write using OpenAI API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Write_a_press_release.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Write_a_press_release.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "96e1ff47c1c4011d1a31e25cba022771284016208eec7cdb625e49d2a326f65e", "tool": "OpenAI", "notebook": "Write a social media post", "action": "", "tags": ["#openai", "#socialmedia", "#post", "#prompt", "#tone", "#platform"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will create a prompt to write a social media post and be able to set the topic, the tone and the platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Write_a_social_media_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Write_a_social_media_post.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "77e886f6f04a14ced07e702a5722295c4ad6dd3ce080c11e25dd2f7d5cbc5874", "tool": "OpenAI", "notebook": "Write an outline", "action": "", "tags": ["#openai", "#outline", "#writing", "#topic", "#structure", "#organize"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will provide an outline for writing a specific topic. An outline is a structured plan or framework that serves as a blueprint for organizing and presenting information in a clear and logical way. Outlines can be used for a variety of purposes, such as organizing an essay or research paper, preparing a speech or presentation, or planning a project.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Write_an_outline.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Write_an_outline.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "29a4f52536d76475d169c74de659e2d0d3f557860ecc062b0374adbf28db05c2", "tool": "OpenAlex", "notebook": "Get lists of authors", "action": "", "tags": ["#openalex", "#api", "#entities", "#authors", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of authors from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_authors.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_authors.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "37dd53baf05766a23edd9b0c3d2efd0e35997d2ea98448c2649d27533c46348a", "tool": "OpenAlex", "notebook": "Get lists of concepts", "action": "", "tags": ["#openalex", "#api", "#entities", "#concepts", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of concepts from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_concepts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_concepts.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "0f7ad43306b5ffe0ac30096d2e74b67a4e2e968aba801e33bfb33de97dffc902", "tool": "OpenAlex", "notebook": "Get lists of funders", "action": "", "tags": ["#openalex", "#api", "#entities", "#funders", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of funders from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_funders.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_funders.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "daa55946917d46e91f745d8bb80015bb01c9b089f8d593cb295f068eba737713", "tool": "OpenAlex", "notebook": "Get lists of institutions", "action": "", "tags": ["#openalex", "#api", "#entities", "#institutions", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of institutions from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_institutions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_institutions.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "deac59c6ef3ad57a0c139099d6e1967888bf53c250eae9228230aacbcff5aa3e", "tool": "OpenAlex", "notebook": "Get lists of publishers", "action": "", "tags": ["#openalex", "#api", "#entities", "#publishers", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of publishers from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_publishers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_publishers.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "c7d44879bd6ddfd704a5edeea24d1aa2ad3f3a2f31e01e96559faa13274465b3", "tool": "OpenAlex", "notebook": "Get lists of sources", "action": "", "tags": ["#openalex", "#api", "#entities", "#sources", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of sources from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_sources.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_sources.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "c7d23e7145aa523f18b4b2d09a9c05ed3a857b0fc3a2fd9ad417256bed440d3c", "tool": "OpenAlex", "notebook": "Get lists of works", "action": "", "tags": ["#openalex", "#api", "#entities", "#works", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of works from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_works.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_works.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "4aba3ab8d023730a829408b7fa52a3ae14366326c9e47fa801a2384e5569c73d", "tool": "OpenBB", "notebook": "Create an kernel on Naas", "action": "", "tags": ["#openbb", "#naas", "#ipython", "#conda", "#kernel"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-01-11", "description": "This Jupyter Notebook will enable you to establish a new IPython Kernel that you can customize, allowing you to install any desired tools, here OpenBB. This kernel, once created, can be selected to run your notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenBB/OpenBB_Create_an_OpenBB_kernel_on_Naas.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenBB/OpenBB_Create_an_OpenBB_kernel_on_Naas.ipynb", "imports": [], "image_url": ""}, {"objectID": "bdebeee1fe5060091a5671ca9ea02112b9539ad2f8e26b584f668c3339c30745", "tool": "OpenPIV", "notebook": "Openpiv-python-template", "action": "", "tags": ["#piv", "#openpiv", "#fluidmechanics", "#openpiv-python"], "author": "Alex Liberzon", "author_url": "https://www.linkedin.com/in/alexliberzon/", "updated_at": "2023-04-12", "created_at": "2022-12-07", "description": "This notebook provides a template for using the open source Python library OpenPIV to analyze particle image velocimetry data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenPIV/openpiv-python-template.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenPIV/openpiv-python-template.ipynb", "imports": ["openpiv.tools, validation, filters, scaling, pyprocess", "numpy", "matplotlib.pyplot", "IPython.display.display", "ipywidgets.interact_manual, interactive, fixed, IntSlider, HBox, VBox, Layout", "openpiv.piv, tools", "ipywidgets.interact, interactive, fixed, interact_manual", "IPython.display.Image", "imageio", "skimage.img_as_uint"], "image_url": ""}, {"objectID": "84c4cccf44f66d7957f7c938252f5b5582637a13eed6818af52b2dbd038d582c", "tool": "OpenWeatherMap", "notebook": "Get City Weather", "action": "", "tags": ["#openweathermap", "#opendata", "#snippet", "#dataframe"], "author": "Christophe Blefari", "author_url": "https://www.linkedin.com/in/christopheblefari/", "updated_at": "2023-04-12", "created_at": "2021-07-21", "description": "This notebook provides an easy way to access current weather data for any city using the OpenWeatherMap API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenWeatherMap/OpenWeatherMap_Get_City_Weather.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenWeatherMap/OpenWeatherMap_Get_City_Weather.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "f4d4d561d540e27d1820edc3f73ffc5d3cffab1fb7d280c1c6fb8780c3804056", "tool": "OpenWeatherMap", "notebook": "Get City temperature weather-type wind-speed", "action": "", "tags": ["#openweathermap", "#opendata", "#snippet", "#dataframe"], "author": "Kanishk Pareek", "author_url": "https://in.linkedin.com/in/kanishkpareek", "updated_at": "2023-06-14", "created_at": "2022-10-06", "description": "This notebook helps to get the temperature and wind speed of your city by only giving the city as input.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenWeatherMap/OpenWeatherMap_Get_City_temperature_weather-type_wind-speed.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenWeatherMap/OpenWeatherMap_Get_City_temperature_weather-type_wind-speed.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "7ed1b4da0f14ddd2edc45c590983df0307cbbfe311cd4289de3e9d39765c6a41", "tool": "OpenWeatherMap", "notebook": "Send daily email with predictions", "action": "", "tags": ["#openweathermap", "#weather", "#plotly", "#prediction", "#email", "#naas_drivers", "#automation", "#opendata", "#analytics", "#ai", "#image", "#html", "#text"], "author": "Gautier Vivard", "author_url": "https://www.linkedin.com/in/gautier-vivard-1811b877/", "updated_at": "2023-04-12", "created_at": "2022-02-11", "description": "This notebook sends a daily email with weather predictions from OpenWeatherMap.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenWeatherMap/OpenWeatherMap_Send_daily_email_with_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenWeatherMap/OpenWeatherMap_Send_daily_email_with_predictions.ipynb", "imports": ["requests", "markdown2", "time", "pandas", "naas", "naas_drivers.plotly, prediction"], "image_url": ""}, {"objectID": "a01f17dcdd69a089120f8effd220d3a92241221e9c143270fe441934be4d8e67", "tool": "OwnCloud", "notebook": "Download file", "action": "", "tags": ["#owncloud", "#cloud", "#storage", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-08", "description": "This notebook allows users to download files from their OwnCloud account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OwnCloud/OwnCloud_Download_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OwnCloud/OwnCloud_Download_file.ipynb", "imports": ["naas", "owncloud"], "image_url": ""}, {"objectID": "80e640b22b8ac5254779988dbd2db06195ea2efa222ca5076c6cd225b76fb848", "tool": "OwnCloud", "notebook": "Upload file", "action": "", "tags": ["#owncloud", "#cloud", "#storage", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-08", "description": "This notebook allows users to securely upload files to their own personal cloud storage.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OwnCloud/OwnCloud_Upload_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OwnCloud/OwnCloud_Upload_file.ipynb", "imports": ["naas", "owncloud"], "image_url": ""}, {"objectID": "24264f1dc83845e25fdf023a95210e84987b196ef0a99dfd78a662d984443f96", "tool": "PDF", "notebook": "Extract Text from file", "action": "", "tags": ["#pdf", "#extract", "#snippet", "#operations", "#text"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-07-04", "created_at": "2022-10-03", "description": "This notebook extracts text from a PDF file in local or an URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PDF/PDF_Extract_Text_from_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PDF/PDF_Extract_Text_from_file.ipynb", "imports": ["io", "requests", "urllib.parse.urlparse", "urllib", "PyPDF2.PdfReader", "PyPDF2.PdfReader"], "image_url": ""}, {"objectID": "8bb6225a686349e47e170097cd65d15a077192613a84eeadafb1747d28342177", "tool": "PDF", "notebook": "Merge multiple documents", "action": "", "tags": ["#pdf", "#extract", "#snippet", "#operations", "#text"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-10-05", "description": "This notebook allows users to combine multiple PDF documents into a single file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PDF/PDF_Merge_multiple_PDF_documents.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PDF/PDF_Merge_multiple_PDF_documents.ipynb", "imports": ["io", "requests", "urllib.parse.urlparse", "PyPDF2.PdfFileReader, PdfFileWriter", "PyPDF2.PdfFileReader, PdfFileWriter"], "image_url": ""}, {"objectID": "260f8c6ceef5c7c165c4591bc6db22389b0eb540c849af035040ff3f31230c28", "tool": "PDF", "notebook": "Transform to MP3", "action": "", "tags": ["#pdf", "#text2audio", "#snippet", "#operations", "#mp3"], "author": "Sanjay Sabu", "author_url": "https://www.linkedin.com/in/sanjay-sabu-4205/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook converts PDF documents into MP3 audio files.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PDF/PDF_Transform_to_MP3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PDF/PDF_Transform_to_MP3.ipynb", "imports": ["io.StringIO", "pdfminer.converter.TextConverter", "pdfminer.layout.LAParams", "pdfminer.pdfdocument.PDFDocument", "pdfminer.pdfinterp.PDFResourceManager, PDFPageInterpreter", "pdfminer.pdfpage.PDFPage", "pdfminer.pdfparser.PDFParser", "gtts.gTTS"], "image_url": ""}, {"objectID": "5d27e3bd7fdfda696205d0e879b9a00e31ece1a64cae3c864ab22b006a0ab495", "tool": "Pandas", "notebook": "Apply custom styles on column", "action": "", "tags": ["#pandas", "#dataframe", "#style", "#column", "#apply", "#custom"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-25", "created_at": "2023-07-24", "description": "This notebook will show how to apply custom styles on a column of a Pandas DataFrame. It is usefull for data analysis and data visualization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Apply_custom_styles_on_column.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Apply_custom_styles_on_column.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "3f4e8e954fbc8a7f0e0ef3c8d8fc7e2296a180433067b08baee8d3258699f2fc", "tool": "Pandas", "notebook": "Check Columns type", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-11-29", "description": "This notebook checks columns in a dataframe. It could be very usefull to apply specific rules regarding columns format.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Check_Columns_type.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Check_Columns_type.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "1cdf0c27d04d84326ec48579541ee6ba9fb14172a2854e61231d11721984cea2", "tool": "Pandas", "notebook": "Check if column is in date format", "action": "", "tags": ["#pandas", "#dataframe", "#date", "#datetime", "#column", "#format"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-27", "created_at": "2023-06-13", "description": "This notebook will check if a column of a Pandas DataFrame is in date format. It is usefull for organizations to quickly check if a column is in the right format.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Check_if_column_is_in_date_format.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Check_if_column_is_in_date_format.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "01ec5aa3d067f1b4fe7b0e50d1a69fbffe59bb202fb9162ccdada4e82ef1174b", "tool": "Pandas", "notebook": "Concatenate dataframes", "action": "", "tags": ["#pandas", "#concatenate", "#dataframe", "#snippet", "#operations"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-30", "created_at": "2023-06-06", "description": "This notebook demonstrates how to concatenate dataframes across rows or columns using the Pandas library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Concatenate_dataframes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Concatenate_dataframes.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "3747b1ba5d9239ad75873c8918a7988f1253b0d87fe30db99b29078203d3fd2f", "tool": "Pandas", "notebook": "Convert datetime series", "action": "", "tags": ["#pandas", "#python", "#date", "#conversion", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2022-05-12", "description": "This notebook provides instructions on how to use the Pandas library to convert a datetime series into a usable format.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Convert_datetime_series.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Convert_datetime_series.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "9af61c9bfbaa205ab7a89d08fd076daa97551b36e768b0e2e388f71702a8d4e4", "tool": "Pandas", "notebook": "Create Pivot Table", "action": "", "tags": ["#pandas", "#pivot", "#operations", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-10-06", "description": "This notebook provides an example of how to use the Pandas library to create a pivot table.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Create_Pivot_Table.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Create_Pivot_Table.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "5dea1727d2325c2d39e0c97291eaad55fbaac39738b6f9870fcc25d9994de449", "tool": "Pandas", "notebook": "Create conditional column enrichment using DataFrame.loc", "action": "", "tags": ["#pandas", "#snippet", "#datenrichment", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-04", "created_at": "2023-06-04", "description": "This notebook demonstrates the practical application of `DataFrame.loc` for implementing conditions, enabling users to seamlessly enrich a DataFrame by generating new columns based on conditions derived from existing ones. Its versatility makes it an invaluable tool for DataFrame manipulation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Create_conditional_column_enrichment_using_DataFrame.loc.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Create_conditional_column_enrichment_using_DataFrame.loc.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "08aa6d5c2fcc85a4d1298f7c041485ceae994f6a8646b16f49dc3a1dd2c737c6", "tool": "Pandas", "notebook": "Create dataframe from dict", "action": "", "tags": ["#pandas", "#dict", "#snippet", "#dataframe", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-06-07", "created_at": "2022-03-07", "description": "This notebook provides a step-by-step guide to creating a dataframe from a dictionary using the Pandas library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Create_dataframe_from_dict.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Create_dataframe_from_dict.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "3b5664bbc6d912853acf24f4abd081bf5d0f7be6dc03b6c64adb8d2a0ef347af", "tool": "Pandas", "notebook": "Drop Columns By Index", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Sunny Chugh", "author_url": "https://www.linkedin.com/in/sunny-chugh-ab1630177/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook shows how to drop columns in Pandas DataFrame by index.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Drop_Columns_By_Index.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Drop_Columns_By_Index.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "9dc849f238938acd6d80c65a1dc602684a11c7650ba75ad919d1f36e183ceca1", "tool": "Pandas", "notebook": "Drop First column", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-11-28", "description": "This notebook shows how to drop First Column in Pandas DataFrame (3 Methods).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Drop_First_column.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Drop_First_column.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "10766514d077aaf045278657b7690bc7719fc6962cd9a47afe2312f1c3e9b91a", "tool": "Pandas", "notebook": "Drop columns", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook shows how to define a new DataFrame that drops columns defined in Input section.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Drop_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Drop_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "d6fb1e632b01ef9b6537987e8a40f196a59dbe2dc049961dbfaeeea7833d9f17", "tool": "Pandas", "notebook": "Drop duplicates", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Sunny Chugh", "author_url": "https://www.linkedin.com/in/sunny-chugh-ab1630177/", "updated_at": "2023-06-04", "created_at": "2023-06-04", "description": "This notebook shows how to drop duplicates in a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Drop_duplicates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Drop_duplicates.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "24261058569d9db319d5a70d1be2371ff1cc19b5b47bf391fdc996437e3d2506", "tool": "Pandas", "notebook": "Enforce data types to columns", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-04", "created_at": "2023-06-04", "description": "This notebook enforces specific data types to columns using Pandas, elevating your data consistency and accuracy. Availables types:\n- Numeric types: int, float, complex\n- Textual types: str\n- Date and time types: datetime, timedelta\n- Categorical types: category\n- Boolean type: bool\n- Object type: object", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Enforce_data_types_to_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Enforce_data_types_to_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "b412dd6032e5b39b130a8a012daaa8edda669ca6a9ff60187cdd86e1a8140a35", "tool": "Pandas", "notebook": "Fill emtpy values", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2022-11-29", "description": "This notebook fill empty values in dataframe columns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Fill_emtpy_values.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Fill_emtpy_values.ipynb", "imports": ["pandas", "numpy"], "image_url": ""}, {"objectID": "314b97f33ad0926c9bcdc4dd545c9bee424e648c6e041e35454f084d140fa51f", "tool": "Pandas", "notebook": "Filter DataFrame", "action": "", "tags": ["#pandas", "#dataframe", "#filter", "#python", "#dataanalysis"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-04", "created_at": "2023-03-02", "description": "This notebook will show how to filter a DataFrame using Pandas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Filter_DataFrame.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Filter_DataFrame.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "17af8c0029b88a375ce0ca2eada983c97f6d6c0f4bab83a36a524026cc5e74d4", "tool": "Pandas", "notebook": "Flatten MultiIndex Columns", "action": "", "tags": ["#pandas", "#dataframe", "#multiindex", "#flatten", "#columns"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook explains how to flatten a MultiIndex column in a Pandas DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Flatten_MultiIndex_Columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Flatten_MultiIndex_Columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "58c0be4a754b9695c5d1bb790222ff5c3d8426dc0fa876d1f948fce48d4730c5", "tool": "Pandas", "notebook": "Format URL as clickable link on column", "action": "", "tags": ["#pandas", "#dataframe", "#url", "#link", "#column", "#format"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook will show how to format a URL as a clickable link on a column of a Pandas DataFrame. This is usefull for organizations to quickly access to a website from a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Format_URL_as_clickable_link_on_column.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Format_URL_as_clickable_link_on_column.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "2ddb6eb54c1253c857cef66aeec26ee3d1fe3c61864951d3b23ca2dfda2f3cf6", "tool": "Pandas", "notebook": "Format number to string", "action": "", "tags": ["#pandas", "#dataframe", "#format", "#snippet", "#yahoofinance", "#naas_drivers", "#operations", "#jupyternotebooks"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an example of how to convert numerical values to strings using the Pandas library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Format_number_to_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Format_number_to_string.ipynb", "imports": ["naas_drivers.yahoofinance"], "image_url": ""}, {"objectID": "15c411f00d45474fa8f6c3e97c526d6e56dfd00b2dbebacafc15823ff5ea5618", "tool": "Pandas", "notebook": "Get n largest", "action": "", "tags": ["#pandas", "#dataframe", "#nlargest", "#python", "#data", "#analysis"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-14", "created_at": "2023-06-13", "description": "This notebook will demonstrate how to use the `nlargest` function in Pandas to get the n largest values from a DataFrame. This is useful for data analysis and data manipulation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Get_n_largest.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Get_n_largest.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "11148b2df16b8fc1df13c6aaa2928e94e1335bda5e3cb7410191d4772db14fc1", "tool": "Pandas", "notebook": "Get n smallest", "action": "", "tags": ["#pandas", "#dataframe", "#nsmallest", "#python", "#data", "#analysis"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-13", "created_at": "2023-06-13", "description": "This notebook explains how to use the `nsmallest` function from the Pandas library to get the n smallest values from column in a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Get_n_smallest.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Get_n_smallest.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "2f781b99d1e3e490fc5110f16be03119b1ab962d2b8ec93cfaf384332518ec74", "tool": "Pandas", "notebook": "Groupby and Aggregate", "action": "", "tags": ["#pandas", "#snippet", "#datamining", "#dataaggragation", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2022-11-30", "description": "This notebook groups and perform aggregation on columns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Groupby_and_Aggregate.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Groupby_and_Aggregate.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "bbc337a0d36c172e2e37ae7f50ffe79583936213893f036e3e538450012a1a46", "tool": "Pandas", "notebook": "ISO Date Conversion", "action": "", "tags": ["#pandas", "#python", "#date", "#conversion", "#isoformat", "#dateconversion", "#operations", "#snippet", "#dataframe"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-04-12", "created_at": "2021-10-06", "description": "This notebook provides a guide to converting ISO dates into Pandas-compatible formats.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_ISO_Date_Conversion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_ISO_Date_Conversion.ipynb", "imports": ["pandas", "dateutil.parser.parse"], "image_url": ""}, {"objectID": "dff9d7790f99b4c6981061774c7fcfc49b0814bc0b161ec88d96f69c857a6af2", "tool": "Pandas", "notebook": "Insert column", "action": "", "tags": ["#pandas", "#column", "#insert", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-04", "created_at": "2023-06-04", "description": "This notebook show how to insert column into DataFrame at specified location.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Insert_column.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Insert_column.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "c27a3508278911a39eefd92d7cbd38a4a34ff68c0ca048ad6a5871647f86af3d", "tool": "Pandas", "notebook": "Iterate over DataFrame rows", "action": "", "tags": ["#pandas", "#python", "#loops", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook demonstrates how to iterate over DataFrame rows as (index, Series) pairs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Iterate_over_DataFrame_rows.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Iterate_over_DataFrame_rows.ipynb", "imports": ["pandas", "numpy"], "image_url": ""}, {"objectID": "56f61acbe2bb3fb0a64d18a0d1d86efe024967f9d0f7640c21efbc6fab85d961", "tool": "Pandas", "notebook": "Iterate over DataFrame rows as namedtuples", "action": "", "tags": ["#pandas", "#python", "#loops", "#snippet", "#operations", "#namedtuples", "#dataframe"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-08", "created_at": "2023-06-07", "description": "This notebook demonstrates how to iterate over DataFrame rows as namedtuples", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Iterate_over_DataFrame_rows_as_namedtuples.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Iterate_over_DataFrame_rows_as_namedtuples.ipynb", "imports": ["pandas", "numpy", "collections.namedtuple"], "image_url": ""}, {"objectID": "66637c0e78b1cafa7d6ad81906a679a160528a45efad2fc436c804d12b40ca49", "tool": "Pandas", "notebook": "Keep columns", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook shows how to define a new DataFrame that only keeps columns defined in Input section.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Keep_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Keep_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "0b45752d1f47b9ea195133d22bb8a86066c2eb1baad4a0308a994c5a424e9fbc", "tool": "Pandas", "notebook": "Looping Over Dataframe", "action": "", "tags": ["#pandas", "#python", "#loops", "#dataframes", "#forloop", "#loop", "#snippet", "#operations"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-06-06", "created_at": "2021-10-07", "description": "This notebook provides an overview of multiples ways to use loops to iterate over a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Looping_Over_Dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Looping_Over_Dataframe.ipynb", "imports": ["pandas", "numpy"], "image_url": ""}, {"objectID": "4ad864c7c502f13639fafe2b968aa7346943bb6330ba7557259e9e431848adcc", "tool": "Pandas", "notebook": "Map column with values in dict", "action": "", "tags": ["#pandas", "#dict", "#map", "#series"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-08", "description": "This notebook shows how to map a column of a Pandas DataFrame with values from a dictionary.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Map_column_with_values_in_dict.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Map_column_with_values_in_dict.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "ea957a5f2454415ccc337c1c056b1e7a9e2cb345f786c1938a3ef0b4a434955e", "tool": "Pandas", "notebook": "Merge Dataframes", "action": "", "tags": ["#pandas", "#python", "#merging", "#merge", "#dataframes", "#consolidate", "#operations", "#snippet", "#dataframe"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-06-04", "created_at": "2021-10-07", "description": "This notebook provides an overview of how to use the Pandas library to merge two or more dataframes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Merge_Dataframes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Merge_Dataframes.ipynb", "imports": ["pandas", "numpy"], "image_url": ""}, {"objectID": "dfd4c9e70e3517613da38637dc496216b24dd65e6305d5edc6f1eae5d0172d6c", "tool": "Pandas", "notebook": "Pivot rows to columns", "action": "", "tags": ["#pandas", "#pivot", "#snippet", "#operations", "#utils", "#data"], "author": "Ismail Chihab", "author_url": "https://www.linkedin.com/in/ismail-chihab-4b0a04202/", "updated_at": "2023-04-12", "created_at": "2022-09-09", "description": "This notebook demonstrates how to use the Pandas library to transform data by pivoting rows into columns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Pivot_rows_to_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Pivot_rows_to_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "4932d57368797cb77d7866263669d24705499a09d49a57e4c15f334eba2cf2a1", "tool": "Pandas", "notebook": "Read CSV", "action": "", "tags": ["#pandas", "#csv", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook show how to read a CSV file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Read_CSV.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Read_CSV.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "de43d3c8b9aa8a86b8179624cf2d7dc2cfeb49e5c922858f7419de9daa6b2dc2", "tool": "Pandas", "notebook": "Read Excel", "action": "", "tags": ["#pandas", "#excel", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook show how to read a Excel file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Read_Excel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Read_Excel.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "846a0b00f4ab77df51ec9a47797b3a4440bb682426600b7a7a3b7b5fbdf0c652", "tool": "Pandas", "notebook": "Rename columns", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook renames columns in a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Rename_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Rename_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "5af9dafa2814c72a3b62ec58dbe2de6fc94c096c7cf3ec68e341701bed102914", "tool": "Pandas", "notebook": "Save dataframe to CSV", "action": "", "tags": ["#pandas", "#csv", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook show how to save a dataframe to a CSV file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Save_dataframe_to_CSV.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Save_dataframe_to_CSV.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "c2f8f6055e4d62602616107e3d9098ce962d1a64c169978495b1ffe2b51ac751", "tool": "Pandas", "notebook": "Save dataframe to Excel", "action": "", "tags": ["#pandas", "#excel", "#snippet", "#operation", "#dataframe", "#save"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-09", "created_at": "2023-06-07", "description": "This notebook show how to save a dataframe to Excel.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Save_dataframe_to_Excel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Save_dataframe_to_Excel.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "1d2d1155e7b45a7959095737ba4ecd08e96ffc02a72d097d5271eae4b71902a5", "tool": "Pandas", "notebook": "Sort values by multiples columns", "action": "", "tags": ["#pandas", "#dataframe", "#sort", "#columns", "#values", "#multiples"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-16", "created_at": "2023-06-13", "description": "This notebook will show how to sort values by multiples columns in Pandas. It is usefull for data analysis and data manipulation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Sort_values_by_multiples_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Sort_values_by_multiples_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "b27675b70ee0475d12381be158a83a7888089de73a76f6f28e4f4d3c1088bfad", "tool": "Pandas", "notebook": "Transform DataFrame to json file", "action": "", "tags": ["#pandas", "#dataframe", "#json", "#transform", "#file", "#dict", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-09", "created_at": "2023-05-09", "description": "This notebook will show how to transform a DataFrame into a json file. It is usefull for organizations that need to store data in a json format.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Transform_DataFrame_to_json_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Transform_DataFrame_to_json_file.ipynb", "imports": ["pandas", "json"], "image_url": ""}, {"objectID": "1961a79a86f4ee0ee0e0b29f136404431cb29587979223fe04ef6dec574cbc69", "tool": "Pandas", "notebook": "Transform Dataframe to dict", "action": "", "tags": ["#pandas", "#dataframe", "#dict", "#snippet", "#yahoofinance", "#naas_drivers", "#operations", "#jupyternotebooks"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-09", "created_at": "2023-05-09", "description": "This notebook provides an example of how to use the Pandas library to convert a dataframe into a dictionary.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Transform_Dataframe_to_dict.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Transform_Dataframe_to_dict.ipynb", "imports": ["naas_drivers.yahoofinance"], "image_url": ""}, {"objectID": "76ce3d48a02d92cc6ef4e068ea8883a5381c4583f32d993f672106b1f295be90", "tool": "Pandasql", "notebook": "Query CSV Using SQL", "action": "", "tags": ["#pandas", "#csv", "#snippet", "#read", "#dataframe", "#sql", "#pandasql", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2023-02-04", "description": "This notebook demonstrates how to use Pandasql to query CSV files as if they were relational databases, using SQL syntax. The aim is to provide an alternative to traditional Pandas methods for filtering, grouping, and aggregating data, and make it easier for users who are familiar with SQL to perform these tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandasql/Pandasql_Query_CSV_Using_SQL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandasql/Pandasql_Query_CSV_Using_SQL.ipynb", "imports": ["pandas", "pandasql.sqldf", "pandasql.sqldf"], "image_url": ""}, {"objectID": "bb199c1091a4a9f5a538365d093d290b3d47e406206122d2fbe8fec17af8ab0a", "tool": "Pandasql", "notebook": "Query Excel Using SQL", "action": "", "tags": ["#pandas", "#excel", "#snippet", "#read", "#dataframe", "#sql", "#pandasql", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2023-04-07", "description": "This notebook demonstrates how to use Pandasql to query Excel files as if they were relational databases, using SQL syntax. The aim is to provide an alternative to traditional Pandas methods for filtering, grouping, and aggregating data, and make it easier for users who are familiar with SQL to perform these tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandasql/Pandasql_Query_Excel_Using_SQL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandasql/Pandasql_Query_Excel_Using_SQL.ipynb", "imports": ["pandas", "pandasql.sqldf", "pandasql.sqldf"], "image_url": ""}, {"objectID": "6a9d3147aa50285ac5a92cd7539565be2378fdb41aea7a36da585c2187e03632", "tool": "Pandasql", "notebook": "Query Parquet Using SQL", "action": "", "tags": ["#pandas", "#parquet", "#snippet", "#read", "#dataframe", "#sql", "#pandasql", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2023-04-07", "description": "This notebook demonstrates how to use Pandasql to query Parquet files as if they were relational databases, using SQL syntax. The aim is to provide an alternative to traditional Pandas methods for filtering, grouping, and aggregating data, and make it easier for users who are familiar with SQL to perform these tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandasql/Pandasql_Query_Parquet_Using_SQL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandasql/Pandasql_Query_Parquet_Using_SQL.ipynb", "imports": ["pandas", "pandasql.sqldf", "pandasql.sqldf"], "image_url": ""}, {"objectID": "1f5b6f5d2d919274a737d5b13f4427d7cc779367fb8efffbd61ea6c7d767a2b0", "tool": "Panel", "notebook": "Create a kernel on Naas", "action": "", "tags": ["#panel", "#ipython", "#conda", "#naas", "#kernel"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-01-11", "description": "This Jupyter Notebook will enable you to establish a new IPython Kernel that you can customize, allowing you to install any desired tools. This kernel, once created, can be selected to run your notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Panel/Panel_Create_a_Panel_kernel_on_Naas.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Panel/Panel_Create_a_Panel_kernel_on_Naas.ipynb", "imports": [], "image_url": ""}, {"objectID": "43a2d5488f55091c2a69c598836fe3680e4003c3117c71b687912fc67b7611c0", "tool": "Pillow", "notebook": "Add data to image", "action": "", "tags": ["#pillow", "#opendata", "#snippet", "#data", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-04-19", "description": "This notebook demonstrates how to use the Pillow library to add data to an existing image.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pillow/Pillow_Add_data_to_image.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pillow/Pillow_Add_data_to_image.ipynb", "imports": ["PIL.Image, ImageDraw, ImageFont", "naas"], "image_url": ""}, {"objectID": "5ac6df900da4dc00365e842c34cceb80b361d19e824618b4b49ddc8275d355cf", "tool": "Pillow", "notebook": "Create indicator", "action": "", "tags": ["#pillow", "#opendata", "#snippet", "#data", "#image", "#indicator", "#kpi"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-12-06", "description": "This notebook creates an indicator with title and kpi using Pillow.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pillow/Pillow_Create_indicator.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pillow/Pillow_Create_indicator.ipynb", "imports": ["PIL.Image, ImageDraw, ImageFont", "urllib"], "image_url": ""}, {"objectID": "36a46b8dea31448e6c96ce86e134eb3596ca9606f23ba38d98c952a3bc8246b4", "tool": "Pillow", "notebook": "Create new image", "action": "", "tags": ["#pillow", "#opendata", "#snippet", "#data", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-12-06", "description": "This notebook creates and saves an image using Pillow. You can setup its width, height and background color.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pillow/Pillow_Create_new_image.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pillow/Pillow_Create_new_image.ipynb", "imports": ["PIL.Image"], "image_url": ""}, {"objectID": "ed2a0acd5f746906d09577c801960c8a21014484ac59e04b2875b57fad351e2c", "tool": "Pillow", "notebook": "Generate A Certificate Template", "action": "", "tags": ["#Pillow", "#Python", "#certificate-template", "#naas"], "author": "Suhas B", "author_url": "https://www.linkedin.com/in/suhasbrao/", "updated_at": "2023-04-12", "created_at": "2022-10-06", "description": "This notebook provides a template for generating a personalized certificate using the Pillow library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pillow/Pillow_Generate_A_Certificate_Template.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pillow/Pillow_Generate_A_Certificate_Template.ipynb", "imports": ["PIL.Image, ImageDraw, ImageFont", "requests", "io.BytesIO", "bs4.BeautifulSoup"], "image_url": ""}, {"objectID": "f67f0e92ee4940e9983e194e6375686842a22bcbc68eec6f4066e69b528aeaf0", "tool": "Pipedrive", "notebook": "Get contact", "action": "", "tags": ["#pipedrive", "#crm", "#contact", "#sales", "#snippet", "#dataframe"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2021-10-18", "description": "This notebook provides a way to quickly and easily get contact information from Pipedrive.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pipedrive/Pipedrive_Get_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pipedrive/Pipedrive_Get_contact.ipynb", "imports": ["pipedrive.client.Client", "pipedrive.client.Client", "pandas"], "image_url": ""}, {"objectID": "d6e7f95dbe41f7777d676406ded33033d8f4320cf952759eb61fc8638a3f7f28", "tool": "Plaid", "notebook": "Get accounts", "action": "", "tags": ["#plaid", "#bank", "#accounts", "#snippet", "#finance", "#dataframe"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides an easy way to access financial accounts and transactions through Plaid's API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plaid/Plaid_Get_accounts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plaid/Plaid_Get_accounts.ipynb", "imports": ["os", "plaid", "IPython.core.display", "uuid", "naas", "json", "pandas"], "image_url": ""}, {"objectID": "1c0a3c221963dae426dec4dcc8f110df19362ac20b1950d88159dcc05db17305", "tool": "Plaid", "notebook": "Get transactions", "action": "", "tags": ["#plaid", "#bank", "#transactions", "#snippet", "#finance", "#dataframe"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a guide to retrieving financial transaction data from Plaid.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plaid/Plaid_Get_transactions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plaid/Plaid_Get_transactions.ipynb", "imports": ["os", "plaid", "naas", "IPython.core.display", "uuid", "json"], "image_url": ""}, {"objectID": "8c98be6f5ca47cc8237544ca1fd6637230bb0e9ec0d7d55da7e49d0aa05cbe82", "tool": "Plotly", "notebook": "Create Balance Sheet Treemaps", "action": "", "tags": ["#plotly", "#treemap", "#snippet", "#dataviz", "#balancesheet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-31", "description": "This notebook displays Balance Sheet items into treemap graphs. In a balance sheet, treemap templates can be used to show the distribution of assets and liabilities. The assets can be divided into smaller categories such as cash, marketable securities, accounts receivable, and inventory, while the liabilities can be separated into categories like loans payable, bonds payable, and accounts payable. With a treemap, it is easy to see the relative proportions of each category, making it easier to identify any trends or patterns in the data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Balance_Sheet_Treemaps.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Balance_Sheet_Treemaps.ipynb", "imports": ["plotly.graph_objects", "plotly.subplots.make_subplots", "pandas", "naas"], "image_url": ""}, {"objectID": "c484ebf9f234ef9eee9185595ec6d6d402641b76aade153dd892444ef3b299c9", "tool": "Plotly", "notebook": "Create Barline chart", "action": "", "tags": ["#plotly", "#naas", "#snippet", "#operations", "#barline"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2022-05-26", "description": "This notebook provides instructions on how to create a barline chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Barline_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Barline_chart.ipynb", "imports": ["pandas", "plotly.graph_objects", "plotly.subplots.make_subplots", "naas"], "image_url": ""}, {"objectID": "f6d7102dbaeec65604e69539224a108362eacf8079a71cc0dbd46bf166fc0062", "tool": "Plotly", "notebook": "Create Bubblechart", "action": "", "tags": ["#plotly", "#chart", "#bubblechart", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a bubble chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Bubblechart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Bubblechart.ipynb", "imports": ["naas", "plotly.express", "pandas"], "image_url": ""}, {"objectID": "662519b80629a12be69f987f9d8875dddf515b461d05e9055158e24ff7fc2207", "tool": "Plotly", "notebook": "Create Bubblemap by City", "action": "", "tags": ["#plotly", "#bubblemap", "#city", "#python", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will show how to creates a bubblemap with values by city using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Bubblemap_by_City.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Bubblemap_by_City.ipynb", "imports": ["pandas", "plotly.express", "naas"], "image_url": ""}, {"objectID": "517e1dc7f83b92be09f8be6d565dc49f1b608178f833c7e3aa8b30f5b4687c7f", "tool": "Plotly", "notebook": "Create Candlestick", "action": "", "tags": ["#plotly", "#chart", "#candlestick", "#group", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an example of how to create a candlestick chart using the Plotly library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Candlestick.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Candlestick.ipynb", "imports": ["naas", "naas_drivers.yahoofinance", "plotly.graph_objects", "pandas"], "image_url": ""}, {"objectID": "d4631b09503ea4ffa69803e63b11d3c51800ee8a8468c962406c93f0398abbde", "tool": "Plotly", "notebook": "Create Gantt chart", "action": "", "tags": ["#plotly", "#chart", "#gant", "#project", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a Gantt chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Gantt_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Gantt_chart.ipynb", "imports": ["plotly.express", "pandas"], "image_url": ""}, {"objectID": "38ddb9935318bf5698eae5b352037f790c225ef788173972b6896f6f028a0814", "tool": "Plotly", "notebook": "Create Heatmap", "action": "", "tags": ["#plotly", "#chart", "#heatmap", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an example of how to create a heatmap using the Plotly library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Heatmap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Heatmap.ipynb", "imports": ["naas", "plotly.graph_objects", "plotly.express", "pandas"], "image_url": ""}, {"objectID": "f71d07001cfdc2d67718ef0fd91d6bcab1b1c98e043fdbf770d52276f6449f3b", "tool": "Plotly", "notebook": "Create Horizontal Barchart", "action": "", "tags": ["#plotly", "#chart", "#horizontalbar", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a horizontal bar chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Horizontal_Barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Horizontal_Barchart.ipynb", "imports": ["plotly.graph_objects"], "image_url": ""}, {"objectID": "363d1b3f489a134479cfec35ff780e213e571c9d2356959cc5daff21d5dea34a", "tool": "Plotly", "notebook": "Create Leaderboard", "action": "", "tags": ["#plotly", "#chart", "#horizontalbar", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an interactive way to visualize and compare data using Plotly to create a leaderboard.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Leaderboard.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Leaderboard.ipynb", "imports": ["plotly.express", "pandas"], "image_url": ""}, {"objectID": "a64b46ba602d154f700f434315aea461c9170c8f939d1062ae9277dd131941c8", "tool": "Plotly", "notebook": "Create Leaderboard stacked", "action": "", "tags": ["#plotly", "#chart", "#horizontalbar", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an example of how to create a leaderboard using Plotly's stacked bar chart visualization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Leaderboard_stacked.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Leaderboard_stacked.ipynb", "imports": ["plotly.express", "pandas"], "image_url": ""}, {"objectID": "e83171a9bd64008af6a5ea1e0510c738dc249f6741a28092160b5e3f3e8a68a9", "tool": "Plotly", "notebook": "Create Linechart", "action": "", "tags": ["#plotly", "#chart", "#linechart", "#trend", "#dataviz", "#yahoofinance", "#naas_drivers", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-11-23", "description": "This notebook provides instructions on how to create a line chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Linechart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Linechart.ipynb", "imports": ["naas", "naas_drivers.yahoofinance, plotly"], "image_url": ""}, {"objectID": "ae9899cd48c331274221a68cb0007765c4f1f79dbb8a197ffc9e19729393b3ff", "tool": "Plotly", "notebook": "Create Mapchart world", "action": "", "tags": ["#plotly", "#chart", "#worldmap", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides a step-by-step guide to creating an interactive mapchart of the world using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Mapchart_world.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Mapchart_world.ipynb", "imports": ["naas", "plotly.graph_objects", "pandas"], "image_url": ""}, {"objectID": "77b1042719f22bd7aec139151ff411e84fa83863e854fddce69e34042a4b90fa", "tool": "Plotly", "notebook": "Create Treemaps with plotly.express", "action": "", "tags": ["#plotly", "#treemap", "#snippet", "#dataviz", "#plotly.express", "#px"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-31", "description": "This notebook creates Treemaps with plotly.express. Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Treemaps_with_plotly.express.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Treemaps_with_plotly.express.ipynb", "imports": ["plotly.express", "numpy", "pandas", "naas"], "image_url": ""}, {"objectID": "33642dbaa758ab80c8d181a5e069bbd51c833d71d3f5b8802bd45cd6f7062ff9", "tool": "Plotly", "notebook": "Create Treemaps with plotly.graph objects", "action": "", "tags": ["#plotly", "#treemap", "#snippet", "#dataviz", "#plotly.graph_objects", "#go"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-31", "description": "This notebook creates Treemaps with plotly.graph_objects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Treemaps_with_plotly.graph_objects.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Treemaps_with_plotly.graph_objects.ipynb", "imports": ["plotly.graph_objects", "plotly.subplots.make_subplots", "numpy", "pandas", "naas"], "image_url": ""}, {"objectID": "63c55ffff60a0fc449fa140924c522ce65f38ad178f439c9bdd11f61817b50aa", "tool": "Plotly", "notebook": "Create Vertical Barchart", "action": "", "tags": ["#plotly", "#chart", "#verticalbarchart", "#group", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a vertical barchart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Vertical_Barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Vertical_Barchart.ipynb", "imports": ["naas", "plotly.graph_objects", "pandas"], "image_url": ""}, {"objectID": "f71af3953b75a90bc666f15072437705826d17bad8625bdc8561353a683b6931", "tool": "Plotly", "notebook": "Create Vertical Barchart group", "action": "", "tags": ["#plotly", "#chart", "#verticalbarchart", "#group", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a vertical barchart group using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Vertical_Barchart_group.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Vertical_Barchart_group.ipynb", "imports": ["naas", "plotly.graph_objects", "pandas"], "image_url": ""}, {"objectID": "ad519db0908de78d9d45a66e5b96a2682fe6b2a85fc2ea9410841cae78e0247a", "tool": "Plotly", "notebook": "Create Vertical Barchart stacked", "action": "", "tags": ["#plotly", "#chart", "#verticalbarchart", "#group", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a vertical barchart with stacked bars using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Vertical_Barchart_stacked.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Vertical_Barchart_stacked.ipynb", "imports": ["naas", "plotly.graph_objects", "pandas"], "image_url": ""}, {"objectID": "e90ce80fa0c56a2714a58552d3ca00e07d35d53d5d2a89216f1449170e347e6d", "tool": "Plotly", "notebook": "Create Waterfall chart", "action": "", "tags": ["#plotly", "#chart", "#warterfall", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a Waterfall chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Waterfall_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Waterfall_chart.ipynb", "imports": ["naas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "49ed2a1b8e8e4d090e53319021c0d31dff5664db5991ffdf6ec49d5620eec924", "tool": "Polars", "notebook": "Concatenate DataFrames", "action": "", "tags": ["#polars", "#dataframes", "#concatenate", "#python", "#pandas", "#data", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook explains how to concatenate DataFrames using Polars and Python. It is usefull for data analysis and data manipulation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Concatenate_DataFrames.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Concatenate_DataFrames.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "b0ec8cb4ccca4c7e92db03bd0282150b5301b49d4afd039cd3d6d134bc302247", "tool": "Polars", "notebook": "Create DataFrame", "action": "", "tags": ["#polars", "#dataframe", "#read", "#python", "#library", "#data", "#csv"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-06", "created_at": "2023-07-06", "description": "This notebook demonstrates how to create a DataFrame using `polars` library.\n\nAbout Polars:\n- `polars` is a Python library for data manipulation that is built on top of Rust's `Apache Arrow` and `DataFusion` projects.\n- It offers fast and efficient data processing and manipulation capabilities for large datasets, with a Pandas-like API and support for advanced data types.\n- `polars` is especially useful for data-intensive applications such as machine learning, data analysis, and data visualization, and can handle datasets that are too large to fit into memory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Create_DataFrame.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Create_DataFrame.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "5ad976a4ad2a8c89054f8c2676b823083a4ffa05d5d8803d3ad6164a6649f777", "tool": "Polars", "notebook": "Read CSV", "action": "", "tags": ["#polars", "#dataframe", "#read", "#python", "#library", "#data", "#csv"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2023-04-07", "description": "This notebook will demonstrate how to read a csv using the Polars library.\n\nAbout Polars:\n- `polars` is a Python library for data manipulation that is built on top of Rust's `Apache Arrow` and `DataFusion` projects.\n- It offers fast and efficient data processing and manipulation capabilities for large datasets, with a Pandas-like API and support for advanced data types.\n- `polars` is especially useful for data-intensive applications such as machine learning, data analysis, and data visualization, and can handle datasets that are too large to fit into memory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Read_CSV.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Read_CSV.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "3521a51627aded39438fb89161151234ff86772c86c9ffee7fd4cef55c3cac79", "tool": "Polars", "notebook": "Select columns", "action": "", "tags": ["#polars", "#dataframe", "#read", "#python", "#library", "#data", "#csv"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-06", "created_at": "2023-07-06", "description": "This notebook demonstrates how to select columns in a DataFrame using `polars` library.\n\nAbout Polars:\n- `polars` is a Python library for data manipulation that is built on top of Rust's `Apache Arrow` and `DataFusion` projects.\n- It offers fast and efficient data processing and manipulation capabilities for large datasets, with a Pandas-like API and support for advanced data types.\n- `polars` is especially useful for data-intensive applications such as machine learning, data analysis, and data visualization, and can handle datasets that are too large to fit into memory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Select_Columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Select_Columns.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "fa25e3ec1012dad1c63aeda4b86a6f93f308c4643b6260611d01662a65f294e7", "tool": "Polars", "notebook": "Select rows", "action": "", "tags": ["#polars", "#dataframe", "#read", "#python", "#library", "#data", "#csv"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-06", "created_at": "2023-07-06", "description": "This notebook demonstrates how to select rows in a DataFrame using `polars` library.\n\nAbout Polars:\n- `polars` is a Python library for data manipulation that is built on top of Rust's `Apache Arrow` and `DataFusion` projects.\n- It offers fast and efficient data processing and manipulation capabilities for large datasets, with a Pandas-like API and support for advanced data types.\n- `polars` is especially useful for data-intensive applications such as machine learning, data analysis, and data visualization, and can handle datasets that are too large to fit into memory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Select_Rows.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Select_Rows.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "7a9f09587076ee0c3192e964f346d57f656558be530916d518954ff4dcf37679", "tool": "Polars", "notebook": "Select both rows and columns", "action": "", "tags": ["#polars", "#dataframe", "#read", "#python", "#library", "#data", "#csv"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-06", "created_at": "2023-07-06", "description": "This notebook demonstrates how to select columns, rows, and both columns and rows at once in a DataFrame using `polars` library.\n\nAbout Polars:\n- `polars` is a Python library for data manipulation that is built on top of Rust's `Apache Arrow` and `DataFusion` projects.\n- It offers fast and efficient data processing and manipulation capabilities for large datasets, with a Pandas-like API and support for advanced data types.\n- `polars` is especially useful for data-intensive applications such as machine learning, data analysis, and data visualization, and can handle datasets that are too large to fit into memory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Select_Rows_and_Columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Select_Rows_and_Columns.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "228a81ed357d309e1ec921bcacf182615172dd1fabda1a70ac76cc2403589444", "tool": "PostgresSQL", "notebook": "Get data from database", "action": "", "tags": ["#postgressql", "#database", "#operations", "#snippet", "#dataframe"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-05-02", "description": "This notebook provides instructions on how to query a PostgreSQL database and retrieve data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PostgresSQL/PostgresSQL_Get_data_from_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PostgresSQL/PostgresSQL_Get_data_from_database.ipynb", "imports": ["psycopg2", "psycopg2", "pandas", "naas"], "image_url": ""}, {"objectID": "d407f6c7c08a81f0c5871257274d21d6b1ca36d44fdb2483cc0caab78c998412", "tool": "PowerPoint", "notebook": "Add Slide With Image", "action": "", "tags": ["#powerpoint", "#slide", "#portrait", "#pptx", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-30", "description": "This notebook provides instructions on how to add an image to a PowerPoint slide.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Add_Slide_With_Image.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Add_Slide_With_Image.ipynb", "imports": ["pptx.Presentation", "pptx.Presentation", "pptx.util.Inches"], "image_url": ""}, {"objectID": "85d11fb04a9f5d15ba18c7cad27cc4241d0cbb163c4d27551bec621c5896932d", "tool": "PowerPoint", "notebook": "Add Slide With Textbox", "action": "", "tags": ["#powerpoint", "#slide", "#portrait", "#pptx", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-30", "description": "This notebook allows users to create a new slide in PowerPoint with a textbox.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Add_Slide_With_Textbox.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Add_Slide_With_Textbox.ipynb", "imports": ["pptx.Presentation", "pptx.Presentation", "pptx.util.Inches, Pt"], "image_url": ""}, {"objectID": "e3d8e2acd0d06ddfb9d30c2f126b22ec639ec52fb578e2bf890674239ab7e4b6", "tool": "PowerPoint", "notebook": "Add Slide With Title Subtitle", "action": "", "tags": ["#powerpoint", "#slide", "#portrait", "#pptx", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-30", "description": "This notebook allows users to quickly and easily create a new slide in PowerPoint with a title and subtitle.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Add_Slide_With_Title_Subtitle.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Add_Slide_With_Title_Subtitle.ipynb", "imports": ["pptx.Presentation", "pptx.Presentation", "pptx.util.Inches"], "image_url": ""}, {"objectID": "f8ca7d5fbaed2f83b5a5b90bfd54a5d9965f635427725abef04601fc7c340129", "tool": "PowerPoint", "notebook": "Add title + line in presentation", "action": "", "tags": ["#powerpoint", "#naas", "#python", "#python_pptx"], "author": "Ayoub Berdeddouch", "author_url": "https://www.linkedin.com/in/ayoub-berdeddouch", "updated_at": "2023-04-12", "created_at": "2022-11-01", "description": "This notebook Adds a title + Line to a presentation in PowerPoint", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Add_title_%2B_line_in_presentation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Add_title_%2B_line_in_presentation.ipynb", "imports": ["pptx.Presentation", "pptx.enum.shapes.MSO_CONNECTOR", "pptx.util.Inches"], "image_url": ""}, {"objectID": "4944a903bfe77005932df44840be3cc20f84adb51aa8fc7a18eb411e04aef75a", "tool": "PowerPoint", "notebook": "Create Presentation", "action": "", "tags": ["#powerpoint", "#naas", "#python", "#pythonpptx", "#asset", "#snippet", "#operations", "#slide", "#microsoft"], "author": "Ayoub Berdeddouch", "author_url": "https://www.linkedin.com/in/ayoub-berdeddouch", "updated_at": "2023-04-12", "created_at": "2022-10-23", "description": "This notebook creates a PowerPoint presentation with a cover page, 3 pages with graphs and text and a last page.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Create_Presentation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Create_Presentation.ipynb", "imports": ["pptx.Presentation", "pptx.enum.shapes.MSO_SHAPE", "pptx.dml.color.RGBColor", "pptx.util.Inches, Pt", "pptx.enum.dml.MSO_THEME_COLOR", "pptx.chart.data.CategoryChartData", "pptx.enum.chart.XL_CHART_TYPE", "pptx.chart.data.ChartData", "pptx.util.Inches", "numpy", "datetime", "requests", "plotly.graph_objects", "pandas", "naas"], "image_url": ""}, {"objectID": "87b9a5c96c8ceccefe39e7dbb996c586cdd15f07b0317200b63be92aeb8d3281", "tool": "PowerPoint", "notebook": "Set portrait format", "action": "", "tags": ["#powerpoint", "#slide", "#portrait", "#pptx", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-30", "description": "This notebook allows you to easily set the portrait format for your PowerPoint presentation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Set_portrait_format.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Set_portrait_format.ipynb", "imports": ["pptx.Presentation", "pptx.Presentation", "pptx.util.Inches"], "image_url": ""}, {"objectID": "6dc53ab8a25919a7cd0c364aec804a3e259bce5341b0ac2694bc44c4cc19ff65", "tool": "PyCaret", "notebook": "Automl classification", "action": "", "tags": ["#automl", "#pandas", "#snippet", "#classification", "#dataframe", "#visualize", "#pycaret", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-05-28", "description": "This notebook demonstrates how to use PyCaret to quickly and easily build and evaluate machine learning models for classification tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PyCaret/PyCaret_automl_classification.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PyCaret/PyCaret_automl_classification.ipynb", "imports": ["pandas", "pycaret.classification.setup, compare_models, evaluate_model, predict_model, finalize_model, \\", "pycaret.classification.setup, compare_models, evaluate_model, predict_model, finalize_model, \\"], "image_url": ""}, {"objectID": "7836b18a1acc436173deeed60d42ff7bd8ddf36559c8275931e2ec346a0b7087", "tool": "PyCaret", "notebook": "Automl regression", "action": "", "tags": ["#automl", "#pandas", "#snippet", "#regression", "#dataframe", "#visualize", "#pycaret", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-05-28", "description": "This notebook demonstrates how to use PyCaret's automated machine learning capabilities to perform regression tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PyCaret/PyCaret_automl_regression.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PyCaret/PyCaret_automl_regression.ipynb", "imports": ["pandas", "pycaret.regression.setup, compare_models, evaluate_model, predict_model, finalize_model, \\", "pycaret.regression.setup, compare_models, evaluate_model, predict_model, finalize_model, \\"], "image_url": ""}, {"objectID": "47b1d63eba6e37dd5d1ed7fe4be46bb37f6914de53819f21fadae86a6f19acdf", "tool": "PyGWalker", "notebook": "Analyze Pandas dataframe", "action": "", "tags": ["#pandas", "#dataframe", "#tableau", "#pygwalker", "#analyze", "#jupyter"], "author": "Abraham Israel", "author_url": "https://www.linkedin.com/in/abraham-israel/", "updated_at": "2023-04-12", "created_at": "2023-03-07", "description": "This notebook will demonstrate how to analyze a Pandas dataframe in Jupyter using a Tableau-style interface.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PyGWalker/PyGWalker_Analyze_Pandas_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PyGWalker/PyGWalker_Analyze_Pandas_dataframe.ipynb", "imports": ["pandas", "numpy", "pygwalker", "pygwalker"], "image_url": ""}, {"objectID": "8da37e2aaf56e0b26e7ee696dc16f492d45a2e204454444b107880aac4b15824", "tool": "PyPI", "notebook": "- Get number of downloads any package", "action": "", "tags": ["#pypi", "#downloads", "#package", "#operations", "#analytics", "#plotly", "#html", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-27", "description": "This notebook provides a way to retrieve the download count of any package from the Python Package Index (PyPI).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PyPI/PyPI_Get_number_of_downloads_any_package.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PyPI/PyPI_Get_number_of_downloads_any_package.ipynb", "imports": ["pypistats", "pypistats", "pprint.pprint", "datetime.datetime", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "5b61a4c4382b4f68bdf9dd662ae75f7e84c36a567a9eabf26257aa87cf5c4046", "tool": "PyPI", "notebook": "Get release dates from package", "action": "", "tags": ["#pypi", "#downloads", "#package", "#operations", "#analytics", "#plotly", "#html", "#csv", "#image", "#png"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook get the release dates a package from the Python Package Index (PyPI) and plot a Barchart and Scatter Plot to display the release by month. \n\nNB: We have noticed that sometimes not all versions are accessible via this endpoint in comparison with the website. Please let us know if you manage to find a solution to this issue, we would appreciate.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PyPI/PyPI_Get_release_dates_from_package.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PyPI/PyPI_Get_release_dates_from_package.ipynb", "imports": ["requests", "numpy", "matplotlib.pyplot", "matplotlib.dates", "dateutil.parser.parse"], "image_url": ""}, {"objectID": "f4efb27c8503f52f1198dec50fc0602cc6147fa541b8869da617593b6cf6e43c", "tool": "Python", "notebook": "Calculate the percentage of similarity between two strings", "action": "", "tags": ["#python", "#string", "#similarity", "#calculate", "#percentage", "#compare"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-28", "created_at": "2023-08-28", "description": "This notebook calculates the percentage of similarity between two strings and is usefull for organizations to compare two strings and measure their similarity.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Calculate_the_percentage_of_similarity_between_two_strings.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Calculate_the_percentage_of_similarity_between_two_strings.ipynb", "imports": ["difflib.SequenceMatcher"], "image_url": ""}, {"objectID": "1285d5b317f4b36ebfc42542b8f98c906a4c3ea71f825078f09766ea31bc076e", "tool": "Python", "notebook": "Check if string is number", "action": "", "tags": ["#python", "#string", "#number", "#check", "#isnumber", "#function"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook will check if a string is a number and how it is useful for organizations. It will help to identify if a string is a number or not.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Check_if_string_is_number.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Check_if_string_is_number.ipynb", "imports": ["string"], "image_url": ""}, {"objectID": "03bc3ba50473a4aff2cfca6b15c26f19dd51443a7e99da17d33864435520c19e", "tool": "Python", "notebook": "Clean your download folder", "action": "", "tags": ["#python", "#automation", "#clean_folder"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-04-12", "created_at": "2023-04-01", "description": "This notebook will go through your given folder and check each file last modification time, and if it's been more than 30 days it will move those file to new folder 'files_to_delete'", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Clean_your_download_folder.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Clean_your_download_folder.ipynb", "imports": ["os", "shutil", "datetime.datetime, timedelta"], "image_url": ""}, {"objectID": "6803ffcd1c5475d13f4ef26dd7761f41d317f9a20677f2e8e30352537c2c9cf5", "tool": "Python", "notebook": "Compress images", "action": "", "tags": ["#python", "#PIL", "#images", "#compress"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-05-23", "created_at": "2023-05-23", "description": "This notebook uses PIL library to compress the image.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Compress_images.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Compress_images.ipynb", "imports": ["PIL.Image", "PIL.Image", "os", "requests"], "image_url": ""}, {"objectID": "ccf490cb6569994548b9c95421373ae1e94bb10fa7fb61dadd3576a073277f1d", "tool": "Python", "notebook": "Consolidate Excel files", "action": "", "tags": ["#python", "#consolidate", "#files", "#productivity", "#snippet", "#operations", "#excel"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-10-07", "description": "The objective of this notebook is to consolidate multiple Excel files (.xlsx) into one.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Consolidate_Excel_files.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Consolidate_Excel_files.ipynb", "imports": ["os", "pandas"], "image_url": ""}, {"objectID": "d41e9d952be285475cb26b5226195474cd7ba62ace4f711fe492d5f79b7ba97c", "tool": "Python", "notebook": "Convert CSV to Excel", "action": "", "tags": ["#python", "#csv", "#excel", "#pandas", "#file"], "author": "Sophia Iroegbu", "author_url": "www.linkedin.com/in/sophia-iroegbu", "updated_at": "2023-04-12", "created_at": "2022-10-10", "description": "This notebook provides a step-by-step guide to converting CSV files to Excel spreadsheets using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_CSV_to_Excel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_CSV_to_Excel.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "5b5dee3ead8fd96908827f51ac99cb0b72b7dbfc37239147e2dfb6feba7426ef", "tool": "Python", "notebook": "Convert degrees-minutes-seconds to decimal degrees", "action": "", "tags": ["#python", "#geopy", "#snippet", "#navigation"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook shows how to convert degrees-minutes-seconds to decimal degrees. Converting coordinates from Degrees, Minutes, and Seconds (DMS) to decimal degrees can be useful for compatibility with modern systems that use decimal format. It also simplifies calculations and data processing, as working with decimal numbers is often easier and more straightforward than working with degrees, minutes, and seconds.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_DMS_to_decimal_degrees.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_DMS_to_decimal_degrees.ipynb", "imports": [], "image_url": ""}, {"objectID": "0069c1c7add214fdd2655b1fa2238a2f17d761feb5403f7dfeb95c27114911eb", "tool": "Python", "notebook": "Convert PNG Images To JPG", "action": "", "tags": ["#jpg", "#png", "#to", "#image", "#images", "#convert"], "author": "Ahmed Mousa", "author_url": "https://www.linkedin.com/in/akmousa/", "updated_at": "2023-04-12", "created_at": "2022-11-10", "description": "This notebook converts png images to jpg images.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_PNG_Images_To_JPG.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_PNG_Images_To_JPG.ipynb", "imports": ["PIL.Image"], "image_url": ""}, {"objectID": "ea5c6ad4046dea2b3a2e3f412203b3899b9f88cffa458917a9b828ee0b6dd11b", "tool": "Python", "notebook": "Convert URL to string", "action": "", "tags": ["#python", "#urllib", "#string", "#url", "#convert", "#library"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook will show how to convert a URL to a string using urllib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_URL_to_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_URL_to_string.ipynb", "imports": ["urllib.parse"], "image_url": ""}, {"objectID": "bb57377a72ad818450b8065fe617392e959e8c11b27e830a1548a57af32e054c", "tool": "Python", "notebook": "Convert audiofile from wav to mp3", "action": "", "tags": ["#python", "#audio", "#wavtomp3", "#pydub"], "author": "Mohit Singh", "author_url": "", "updated_at": "2023-04-12", "created_at": "2023-03-08", "description": "This notebook uses the Pydub library to convert audio file from wav to mp3.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_audiofile_from_wav_to_mp3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_audiofile_from_wav_to_mp3.ipynb", "imports": ["os", "pydub.AudioSegment", "pydub.AudioSegment", "requests"], "image_url": ""}, {"objectID": "efc49f04ec827f01ebc298a6468803093908ebcaa46a2f7fcd8353cf67289731", "tool": "Python", "notebook": "Convert coordinates to degrees-minutes-seconds", "action": "", "tags": ["#python", "#geopy", "#snippet", "#navigation"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook shows how to convert coordinates to to Degrees, Minutes, and Seconds (DMS). Converting coordinates to Degrees, Minutes, and Seconds (DMS) can be beneficial for compatibility with systems that use DMS as their standard format. It can also improve precision in fields like surveying or navigation, where accurate measurements are crucial.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_coordinates_to_DMS.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_coordinates_to_DMS.ipynb", "imports": [], "image_url": ""}, {"objectID": "1b0f742b14019f6471df8b63da4b92c06192acbe92d849987e62afafb2dac907", "tool": "Python", "notebook": "Convert currency", "action": "", "tags": ["#python", "#exchange", "#currency", "#converter", "#convert", "#snippet", "#operations"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-19", "created_at": "2023-06-19", "description": "This workbook shows you how to convert any currency into any other currency in real time using `forex_python` library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_currency.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_currency.ipynb", "imports": ["forex_python.converter.CurrencyRates", "forex_python.converter.CurrencyRates"], "image_url": ""}, {"objectID": "30b65ea2617db409e1fba9cc5ff0c4b258e5a8e58ebde18fe4ff5314a177810e", "tool": "Python", "notebook": "Convert length", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#length"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert length using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_length.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_length.ipynb", "imports": [], "image_url": ""}, {"objectID": "a16c1298d415f1c4c24ae79bf540d33cbde9150d81bae2d196bbbba37a742116", "tool": "Python", "notebook": "Convert speed", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#speed"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert speed using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_speed.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_speed.ipynb", "imports": [], "image_url": ""}, {"objectID": "c3b9f65c829ea7dd7c8fe689d18199671b582c28e65ca5ab0544da17e9566633", "tool": "Python", "notebook": "Convert string boolean to boolean", "action": "", "tags": ["#python", "#string", "#boolean", "#convert", "#type", "#data"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook will show how to convert a string boolean to a boolean type in Python. It is usefull for data cleaning and data manipulation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_string_boolean_to_boolean.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_string_boolean_to_boolean.ipynb", "imports": ["ast"], "image_url": ""}, {"objectID": "8dacf09e80d19c288d77ccdf43ba69339901ed23a093c040857e1e6abdc05eee", "tool": "Python", "notebook": "Convert string to URL", "action": "", "tags": ["#python", "#urllib", "#string", "#url", "#convert", "#library"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook will show how to convert a string to a URL using urllib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_string_to_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_string_to_URL.ipynb", "imports": ["urllib.parse"], "image_url": ""}, {"objectID": "067b3975c0bfb9d91f586f52bc48f9b131588dccf939568abb539de93f96b308", "tool": "Python", "notebook": "Convert temperature", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#temperature"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert units temperature using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_temperature.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_temperature.ipynb", "imports": [], "image_url": ""}, {"objectID": "56b5020fb5de6bd618fd2b48c7fdf5e338135bbc4cb8b7a39b8a847fdabf45a3", "tool": "Python", "notebook": "Convert time", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#time"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert time using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_time.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_time.ipynb", "imports": [], "image_url": ""}, {"objectID": "03791db2779f73d9044c86f3b1f51a2f2c9b4343f9717fd1e2ccf0aa65da85c6", "tool": "Python", "notebook": "Convert time delta to months", "action": "", "tags": ["#python", "#datetime", "#timedelta", "#calculate", "#date", "#time"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-22", "created_at": "2023-05-22", "description": "This notebook convert the time delta between two dates to months.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_time_delta_to_months.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_time_delta_to_months.ipynb", "imports": ["datetime.datetime"], "image_url": ""}, {"objectID": "e124d5cbb19b3fbe5b868dcf46bb16fa5e5b8c2d1caf34e712fd11ce10360bf5", "tool": "Python", "notebook": "Convert units", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#length", "#temperature", "#weight", "#time", "#volume", "#speed"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-19", "created_at": "2023-06-19", "description": "This notebook shows you how to convert units (length, temperature, weight, time, volume, speed) using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_units.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_units.ipynb", "imports": [], "image_url": ""}, {"objectID": "7b235c7c8db12861213c775e7d7ae25d6d24f1ab8ef535cb438e651f2e7a2d47", "tool": "Python", "notebook": "Convert volume", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#volume"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert volume using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_volume.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_volume.ipynb", "imports": [], "image_url": ""}, {"objectID": "f5e386585bbd320a3d0dde509039baec9d255f0945b148fba09d94b400642d56", "tool": "Python", "notebook": "Convert weight", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#weight"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert weight using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_weight.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_weight.ipynb", "imports": [], "image_url": ""}, {"objectID": "8b78cb9c1482a8aa5d796c3cb0084b2af3a3e9efaeebeb65de5a5c82143af234", "tool": "Python", "notebook": "Copy files and subdir from directory to another directory", "action": "", "tags": ["#python", "#os", "#shutil", "#operations", "#snippet"], "author": "Parth Panchal", "author_url": "https://www.linkedin.com/in/parthpanchal8401/", "updated_at": "2023-04-12", "created_at": "2022-10-14", "description": "This notebook provides a Python script to copy files and subdirectories from one directory to another.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Copy_files_and_subdir_from_directory_to_another_directory.ipynb.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Copy_files_and_subdir_from_directory_to_another_directory.ipynb.ipynb", "imports": ["shutil", "os"], "image_url": ""}, {"objectID": "7a22581a89abec8e9064d61cbe041eb2714389315534606904bb777e73f3eb7b", "tool": "Python", "notebook": "Create Email Combination with Firstname Lastname Domain address", "action": "", "tags": ["#python", "#email", "#combination", "#firstname", "#lastname", "#domain", "#sales", "#prospect"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-27", "description": "This notebook will create a list of emails combination with firstname, lastname and domain address. This notebook can be used to find and test an email address for a prospect.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Create_Email_Combination_with_Firstname_Lastname_Domain_address.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Create_Email_Combination_with_Firstname_Lastname_Domain_address.ipynb", "imports": [], "image_url": ""}, {"objectID": "287f76fafc85efc85412756d89bbbcfe44730e5f2bb38149ac0374522f23c2dd", "tool": "Python", "notebook": "Create Strong Random Password", "action": "", "tags": ["#python", "#password", "#random", "#snippet", "#operations"], "author": "Sunny", "author_url": "https://www.linkedin.com/in/sunny-chugh-ab1630177/", "updated_at": "2023-04-12", "created_at": "2022-11-30", "description": "The objective of this notebook is to Create Strong random password.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Create_Strong_Random_Password.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Create_Strong_Random_Password.ipynb", "imports": ["random", "string"], "image_url": ""}, {"objectID": "dc2e29332347a26e140e365029573d514acb1dae172eb15ce21ad5c557bba2c6", "tool": "Python", "notebook": "Create dataframe from lists", "action": "", "tags": ["#python", "#list", "#dataframe", "#snippet", "#pandas", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to use Python to create a dataframe from lists.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Create_dataframe_from_lists.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Create_dataframe_from_lists.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "d7d863424921d5fede902600607bd28d9bf4753d1c27af768c5b35cc1d1abe0c", "tool": "Python", "notebook": "Create dict from lists", "action": "", "tags": ["#python", "#list", "#dict", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a dictionary from two lists in Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Create_dict_from_lists.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Create_dict_from_lists.ipynb", "imports": [], "image_url": ""}, {"objectID": "03afcf02c7e061c5c2deb5f4d6cd7467b149399644cb1bba64ea2e36dd15f196", "tool": "Python", "notebook": "Delete entire directory tree", "action": "", "tags": ["#python", "#shutil", "#delete", "#folder", "#file", "#directory"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-26", "created_at": "2023-04-26", "description": "This notebook will show how to delete an entire directory tree using the shutil library. \n\nShutil module in Python provides many functions of high-level operations on files and collections of files. It comes under Python\u2019s standard utility modules. This module helps in automating the process of copying and removal of files and directories. \n\n`shutil.rmtree()` is used to delete an entire directory tree, path must point to a directory (but not a symbolic link to a directory).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Delete_entire_directory_tree.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Delete_entire_directory_tree.ipynb", "imports": ["shutil"], "image_url": ""}, {"objectID": "7a281dea954ab667015391ddacef8e3c6f808fa79c747bb70d288124ffbdd5cb", "tool": "Python", "notebook": "Download Image from URL", "action": "", "tags": ["#python", "#image", "#url", "#naas", "#snippet"], "author": "Abraham Israel", "author_url": "https://www.linkedin.com/in/abraham-israel/", "updated_at": "2023-07-03", "created_at": "2022-10-09", "description": "This notebook demonstrates how to download an image from a URL using Python and `wget` library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Download_Image_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Download_Image_from_URL.ipynb", "imports": ["wget", "wget", "IPython.display.Image"], "image_url": ""}, {"objectID": "872420f12cee8df45fe4b26b0fd0b0626f804e3babb46767478343b72b8a9577", "tool": "Python", "notebook": "Download PDF from URL", "action": "", "tags": ["#python", "#pdf", "#snippet", "#url", "#naas", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-04-29", "description": "This notebook provides a step-by-step guide to downloading a PDF file from a URL using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Download_PDF_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Download_PDF_from_URL.ipynb", "imports": ["urllib"], "image_url": ""}, {"objectID": "957c6b7099115e2ae404fdeea269f27e570a97ae941a603faad6a55502ce016f", "tool": "Python", "notebook": "Download ZIP from URL", "action": "", "tags": ["#python", "#urllib", "#download", "#zip", "#url", "#request"], "author": "Hamid Mukhtar", "author_url": "https://www.linkedin.com/in/mukhtar-hamid/", "updated_at": "2023-05-04", "created_at": "2023-04-11", "description": "This notebook will show how to download a ZIP file from a URL using urllib.request.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Download_ZIP_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Download_ZIP_from_URL.ipynb", "imports": ["os", "shutil", "urllib"], "image_url": ""}, {"objectID": "4c668b1964bb6e1a96dfe7a4ae9cfd6e4a9054a13f2852badfef2a5f5cc31077", "tool": "Python", "notebook": "Download audio file from URL", "action": "", "tags": ["#python", "#download", "#snippet", "#url", "#naas", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-23", "created_at": "2023-07-23", "description": "This notebook demonstrates how to download audio file from an URL using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Download_audio_file_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Download_audio_file_from_URL.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "aed246dedce0dfc3440f08d081ff16e62e1dda1fd1cc0b6c5f39b88ea8617e89", "tool": "Python", "notebook": "Explore Dataset with Pivot Table", "action": "", "tags": ["#python", "#dataset", "#pivottable", "#dataexploration"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2023-01-30", "description": "This notebook allows you to interactively explore and analyze a dataset using a pivot table. It uses the `pivottablejs` library to generate a dynamic pivot table in your web browser, giving you the ability to sort, filter, and aggregate data in real-time. This template provides a simple and intuitive way to explore and gain insights from your dataset, making it a valuable tool for data analysis and visualization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Explore_Dataset_with_Pivot_Table.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Explore_Dataset_with_Pivot_Table.ipynb", "imports": ["pandas", "pivottablejs.pivot_ui", "pivottablejs.pivot_ui"], "image_url": ""}, {"objectID": "4d33b51aeb8bff0d6e56610f53de035ed263c78d3f2399eaee3990e4ccac4b85", "tool": "Python", "notebook": "Extract characters from string", "action": "", "tags": ["#python", "#extract", "#string", "#character"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-13", "created_at": "2023-06-08", "description": "This notebook will show how to extract characters from a string.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Extract_characters_from_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Extract_characters_from_string.ipynb", "imports": [], "image_url": ""}, {"objectID": "f0ed397656db4d35042f2e3dba5ca56a23ab02a7d4a4642cccc077086eaf0e1f", "tool": "Python", "notebook": "Find Phone Number in string", "action": "", "tags": ["#python", "#string", "#number", "#naas", "#operations", "#snippet"], "author": "Anas Tazir", "author_url": "https://github.com/anastazir", "updated_at": "2023-04-12", "created_at": "2022-10-06", "description": "This notebook provides a Python script to identify and extract phone numbers from a given string.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Find_Phone_Number_in_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Find_Phone_Number_in_string.ipynb", "imports": [], "image_url": ""}, {"objectID": "c53dc95597572e013944cf90ff5480eabd8f4deb4a7d116fcb2ef26ad5e76181", "tool": "Python", "notebook": "Find differences between strings", "action": "", "tags": ["#python", "#strings", "#differences", "#compare", "#find", "#string"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will compare two strings and find the differences between them. It is useful for users to quickly identify the differences between two strings.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Find_differences_between_strings.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Find_differences_between_strings.ipynb", "imports": [], "image_url": ""}, {"objectID": "c481bc8d4efd4aff05e1577eb197f2cfeed1834b5fd496a8438a190c5684c9f8", "tool": "Python", "notebook": "Flatten nested dict", "action": "", "tags": ["#python", "#dict", "#flatten", "#nested", "#data", "#structure"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will show how to flatten a nested dict in Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Flatten_nested_dict.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Flatten_nested_dict.ipynb", "imports": [], "image_url": ""}, {"objectID": "333b5d2d5a8adf1385cca957efd4e1193793c91593fdb4ba7eae7593fe88d64f", "tool": "Python", "notebook": "Get Word Definition and Translation", "action": "", "tags": ["#python", "#dictionary", "#project", "#word", "#snippet"], "author": "Sriniketh Jayasendil", "author_url": "https://twitter.com/srini047/", "updated_at": "2023-04-12", "created_at": "2022-10-18", "description": "This notebook get world definition and translation from English using PyDictionary.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_Word_Definition_and_Translation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_Word_Definition_and_Translation.ipynb", "imports": ["PyDictionary.PyDictionary", "PyDictionary.PyDictionary"], "image_url": ""}, {"objectID": "712b3b28a79e451c9bcce99b1cfd032a25416ce695e3c59f9f455df31523b8da", "tool": "Python", "notebook": "Get all files from directory", "action": "", "tags": ["#python", "#naas", "#glob", "#pprint", "#snippet"], "author": "Ayoub Berdeddouch", "author_url": "https://www.linkedin.com/ayoub-berdeddouch", "updated_at": "2023-04-12", "created_at": "2022-10-18", "description": "This notebook gives you the ability to get all files from a directory even in a sub-directory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_all_files_from_directory.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_all_files_from_directory.ipynb", "imports": ["glob", "os.path"], "image_url": ""}, {"objectID": "99b7889c02066945ea9978b756ab4b00c081c15b2f18dc3f7161b8a4f08923d8", "tool": "Python", "notebook": "Get coordinates from address", "action": "", "tags": ["#python", "#snippet", "#naas", "#geocoder"], "author": "Suhas B", "author_url": "https://www.linkedin.com/in/suhasbrao/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook get coordinates from a given address.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_coordinates_from_address.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_coordinates_from_address.ipynb", "imports": ["geocoder", "geocoder"], "image_url": ""}, {"objectID": "785972e87c0df9d4eae498b1c5c285f8fb9f85218c9745ddd20f3a04002b5659", "tool": "Python", "notebook": "Get emojis from text", "action": "", "tags": ["#python", "#text", "#emoji", "#nlp", "#string", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-23", "created_at": "2023-08-23", "description": "This notebook will show how to get emojis from text using `emoji` and `regex` libraries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_emojis_from_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_emojis_from_text.ipynb", "imports": ["emoji", "emoji", "regex"], "image_url": ""}, {"objectID": "8a57a4125fe02a9041a6723a3e80eea843fe2a5efb705b899c2558c8bbd5248e", "tool": "Python", "notebook": "Get last file modified from directy", "action": "", "tags": ["#python", "#os", "#library", "#file", "#modified", "#directory"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-23", "description": "This notebook will show how to get the last file modified from a directory using the os library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_last_file_modified_from_directy.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_last_file_modified_from_directy.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "ebc58d505f37c456cff8fedcc2252596d0f3957a268f00d45856b1231f12e98e", "tool": "Python", "notebook": "Get next occurrences of a cron job", "action": "", "tags": ["#python", "#cron", "#croniter", "#job", "#occurrences", "#scheduling"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-09", "created_at": "2023-05-09", "description": "This notebook will show how to get the next x occurrences of your cron job using croniter. It is usefull for organizations to schedule tasks and jobs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_next_occurrences_of_a_cron_job.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_next_occurrences_of_a_cron_job.ipynb", "imports": ["croniter", "croniter", "pytz", "datetime.datetime"], "image_url": ""}, {"objectID": "273a29ff310403095ebba2c30813413cdbea48f497eb114a7224762e8ae1ebf3", "tool": "Python", "notebook": "Get random number", "action": "", "tags": ["#python", "#number", "#generation", "#random", "#snippet", "#operation"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-08", "created_at": "2023-06-07", "description": "This notebook demonstrates how to get random numbers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_random_number.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_random_number.ipynb", "imports": ["random"], "image_url": ""}, {"objectID": "528d537bbac178bf8781873b2a2aad8e0496c9e1536508e3585d6ad24f41addc", "tool": "Python", "notebook": "Get a random word", "action": "", "tags": ["#python", "#word", "#random", "#snippet"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-19", "created_at": "2023-06-14", "description": "This notebook show how to get a random word.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_random_word.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_random_word.ipynb", "imports": ["random", "nltk.corpus.wordnet", "nltk.corpus.wordnet", "nltk"], "image_url": ""}, {"objectID": "381a06edafb0d844bae219bab0e7cd6772d3ed58bbb597161a0ffecce70fff53", "tool": "Python", "notebook": "List specific files from directory and subdirectories", "action": "", "tags": ["#python", "#glob", "#os", "#files", "#directory", "#subdirectories"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-31", "created_at": "2023-05-31", "description": "This notebook list all specific files from a directory and its subdirectories using glob and os libraries. It is usefull to quickly list all files from a directory and its subdirectories.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_List_specific_files_from_directory_and_subdirectories.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_List_specific_files_from_directory_and_subdirectories.ipynb", "imports": ["glob", "os"], "image_url": ""}, {"objectID": "34facbf13a7e56bfaa689c8351e1f7980a5b0ac0c6818da5b29d7930907d14fd", "tool": "Python", "notebook": "Locate address on map", "action": "", "tags": ["#python", "#geocoding", "#city", "#coordinates", "#location", "#api"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will show how to get coordinates from an address using Python and display it on a map.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Locate_address_on_map.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Locate_address_on_map.ipynb", "imports": ["geocoder", "geocoder", "pandas", "plotly.express"], "image_url": ""}, {"objectID": "f6bac2f96a6ae10b5e54f83f2ed151f5c4094bee0516f3ee795de50c02c95791", "tool": "Python", "notebook": "Locate city on map", "action": "", "tags": ["#python", "#geocoding", "#city", "#coordinates", "#location", "#api"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will show how to get coordinates from a city name using Python and display it on a map.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Locate_city_on_map.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Locate_city_on_map.ipynb", "imports": ["geocoder", "geocoder", "pandas", "plotly.express"], "image_url": ""}, {"objectID": "d55e369e1ac2a640e4019f281f7944654c06cb9f2b0c27c0f1f2f129dd5fa099", "tool": "Python", "notebook": "Locate coordinates", "action": "", "tags": ["#python", "#snippet", "#naas", "#geocoder"], "author": "Suhas B", "author_url": "https://www.linkedin.com/in/suhasbrao/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook provides a way to find the geographic coordinates of a given location using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Locate_coordinates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Locate_coordinates.ipynb", "imports": ["geocoder", "geocoder"], "image_url": ""}, {"objectID": "0d30d21161d2fb93660e3177f2620431276c202a1814b1913273755b86468e8a", "tool": "Python", "notebook": "Looping Over Dataframe", "action": "", "tags": ["#python", "#pandas", "#python", "#loops", "#dataframes", "#forloop", "#loop", "#snippet", "#operations"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-06-06", "created_at": "2021-10-08", "description": "This notebook provides an overview of how to use loops to iterate over a dataframe in Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Looping_Over_Dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Looping_Over_Dataframe.ipynb", "imports": ["pandas", "numpy"], "image_url": ""}, {"objectID": "b3250febe49c96eaa6b828a7d7db8ea79a7be078466bf984f7e3d0495291d190", "tool": "Python", "notebook": "Manage code error with try except", "action": "", "tags": ["#python", "#error", "#try", "#exception", "#snippet"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-16", "created_at": "2023-06-15", "description": "This notebook will demonstrate how to manage code error using try except. \nThe `try` block lets you test a block of code for errors.\nThe `except` block lets you handle the error. You can specify the type of exception to manage error.\nThe `else` block lets you execute code when there is no error.\nThe `finally` block lets you execute code, regardless of the result of the try- and except blocks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Manage_exception_with_try_except.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Manage_exception_with_try_except.ipynb", "imports": [], "image_url": ""}, {"objectID": "0ab9494e481d7f7c2fdead13ca4b8a0d8c8caca6cc43f1c1386eeaa60915720b", "tool": "Python", "notebook": "Organize Directories based on file types", "action": "", "tags": ["#organize", "#files", "#directories"], "author": "Ahmed Mousa", "author_url": "https://www.linkedin.com/in/akmousa/", "updated_at": "2023-04-12", "created_at": "2022-11-11", "description": "This notebook organizes your files based on their extensions to directories for data scientists", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Organize_Directories_based_on_file_types.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Organize_Directories_based_on_file_types.ipynb", "imports": ["shutil.move", "os.path", "os", "glob", "pathlib"], "image_url": ""}, {"objectID": "6b201a517cee73c048da83f5eeea5a372c37d868c68b1ba958a7eb3723778014", "tool": "Python", "notebook": "Pseudonym generator", "action": "", "tags": ["#python", "#pseudonym", "#generation", "#random", "#snippet", "#operation"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-19", "created_at": "2023-06-15", "description": "This notebook demonstrates how to get random pseudonym.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Pseudonym_generator.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Pseudonym_generator.ipynb", "imports": ["random"], "image_url": ""}, {"objectID": "764a61ccadd589be64a9953b0c2f0ae854335e74fb7dd944ed5585051a031eb8", "tool": "Python", "notebook": "Read pickle file", "action": "", "tags": ["#python", "#pickle", "#file", "#load", "#data", "#io"], "author": "Kaushal Krishna", "author_url": "https://www.linkedin.com/in/kaushal-krishna-a48959153/", "updated_at": "2023-04-12", "created_at": "2023-03-13", "description": "This notebook loads a dictionary from pickle object. Loading a dictionary using pickle is a quick and easy process. With just a few lines of code, you can store your dictionary data from a pickle file. \n\nPickle can cause critical security vulnerabilities in code, you should never unpickle data you don\u2019t trust. If you must accept data from an untrusted client, you should use the safer JSON format. And, if you transfer pickled data between trusted applications but need extra measures to prevent tampering, you should generate an HMAC signature you can verify before unpickling.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Read_pickle_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Read_pickle_file.ipynb", "imports": ["pickle"], "image_url": ""}, {"objectID": "0d78a6b4a629c2de8f39bc5862abe5d91077ed048c9ae5b3df5277f419395f72", "tool": "Python", "notebook": "Remove all spaces on string", "action": "", "tags": ["#python", "#remove", "#string", "#space"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-13", "created_at": "2023-06-13", "description": "This notebook shows how to remove all spaces from a string using two different methods", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Remove_all_spaces_on_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Remove_all_spaces_on_string.ipynb", "imports": [], "image_url": ""}, {"objectID": "cfcf72d570d6c8d8d5cb799af70b6e84175428ca194c3838cbaad7876b61aae1", "tool": "Python", "notebook": "Remove duplicates from a list", "action": "", "tags": ["#python", "#list", "#remove", "#duplicates", "#function", "#data"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-28", "created_at": "2023-08-28", "description": "This notebook explains how to remove duplicates from a list in Python. It is usefull for data cleaning and data wrangling.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Remove_duplicates_from_a_list.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Remove_duplicates_from_a_list.ipynb", "imports": [], "image_url": ""}, {"objectID": "2420ecf7c6601531c93fcf5bd3fd74ae7584c3b666889d872cecdd186ac28502", "tool": "Python", "notebook": "Save dict to pickle", "action": "", "tags": ["#python", "#pickle", "#file", "#save", "#data", "#io"], "author": "Kaushal Krishna", "author_url": "https://www.linkedin.com/in/kaushal-krishna-a48959153/", "updated_at": "2023-04-12", "created_at": "2023-03-13", "description": "This notebook saves a dictionary to pickle object. Saving a dictionary using pickle is a quick and easy process. With just a few lines of code, you can store your dictionary data in a binary format that can be easily loaded later on.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Save_dict_to_pickle.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Save_dict_to_pickle.ipynb", "imports": ["pickle"], "image_url": ""}, {"objectID": "cd0eb2047f4ba6ff6d26c2a2842f93e989014f5a4902b69592fd075bbb6859e4", "tool": "Python", "notebook": "Split string", "action": "", "tags": ["#python", "#file", "#string", "#url", "#split", "#snippet", "#operations"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-09", "created_at": "2023-06-08", "description": "This notebook shows you how to split a string object. The `split()` function in Python is useful for dividing a string into smaller parts based on a specified delimiter. It enables efficient string parsing, data cleaning, user input processing, and tokenization in natural language processing tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Split_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Split_string.ipynb", "imports": [], "image_url": ""}, {"objectID": "51927e37f1c930d38501a5524f66df6a3305327b1f73da29f93de18680b7b723", "tool": "Python", "notebook": "Transform String to Secure Hash Algorithm", "action": "", "tags": ["#python", "#security", "#hash", "#algorithm", "#encryption", "#sha"], "author": "Firstname LastName", "author_url": "https://www.linkedin.com/in/xxxxxx/", "updated_at": "2023-06-19", "created_at": "2023-06-19", "description": "This notebook will demonstrate how to create a secure hash algorithm using Python. It is useful for organizations to ensure data security and integrity.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Transform_string_to_Secure_Hash_Algorithm.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Transform_string_to_Secure_Hash_Algorithm.ipynb", "imports": ["hashlib", "hashlib"], "image_url": ""}, {"objectID": "6de9c1a35eb23d9d9f9c7f42401106d9b96ac0cfc31c95f41ee0fa4190b8ed10", "tool": "Python", "notebook": "Validate email and phone numbers", "action": "", "tags": ["#python", "#twilio", "#project", "#call", "#mobile", "#snippet"], "author": "Sriniketh Jayasendil", "author_url": "https://twitter.com/srini047/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook validates a given email address and phone number using `re` and `phonenumbers` modules.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Validate_email_and_phone_numbers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Validate_email_and_phone_numbers.ipynb", "imports": ["re", "phonenumbers", "phonenumbers"], "image_url": ""}, {"objectID": "2df55afca82f21837a817a57c842dcf4460d0908883b76b3c64576ef8f09f864", "tool": "Pyvis", "notebook": "Create a network visualization", "action": "", "tags": ["#python", "#naas", "#scheduler", "#network", "#snippet", "#analytics"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2022-07-27", "description": "With this notebook, you can create a network graph to visualize the relations between different elements.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pyvis/Pyvis_Create_a_network_visualization.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pyvis/Pyvis_Create_a_network_visualization.ipynb", "imports": ["naas", "pyvis.network.Network"], "image_url": ""}, {"objectID": "a7d100e0889cb14f5c824f377c6a44885ee52aa18f9155282c1d08bd2c642f26", "tool": "Qonto", "notebook": "Get cash position trend", "action": "", "tags": ["#qonto", "#bank", "#statement", "#naas_drivers", "#plotly", "#linechart", "#finance", "#analytics", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "This notebook provides an overview of cash position trends for Qonto customers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_cash_position_trend.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_cash_position_trend.ipynb", "imports": ["naas_drivers.qonto", "datetime.datetime", "pandas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "31964e4e6eb09f073ef7878131675b687729a27f0a488f0186e6666b735b861e", "tool": "Qonto", "notebook": "Get organizations", "action": "", "tags": ["#qonto", "#bank", "#organizations", "#positions", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "Qonto is a financial service that helps organizations manage their finances and get organized.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_organizations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_organizations.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "ea9e48f2660d5e99bf7c98f34152cb079f7643c88a1cb3bbb689828118d28d35", "tool": "Qonto", "notebook": "Get positions", "action": "", "tags": ["#qonto", "#bank", "#organizations", "#positions", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-01-26", "description": "This notebook provides an overview of the positions available through Qonto, a digital banking service.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_positions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_positions.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "6a9ad826ce7186c78e78078a3ee167f0a0226478c26805fe708b78eed6659048", "tool": "Qonto", "notebook": "Get statement", "action": "", "tags": ["#qonto", "#bank", "#statement", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "This notebook provides a convenient way to access and view your Qonto account statements.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_statement.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_statement.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "ae25587a760343b76cd21871e8fb5a9348e957b7e89fd66c66edeaa5683a1bcc", "tool": "Qonto", "notebook": "Get statement barline", "action": "", "tags": ["#qonto", "#bank", "#statement", "#plotly", "#barline", "#naas_drivers", "#finance", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-11-05", "description": "This notebook provides a convenient way to generate barlines for Qonto statements.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_statement_barline.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_statement_barline.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "e34d7a0d1f542aed1377cf95b45f7b2ae126679533186edb3529908fe0b406c8", "tool": "Qonto", "notebook": "Get statement ranking by category", "action": "", "tags": ["#qonto", "#bank", "#statement", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "This notebook provides a way to organize and analyze financial statements by category to gain insights into spending patterns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_statement_ranking_by_category.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_statement_ranking_by_category.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "f64cd3ab2aa93155bc8e1bf38148fb31ec7d96744518fe4426086a63de69c306", "tool": "Qonto", "notebook": "Get statement summary by operation type", "action": "", "tags": ["#qonto", "#bank", "#statement", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "This notebook provides a summary of financial operations by type for Qonto users.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_statement_summary_by_operation_type.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_statement_summary_by_operation_type.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "b79366dec95c9ac8fd048926ce03d2ce291bfc116f06d4c12182d386496c48bd", "tool": "Qonto", "notebook": "Get transactions", "action": "", "tags": ["#qonto", "#bank", "#transactions", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "Qonto's notebook allows you to easily access and manage your transactions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_transactions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_transactions.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "9cc3c79640025122d4d08f417b90e3c33382632218f192b7f91b09e0e07d7a36", "tool": "Qonto", "notebook": "Releve de compte augmente", "action": "", "tags": ["#qonto", "#bank", "#statement", "#naas_drivers", "#notification", "#emailbuilder", "#asset", "#scheduler", "#naas", "#finance", "#automation", "#analytics", "#plotly", "#email", "#html", "#image", "#excel"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-07-21", "description": "Recevez un relev\u00e9 de compte augment\u00e9 par email gratuitement, chaque semaine, gr\u00e2ce \u00e0 un template Naas.ai (moteur de donn\u00e9es opensource, 100 cr\u00e9dits offert par mois). \n

\n-Dur\u00e9e de l'installation = 5 minutes
\n-Support d'installation = Guide vid\u00e9o
\n-Niveau = Facile
", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Releve_de_compte_augmente.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Releve_de_compte_augmente.ipynb", "imports": ["naas_drivers.qonto", "datetime.datetime, timedelta", "pandas", "naas", "naas"], "image_url": ""}, {"objectID": "b011d4cb48a9cb6019a9bf3d65607a661c3b457d783fd0a31f524e0d36d500a0", "tool": "Quandl", "notebook": "Get data from API", "action": "", "tags": ["#quandl", "#marketdata", "#opendata", "#finance", "#snippet", "#matplotlib"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a guide to retrieving data from the Quandl API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Quandl/Quandl_Get_data_from_API.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Quandl/Quandl_Get_data_from_API.ipynb", "imports": ["quandl", "matplotlib.pyplot"], "image_url": ""}, {"objectID": "5fc16e4d7e6415f3d4c6c3adb959707425d1e22a89f4c9ed83dce4819a6524be", "tool": "Quandl", "notebook": "Get data from CSV", "action": "", "tags": ["#quandl", "#marketdata", "#opendata", "#finance", "#snippet", "#csv"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a guide to retrieving data from CSV files using the Quandl API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Quandl/Quandl_Get_data_from_CSV.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Quandl/Quandl_Get_data_from_CSV.ipynb", "imports": ["matplotlib.pyplot", "pandas", "os"], "image_url": ""}, {"objectID": "8531d6684ed740ec2ff6fd79b946c490932a6fb0b5f8929ace7f53c543152096", "tool": "Reddit", "notebook": "Get Hot Posts From Subreddit", "action": "", "tags": ["#reddit", "#subreddit", "#data", "#hottopics", "#rss", "#information", "#opendata", "#snippet", "#dataframe"], "author": "Yaswanthkumar GOTHIREDDY", "author_url": "https://www.linkedin.com/in/yaswanthkumargothireddy/", "updated_at": "2023-04-12", "created_at": "2021-08-16", "description": "This notebook allows users to retrieve the hottest posts from a specified subreddit on Reddit.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Reddit/Reddit_Get_Hot_Posts_From_Subreddit.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Reddit/Reddit_Get_Hot_Posts_From_Subreddit.ipynb", "imports": ["praw", "pandas", "numpy", "datetime.datetime"], "image_url": ""}, {"objectID": "8812c328726e145037006c5dcb182640230ec58dcb57aec562289e838e3ae409", "tool": "Redshift", "notebook": "Connect with SQL Magic and IAM Credentials", "action": "", "tags": ["#redshift", "#database", "#snippet", "#operations", "#naas", "#jupyternotebooks"], "author": "Caleb Keller", "author_url": "https://www.linkedin.com/in/calebmkeller/", "updated_at": "2023-04-12", "created_at": "2021-07-16", "description": "## Input\n\n- ipython-sql\n- boto3\n- psycopg2\n- sqlalchemy-redshift\n\nIf you're running in NaaS, you can execute the below to install the necessary libraries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Redshift/Redshift_Connect_with_SQL_Magic_and_IAM_Credentials.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Redshift/Redshift_Connect_with_SQL_Magic_and_IAM_Credentials.ipynb", "imports": ["boto3", "psycopg2", "getpass", "pandas", "urllib.parse"], "image_url": ""}, {"objectID": "4f03512608dfc108d56e8bd6f0396f48d71e76adca829f5753f7ed8172a2f2de", "tool": "RegEx", "notebook": "Check email validity", "action": "", "tags": ["#regex", "#python", "#email", "#validity", "#check", "#string"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook will demonstrate how to check the validity of an email address using `re` module. \nThe `re.search()` function in Python's re module allows you to search for a specified pattern within a string. It returns a match object if the pattern is found, enabling you to extract relevant information from the string based on the given pattern.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/RegEx/RegEx_Check_email_validity.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/RegEx/RegEx_Check_email_validity.ipynb", "imports": ["re"], "image_url": ""}, {"objectID": "685a1f40f7aa4a1232db34e0359c257af7cfb943e0ababc3ce2c39cb4d53a733", "tool": "RegEx", "notebook": "Match pattern", "action": "", "tags": ["#regex", "#python", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook demonstrates how to match a pattern in a string using `re.search()` and `re.match()`. The main difference between `re.search()` and `re.match()` lies in how they apply pattern matching to the input string. `re.search()` scans the entire input string and returns the first occurrence of a pattern match, regardless of its position within the string. On the other hand, `re.match()` only checks for a pattern match at the beginning of the string.\n\nTo start, we recommand you to test your regular expression using this website: https://regex101.com/", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/RegEx/RegEx_Match_pattern.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/RegEx/RegEx_Match_pattern.ipynb", "imports": ["re"], "image_url": ""}, {"objectID": "8f7a2b09ec80741fdd6479ff42823dd333560ec26a5dad2ef45593c41062ba48", "tool": "RegEx", "notebook": "Remove HTML tags from text", "action": "", "tags": ["#regex", "#python", "#html", "#text", "#remove", "#tags", "#string"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-25", "created_at": "2023-08-25", "description": "This notebook shows how to remove HTML tags from a text using Python. It is usefull for organizations that need to clean text from HTML tags before using it.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/RegEx/RegEx_Remove_HTML_tags_from_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/RegEx/RegEx_Remove_HTML_tags_from_text.ipynb", "imports": ["re"], "image_url": ""}, {"objectID": "c1fb82c7c15421cc52e119f4c0989d93fff90d185ae48e67c528a81197f697ce", "tool": "RegEx", "notebook": "Replace value in text in a specific paragraph", "action": "", "tags": ["#regex", "#re", "#python", "#string", "#replace", "#text", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook will show how to replace a value in a specific paragraph of a text using `re` module. The `re.sub()` function enables you to perform pattern-based string substitutions. It allows you to replace occurrences of a pattern in a given string with a specified replacement.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/RegEx/RegEx_Replace_value_in_text_in_a_specific_paragraph.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/RegEx/RegEx_Replace_value_in_text_in_a_specific_paragraph.ipynb", "imports": ["re"], "image_url": ""}, {"objectID": "305c5c190163ec3d354712a27c233a097b14c1492cd412900d9283b6cacc4424", "tool": "Remoteok", "notebook": "Get jobs from categories", "action": "", "tags": ["#remoteok", "#jobs", "#csv", "#snippet", "#opendata", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-03", "description": "Remoteok is a job search platform that allows users to find jobs from a variety of categories.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remoteok/Remoteok_Get_jobs_from_categories.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remoteok/Remoteok_Get_jobs_from_categories.ipynb", "imports": ["pandas", "requests", "datetime.datetime", "time"], "image_url": ""}, {"objectID": "d49a83032e1012afe8025a8ee46e5eca93ea3f5212272486e2ea692bd2783590", "tool": "Remoteok", "notebook": "Post daily jobs on slack", "action": "", "tags": ["#remoteok", "#jobs", "#slack", "#gsheet", "#naas_drivers", "#automation", "#opendata", "#text"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-03", "description": "This notebook allows you to post daily jobs from Remoteok to your Slack workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remoteok/Remoteok_Post_daily_jobs_on_slack.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remoteok/Remoteok_Post_daily_jobs_on_slack.ipynb", "imports": ["pandas", "requests", "datetime.datetime", "time", "naas_drivers.gsheet, slack", "naas"], "image_url": ""}, {"objectID": "2e0a5121d38b84cc390290272eea893ea63d79e5ce7993a046e6c6f332824dfc", "tool": "Remotive", "notebook": "Get categories from job", "action": "", "tags": ["#remotive", "#categories", "#snippet", "#opendata", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-02-14", "description": "This notebook provides a way to categorize jobs posted on Remotive.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remotive/Remotive_Get_categories_from_job.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remotive/Remotive_Get_categories_from_job.ipynb", "imports": ["pandas", "requests"], "image_url": ""}, {"objectID": "e141af26ebf6859a4e26fdf19cbbef08826a4a49ba12d240412d69b89f8b322b", "tool": "Remotive", "notebook": "Get jobs from categories", "action": "", "tags": ["#remotive", "#jobs", "#csv", "#snippet", "#opendata", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-02-14", "description": "This notebook provides a comprehensive list of remote job opportunities from a variety of categories.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remotive/Remotive_Get_jobs_from_categories.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remotive/Remotive_Get_jobs_from_categories.ipynb", "imports": ["pandas", "requests", "time", "datetime.datetime"], "image_url": ""}, {"objectID": "521ba7b3ee67b30d454150ddda5168f097b9f305cc6b56c02297e603aade0ba9", "tool": "Remotive", "notebook": "Post daily jobs on slack", "action": "", "tags": ["#remotive", "#jobs", "#slack", "#gsheet", "#naas_drivers", "#automation", "#opendata", "#text"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-02-09", "description": "Remotive is a Slack app that allows users to post and find remote job opportunities on a daily basis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remotive/Remotive_Post_daily_jobs_on_slack.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remotive/Remotive_Post_daily_jobs_on_slack.ipynb", "imports": ["pandas", "bs4.BeautifulSoup", "requests", "datetime.datetime", "time", "naas_drivers.gsheet, slack", "naas"], "image_url": ""}, {"objectID": "0bae0fd45a541ae9aa454e8fce4a5df9f94d001e54ac616de251c2cf19566aeb", "tool": "Remotive", "notebook": "Send jobs to gsheet", "action": "", "tags": ["#remotive", "#jobs", "#gsheet", "#naas_drivers", "#automation", "#opendata", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-14", "description": "This notebook allows users to quickly and easily send jobs to a Google Sheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remotive/Remotive_Send_jobs_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remotive/Remotive_Send_jobs_to_gsheet.ipynb", "imports": ["pandas", "requests", "datetime.datetime", "time", "naas_drivers.gsheet", "naas"], "image_url": ""}, {"objectID": "c760989aeb646043394a467ce2c6b687a3066f01ab69f8e63a21755361bd5fe0", "tool": "Request", "notebook": "Basic HTTP GET", "action": "", "tags": ["#request", "#http", "#get", "#library", "#python", "#api"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-14", "created_at": "2023-06-09", "description": "This notebook provides a template for making a basic HTTP GET request using the requests library. It covers importing the library, making the request, handling the response, and displaying the retrieved data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Request/Request_Basic_HTTP_GET_Request.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Request/Request_Basic_HTTP_GET_Request.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "e4657f273b8f1a16243f2cf42b54bf6280fd4415f91496be69bae05c845828cc", "tool": "Request", "notebook": "Handling Errors and Exceptions", "action": "", "tags": ["#request", "#error", "#exception", "#handling", "#python", "#library"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-26", "created_at": "2023-06-09", "description": "This notebook template explores how to handle errors and exceptions when using the requests library. It provides examples of error handling techniques, including proper status code checking, handling timeouts, and dealing with connection errors.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Request/Request_Handling_Errors_and_Exceptions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Request/Request_Handling_Errors_and_Exceptions.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "9678f6e9d554c476ab1edd5e4046bdb3c55626b16b11a91767b3ef45250215d2", "tool": "Request", "notebook": "Sending POST s with Data", "action": "", "tags": ["#requests", "#post", "#data", "#python", "#library", "#api"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-16", "created_at": "2023-06-09", "description": "This notebook template demonstrates how to use the requests library to send a POST request with data. It includes importing the library, preparing the data, making the request, handling the response, and verifying the successful submission.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Request/Request_Sending_POST_Requests_with_Data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Request/Request_Sending_POST_Requests_with_Data.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "1ec91cf3ea4e7bc9c5e5fe8f000bfcab76e74a221d3820500f41cb5744282f1d", "tool": "SAP-HANA", "notebook": "Query data", "action": "", "tags": ["#sap-hana", "#sap", "#saphana", "#database", "#snippet", "#operations", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides an introduction to querying data in SAP HANA.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SAP-HANA/SAP-HANA_Query_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SAP-HANA/SAP-HANA_Query_data.ipynb", "imports": ["sap_hana_connector"], "image_url": ""}, {"objectID": "bc8693ec5df8d3d2c7d05271ed8f68e0aeefdcb1ae5c3fcefcf4246df9614dcd", "tool": "SEON", "notebook": "Get email info", "action": "", "tags": ["#seon", "#email", "#enrichment", "#api", "#tool", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-23", "description": "This notebook will demonstrate how to use SEON's standalone email enrichment tool to learn about the approximate minimum age of an email address, its provider, and any connected online profiles and save it into a json file.\n\n*Good to know:*\n- You can use the Fraud API if you want to use the Email API together with any of our Phone API, IP API, and Device Fingerprinting.\n- All SEON API requests are case-sensitive. Please follow the formatting below to avoid errors.\n- Email API requests are limited to 120/minute during your SEON free trial.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SEON/SEON_Get_email_info.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SEON/SEON_Get_email_info.ipynb", "imports": ["requests", "naas", "pprint.pprint", "json"], "image_url": ""}, {"objectID": "dfc7aa18b61ba877af2ccc28a176b6ec5c7ae90df276085a78e8a01d116ec615", "tool": "SQLite", "notebook": "Create Database file", "action": "", "tags": ["#SQLite", "#database", "#databasemanagement", "#filebaseddb", "#dbcreation", "#dbsetup", "#SQLiteDB", "#localstorage", "#datastore", "#SQLitedatabase", "#embeddedDB", "#PythonDB", "#sqllite3", "#DBfile"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook creates a new SQLite database file using the sqlite3 module in Python. Here's an example of how you can create a new SQLite database file called \"mydatabase.db\"", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SQLite/SQLite_Create_Database_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SQLite/SQLite_Create_Database_file.ipynb", "imports": ["sqlite3"], "image_url": ""}, {"objectID": "1bc66c95ce6020ea5e543316f2bf03a0cf0e7d41f12680f81371452e3454320d", "tool": "SQLite", "notebook": "Create Table in Database", "action": "", "tags": ["#SQLite", "#database", "#databasemanagement", "#filebaseddb", "#dbcreation", "#dbsetup", "#SQLiteDB", "#localstorage", "#datastore", "#SQLitedatabase", "#embeddedDB", "#PythonDB", "#sqllite3", "#DBfile"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook creates a table called \"employees\" in a SQLite database. Please note that the new table created will erase the old one if a table already exist in the database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SQLite/SQLite_Create_Table_in_Database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SQLite/SQLite_Create_Table_in_Database.ipynb", "imports": ["sqlite3"], "image_url": ""}, {"objectID": "d9989623aa996ed0e28f3ea73630f21a11e50cc3087b3de6271505d6c59bb986", "tool": "SQLite", "notebook": "Insert data in Table", "action": "", "tags": ["#SQLite", "#database", "#databasemanagement", "#filebaseddb", "#dbcreation", "#dbsetup", "#SQLiteDB", "#localstorage", "#datastore", "#SQLitedatabase", "#embeddedDB", "#PythonDB", "#sqllite3", "#DBfile"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook insert the values into a table in a SQLite database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SQLite/SQLite_Insert_data_in_Table.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SQLite/SQLite_Insert_data_in_Table.ipynb", "imports": ["sqlite3"], "image_url": ""}, {"objectID": "7190661ad83396721f507d763dc721bf6a56ccba205c65a622153be05d637503", "tool": "SQLite", "notebook": "List Tables in Database", "action": "", "tags": ["#SQLite", "#database", "#databasemanagement", "#filebaseddb", "#dbcreation", "#dbsetup", "#SQLiteDB", "#localstorage", "#datastore", "#SQLitedatabase", "#embeddedDB", "#PythonDB", "#sqllite3", "#DBfile"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook lists tables within a SQLite database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SQLite/SQLite_List_Tables_in_Database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SQLite/SQLite_List_Tables_in_Database.ipynb", "imports": ["sqlite3"], "image_url": ""}, {"objectID": "00e01d8540447a9f7dbc8a19ee47f55e785be0d85e821c4ce6f8912fba9b6d33", "tool": "SQLite", "notebook": "Read data in Table", "action": "", "tags": ["#SQLite", "#database", "#databasemanagement", "#filebaseddb", "#dbcreation", "#dbsetup", "#SQLiteDB", "#localstorage", "#datastore", "#SQLitedatabase", "#embeddedDB", "#PythonDB", "#sqllite3", "#DBfile"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook reads data from a table called \"employees\" in a SQLite database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SQLite/SQLite_Read_data_in_Table.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SQLite/SQLite_Read_data_in_Table.ipynb", "imports": ["sqlite3"], "image_url": ""}, {"objectID": "b2640eef0eb25e93c3717902c701273fe4f8689ec7805ec9865aa5dede072f65", "tool": "SWIFT", "notebook": "Create MT940 XML file", "action": "", "tags": ["#swift", "#mt940", "#xml", "#file", "#create", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-17", "description": "This notebook will show how to create an MT940 XML file using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SWIFT/SWIFT_Create_MT940_XML_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SWIFT/SWIFT_Create_MT940_XML_file.ipynb", "imports": ["xml.etree.ElementTree"], "image_url": ""}, {"objectID": "d7e34a46dfdab62d55033522183e338b4bfd89523400494c9c14a7880471b1cb", "tool": "SendGrid", "notebook": "Get all messages", "action": "", "tags": ["#sendgrid", "#activity", "#snippet", "#operations", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-04-04", "description": "This notebook provides a comprehensive overview of all messages sent through SendGrid.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SendGrid/SendGrid_Get_all_messages.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SendGrid/SendGrid_Get_all_messages.ipynb", "imports": ["naas", "requests", "urllib", "pandas"], "image_url": ""}, {"objectID": "49126dfdadde535c9004cb89b3c0e4c1fea355ea72a5e9f019fc99086ba4befc", "tool": "SendGrid", "notebook": "Send message", "action": "", "tags": ["#sendgrid", "#message", "#snippet", "#operations"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook allows you to send messages using SendGrid's email delivery service.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SendGrid/SendGrid_Send_message.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SendGrid/SendGrid_Send_message.ipynb", "imports": ["requests", "sendgrid.SendGridAPIClient", "sendgrid.helpers.mail.*"], "image_url": ""}, {"objectID": "3644b28c400b814d09ab9a29811b9ce0d5c88db8b6ea7288146b12530d88e1ad", "tool": "Sendinblue", "notebook": "Get no of emails opened", "action": "", "tags": ["#sendinblue", "#emails", "#campaign", "#opened", "#emailcampaigns", "#marketing", "#operations", "#snippet"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-07-09", "description": "This notebook provides a way to track the number of emails opened using Sendinblue.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Sendinblue/Sendinblue_Get_no_of_emails_opened.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Sendinblue/Sendinblue_Get_no_of_emails_opened.ipynb", "imports": ["requests", "json", "naas"], "image_url": ""}, {"objectID": "7dcc2250cb71fd6d7df3b877dc5168e6ee68e03beb17aeed32fb057a113f9740", "tool": "Sendinblue", "notebook": "Get no of emails sent", "action": "", "tags": ["#sendinblue", "#emails", "#campaign", "#sent", "#emailcampaigns", "#marketing", "#operations", "#snippet"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-07-09", "description": "This notebook provides a way to track the number of emails sent through Sendinblue.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Sendinblue/Sendinblue_Get_no_of_emails_sent.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Sendinblue/Sendinblue_Get_no_of_emails_sent.ipynb", "imports": ["requests", "json", "naas"], "image_url": ""}, {"objectID": "d44b552d043fa74c9a00ca9ed43835a9acd1016434330820159f1818411b73e4", "tool": "Sendinblue", "notebook": "Get no of spam reports", "action": "", "tags": ["#sendinblue", "#emails", "#campaign", "#spam", "#emailcampaigns", "#marketing", "#operations", "#snippet"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-07-09", "description": "This notebook provides a way to track the number of spam reports received through Sendinblue.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Sendinblue/Sendinblue_Get_no_of_spam_reports.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Sendinblue/Sendinblue_Get_no_of_spam_reports.ipynb", "imports": ["requests", "json", "naas"], "image_url": ""}, {"objectID": "dd7e259333a94870bff986f6e4f3d3e1875f6fd02fbe6c6fccacd81d7fbc1336", "tool": "Sendinblue", "notebook": "Get no of undelivered emails", "action": "", "tags": ["#emails", "#campaign", "#undelivered", "#emailcampaigns", "#marketing", "#sendinblue", "#operations", "#snippet"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook provides a count of emails that were not successfully delivered using Sendinblue.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Sendinblue/Sendinblue_Get_no_of_undelivered_emails.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Sendinblue/Sendinblue_Get_no_of_undelivered_emails.ipynb", "imports": ["requests", "json", "naas"], "image_url": ""}, {"objectID": "e14418219d04e28461426bee2d1dd57778c3265b9e36b8696268ad8ed0b5f0bc", "tool": "SharePoint", "notebook": "Get file", "action": "", "tags": ["#sharepoint", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-07-13", "description": "This notebook provides a guide to retrieving files from a SharePoint server.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SharePoint/SharePoint_Get_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SharePoint/SharePoint_Get_file.ipynb", "imports": ["naas_drivers.sharepoint", "naas"], "image_url": ""}, {"objectID": "ea00d49b6e6488a3327b37ffc55ae0498cbd875f1a50654e4298105e11fd0af2", "tool": "SharePoint", "notebook": "List folder", "action": "", "tags": ["#sharepoint", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-07-13", "description": "This notebook provides a guide to managing and organizing files in a SharePoint List folder.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SharePoint/SharePoint_List_folder.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SharePoint/SharePoint_List_folder.ipynb", "imports": ["naas_drivers.sharepoint", "naas"], "image_url": ""}, {"objectID": "00f1ebf2b83dcf76e8e3264850f5e04de346e4722e102bc8a95aa553a44255fc", "tool": "SharePoint", "notebook": "Upload file", "action": "", "tags": ["#sharepoint", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-07-13", "description": "This notebook provides instructions on how to upload a file to a SharePoint site.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SharePoint/SharePoint_Upload_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SharePoint/SharePoint_Upload_file.ipynb", "imports": ["naas_drivers.sharepoint", "naas"], "image_url": ""}, {"objectID": "310727059ea08d1992077ac57cb0ca54196257738cb92d852bbb2bc3af7a7251", "tool": "Shutterstock", "notebook": "Search for images", "action": "", "tags": ["#shutterstock", "#images", "#search", "#api", "#reference", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-20", "created_at": "2023-02-27", "description": "This notebook will demonstrate how to use the Shutterstock API to search for images.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Shutterstock/Shutterstock_Search_for_images.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Shutterstock/Shutterstock_Search_for_images.ipynb", "imports": ["json", "naas", "requests", "PIL.Image", "io", "matplotlib.pyplot", "pydash"], "image_url": ""}, {"objectID": "69edbf0f3bece275b66ceff5c8dc5510c1db14429f958e7dc109afbf15f02bc2", "tool": "Slack", "notebook": "Add new user to Google Sheets", "action": "", "tags": ["#slack", "#googlesheets", "#operations", "#automation"], "author": "Sanjeet Attili", "author_url": "https://docs.naas.ai/templates/google-sheets", "updated_at": "2023-04-12", "created_at": "2022-04-25", "description": "## Input", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Slack/Slack_Add_new_user_to_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Slack/Slack_Add_new_user_to_Google_Sheets.ipynb", "imports": ["naas_drivers.gsheet", "naas", "pandas", "slack_sdk.WebClient", "datetime.datetime"], "image_url": ""}, {"objectID": "5f730f307f840b3988958c46d7d837ac5877d7294ba2e4e8c77db87521611989", "tool": "Slack", "notebook": "Follow number of users in workspace", "action": "", "tags": ["#slack", "#plotly", "#html", "#image", "#csv", "#marketing", "#automation", "#analytics"], "author": "Sanjeet Attili", "author_url": "https://github.com/slackapi/python-slack-sdk", "updated_at": "2023-04-12", "created_at": "2022-04-25", "description": "## Input", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Slack/Slack_Follow_number_of_users_in_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Slack/Slack_Follow_number_of_users_in_workspace.ipynb", "imports": ["naas", "pandas", "plotly.graph_objects", "slack_sdk.WebClient", "datetime.datetime"], "image_url": ""}, {"objectID": "8c14aab53bd8c6fe6689201ba16d90346db4f37cb888763e61eb7a3c65c38eda", "tool": "Slack", "notebook": "Send blocks to channel", "action": "", "tags": ["#slack", "#message", "#send", "#operations", "#snippet", "#block"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-22", "created_at": "2023-06-19", "description": "This notebook allows you to quickly and easily send blocks through Slack. Blocks are visual components that can be stacked and arranged to create app layouts. Block Kit can make your app's communication clearer while also giving you consistent opportunity to interact with and assist users.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Slack/Slack_Send_blocks_to_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Slack/Slack_Send_blocks_to_channel.ipynb", "imports": ["naas_drivers.slack", "naas"], "image_url": ""}, {"objectID": "0531f44f6ac83d8e06902f52b1460d35fb57a29f6afb4091f1a276d3244a91af", "tool": "Slack", "notebook": "Send message", "action": "", "tags": ["#slack", "#message", "#send", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-22", "created_at": "2023-06-22", "description": "This notebook allows you to quickly and easily send text messages through Slack.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Slack/Slack_Send_message_to_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Slack/Slack_Send_message_to_channel.ipynb", "imports": ["naas_drivers.slack", "naas"], "image_url": ""}, {"objectID": "15defdfba3040a35be89b5bf41b6e7de4dd4317de5bff7d85d5541e1ae4487a4", "tool": "Snowflake", "notebook": "Basics and data querying", "action": "", "tags": ["#snowflake", "#data", "#warehouse", "#naas_drivers", "#snippet"], "author": "Mateusz Polakowski", "author_url": "https://www.linkedin.com/in/polakowski/", "updated_at": "2023-04-12", "created_at": "2022-08-06", "description": "This notebook provides an introduction to the basics of Snowflake and how to query data within it.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Snowflake/Snowflake_Basics_and_data_querying.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Snowflake/Snowflake_Basics_and_data_querying.ipynb", "imports": ["os", "naas_drivers.snowflake", "snowflake.connector.errors.ProgrammingError"], "image_url": ""}, {"objectID": "e34aa1f49930e96ed9f8f3a829011f511890ffdde810c43f4f06637a66d85b9a", "tool": "Snowflake", "notebook": "Ingest csv data from local stage", "action": "", "tags": ["#snowflake", "#data", "#warehouse", "#naas_drivers", "#snippet"], "author": "Mateusz Polakowski", "author_url": "https://www.linkedin.com/in/polakowski/", "updated_at": "2023-04-12", "created_at": "2022-08-06", "description": "This notebook demonstrates how to ingest CSV data from a local stage into Snowflake.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Snowflake/Snowflake_Ingest_csv_data_from_local_stage.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Snowflake/Snowflake_Ingest_csv_data_from_local_stage.ipynb", "imports": ["os", "naas_drivers.snowflake", "snowflake.connector.errors.ProgrammingError"], "image_url": ""}, {"objectID": "e272e6e7fcca9fb2482ff3f91eab93a951c03c36e6bf7ba1fd83d6928b88c88c", "tool": "Snowflake", "notebook": "Ingest data from AWS external stages", "action": "", "tags": ["#snowflake", "#data", "#warehouse", "#naas_drivers", "#snippet"], "author": "Mateusz Polakowski", "author_url": "https://www.linkedin.com/in/polakowski/", "updated_at": "2023-04-12", "created_at": "2022-08-06", "description": "This notebook demonstrates how to ingest data from AWS external stages into Snowflake.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Snowflake/Snowflake_Ingest_data_from_AWS_external_stages.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Snowflake/Snowflake_Ingest_data_from_AWS_external_stages.ipynb", "imports": ["os", "naas_drivers.snowflake", "snowflake.connector.errors.ProgrammingError", "pandas"], "image_url": ""}, {"objectID": "0dfb1e2bec528e076f9a7e599747f0b8ff34b464253c902a17b7f737791862f9", "tool": "Snowflake", "notebook": "Ingest json data from local stage", "action": "", "tags": ["#snowflake", "#data", "#warehouse", "#naas_drivers", "#snippet"], "author": "Mateusz Polakowski", "author_url": "https://www.linkedin.com/in/polakowski/", "updated_at": "2023-04-12", "created_at": "2022-08-06", "description": "This notebook demonstrates how to ingest JSON data from a local stage into Snowflake.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Snowflake/Snowflake_Ingest_json_data_from_local_stage.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Snowflake/Snowflake_Ingest_json_data_from_local_stage.ipynb", "imports": ["os", "naas_drivers.snowflake", "snowflake.connector.errors.ProgrammingError"], "image_url": ""}, {"objectID": "996435d28247d8e9c175da10ebc3f3a3c3a7709f6ab658a453069f27629f80aa", "tool": "Societe.com", "notebook": "Get company details", "action": "", "tags": ["#societe.com", "#companies", "#opendata", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides detailed information about companies registered on Societe.com.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Societe.com/Societe.com_Get_company_details.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Societe.com/Societe.com_Get_company_details.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "44d6284d9798272ec8d8b57d4a4cc811e758e0612d0d87c9fca6bf49c2b79c75", "tool": "Societe.com", "notebook": "Get verif.com", "action": "", "tags": ["#companies", "#opendata", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides access to Societe.com's verification services through Verif.com.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Societe.com/Societe.com_Get_verif.com.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Societe.com/Societe.com_Get_verif.com.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "460cb50b6264b395c250e70db47ad5aa39b2bfcc2b406dc25e5adbce004a87dc", "tool": "Spotify", "notebook": "Create Radar Chart to analyze Playlist", "action": "", "tags": ["#spotify", "#python", "#spotipy", "#analytics", "#operations", "#image"], "author": "Akshaya Parthasarathy", "author_url": "https://github.com/iaks23", "updated_at": "2023-04-12", "created_at": "2021-10-12", "description": "This notebook provides a step-by-step guide to creating a Radar Chart to analyze a Spotify Playlist.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Spotify/Spotify_Create_Radar_Chart_to_analyze_Playlist.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Spotify/Spotify_Create_Radar_Chart_to_analyze_Playlist.ipynb", "imports": ["json", "spotipy", "pandas", "spotipy.oauth2.SpotifyClientCredentials", "sklearn.preprocessing.MinMaxScaler", "matplotlib.pyplot", "math.pi"], "image_url": ""}, {"objectID": "dca116db84f70425c4800366b46cc450713e1b39960edc929e38deed8702789b", "tool": "Stabilty AI", "notebook": "Generate Image from text", "action": "", "tags": ["#stabilityai", "#png", "#prompt", "#generate", "#file", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-27", "description": "This notebook will demonstrate how to execute a basic image generation call via Stability AI API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stabilty%20AI/Stabilty_AI_Generate_Image_from_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stabilty%20AI/Stabilty_AI_Generate_Image_from_text.ipynb", "imports": ["os", "io", "warnings", "PIL.Image", "stability_sdk.client", "stability_sdk.client", "stability_sdk.interfaces.gooseai.generation.generation_pb2", "naas"], "image_url": ""}, {"objectID": "832c6caba950d6fab4bf84f56f9ec0661ca43ffc478e0f39bf5ba999022a6e17", "tool": "Stable Diffusion", "notebook": "Generate image from text", "action": "", "tags": ["#stable-diffusion", "#image-generation", "#text-to-image", "#ai", "#machine-learning", "#deep-learning"], "author": "Oussama El Bahaoui", "author_url": "https://www.linkedin.com/in/oelbahaoui/", "updated_at": "2023-06-19", "created_at": "2023-05-12", "description": "This notebook generate image from text using Stable Diffusion.\n\nIt requires a more powerful machine than the free tier we provide. You have two options to proceed:\n\n1. **Using Google Colab:** If you have a Google account, you can open this notebook in Google Colab(link is above), which provides free access to more powerful computational resources to run this notebook. To do this, click the \u201cOpen in Colab\u201d button located at the end of this paragraph. Please note that you may need to sign in with your Google account or create one if you don\u2019t have it. \"Open\n\n2. **Contacting Us for Machine Upgrade:** If you prefer to run this notebook on your own machine, you can contact us to upgrade your machine. Our team will assist you in setting up the necessary environment. Please reach out to [Jeremy Ravenel](mailto:jeremy@naas.ai) for further assistance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stable%20Diffusion/Stable_Diffusion_Generate_image_from_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stable%20Diffusion/Stable_Diffusion_Generate_image_from_text.ipynb", "imports": ["diffusers.DiffusionPipeline, DPMSolverMultistepScheduler", "PIL.Image", "matplotlib.pyplot", "torch"], "image_url": ""}, {"objectID": "966d01eed050cc4cb01fe7a63b108c7981a5c194867ac50e215e489fe9ef04c0", "tool": "Streamlit", "notebook": "Create prediction app", "action": "", "tags": ["#streamlit", "#app", "#ml", "#ai", "#operations", "#plotly"], "author": "Gagan Bhatia", "author_url": "https://github.com/gagan3012", "updated_at": "2023-04-12", "created_at": "2021-09-01", "description": "This notebook provides a step-by-step guide to creating a Streamlit app that can make predictions based on user input.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Streamlit/Streamlit_Create_prediction_app.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Streamlit/Streamlit_Create_prediction_app.ipynb", "imports": ["naas_drivers.streamlit", "naas_drivers.streamlit, plotly, yahoofinance, prediction", "streamlit"], "image_url": ""}, {"objectID": "ea7c3e26461ab96b7177bdb5a53a4091ee6e0c1d59010899a52e7fdb96b41797", "tool": "Stripe", "notebook": "Create a customer", "action": "", "tags": ["#stripe", "#payment", "#customer", "#api", "#python", "#create", "#crud"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-18", "created_at": "2023-04-30", "description": "This notebook will show how to create a customer using the Stripe API. It is usefull for organizations that need to manage customer payments.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Create_a_customer.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Create_a_customer.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "80d3f6a6c98fb33c54b4e6eb95c5741adf5c5a89f6ca6c85ec149c2d1789a907", "tool": "Stripe", "notebook": "Delete a customer", "action": "", "tags": ["#stripe", "#payment", "#customer", "#api", "#python", "#delete", "#crud"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-18", "created_at": "2023-05-18", "description": "This notebook will show how to delete a customer using the Stripe API. It is usefull for organizations that need to manage customer payments.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Delete_a_customer.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Delete_a_customer.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "2e1162c3667428d176ee2dc9ae136c309599c272948339c3783e0960761b749d", "tool": "Stripe", "notebook": "Get balances", "action": "", "tags": ["#stripe", "#balances", "#snippet", "#operations", "#dataframe"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides a way to view and manage Stripe account balances.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Get_balances.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Get_balances.ipynb", "imports": ["stripe", "stripe", "pandas"], "image_url": ""}, {"objectID": "e75c117c1f5c9fdbef31f27e2df13e2a6e0ff9690f98452eaa7f16e7b41ec6e7", "tool": "Stripe", "notebook": "Get charges", "action": "", "tags": ["#stripe", "#charges", "#snippet", "#operations", "#dataframe"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides an overview of Stripe charges and their associated data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Get_charges.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Get_charges.ipynb", "imports": ["stripe", "stripe", "pandas"], "image_url": ""}, {"objectID": "3bc32324991101e1a88858f766923d627fe005351a5a1424287302bf586dca76", "tool": "Stripe", "notebook": "List all customers", "action": "", "tags": ["#stripe", "#api", "#customers", "#list", "#python", "#reference"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-18", "created_at": "2023-04-26", "description": "This notebook will list all customers from Stripe and explain how to use the Stripe API to do so. It is usefull for organizations that need to manage their customers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_List_all_customers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_List_all_customers.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "d28a5138a2cc901dc326745b136655e50ecd70b823da5cfeb35fa472d429af86", "tool": "Stripe", "notebook": "Retrieve a customer", "action": "", "tags": ["#stripe", "#payment", "#customer", "#api", "#python", "#retrieve", "#crud"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-18", "created_at": "2023-05-18", "description": "This notebook will show how to retrieve a customer using the Stripe API. It is usefull for organizations that need to manage customer payments.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Retrieve_a_customer.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Retrieve_a_customer.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "b812b9cab5dd404fcfa8a097f203dc0ddcfacd3728e8c14ed1205b11b0c2e92d", "tool": "Stripe", "notebook": "Update a customer", "action": "", "tags": ["#stripe", "#payment", "#customer", "#api", "#python", "#update", "#crud"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-18", "created_at": "2023-05-18", "description": "This notebook will show how to update a customer using the Stripe API. It is usefull for organizations that need to manage customer payments.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Update_a_customer.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Update_a_customer.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "07fa9fa6090c516e8d7233c9c4aceb4dafdcbbe96c685eda8ace2314d11df2df", "tool": "Supabase", "notebook": "Email Auth", "action": "", "tags": ["#supabase", "#auth", "#email", "#signin", "#signout", "#verification"], "author": "Sriniketh Jayasendil", "author_url": "http://linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-02-15", "description": "This notebook will utilize the Supabase DB and Authentication (with email verification) to Login users.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Supabase/Supabase_Email_Auth.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Supabase/Supabase_Email_Auth.ipynb", "imports": ["naas", "json", "supabase.create_client", "supabase.create_client"], "image_url": ""}, {"objectID": "9aacc71819205eb5f78d216ff9a089344dc6e6d906707f7c9281232f86dde6aa", "tool": "Telegram", "notebook": "Create crypto sentiment bot", "action": "", "tags": ["#telegram", "#sentiment", "#bot", "#naas_drivers", "#ai", "#investors"], "author": "Yaswanthkumar GOTHIREDDY", "author_url": "https://www.linkedin.com/in/yaswanthkumargothireddy/", "updated_at": "2023-04-12", "created_at": "2021-07-09", "description": "This notebook provides instructions on how to create a Telegram bot that tracks and analyzes sentiment around cryptocurrencies.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Telegram/Telegram_Create_crypto_sentiment_bot.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Telegram/Telegram_Create_crypto_sentiment_bot.ipynb", "imports": ["logging", "telegram.ext.*", "numpy", "naas_drivers.newsapi", "naas_drivers.sentiment", "datetime.datetime, timedelta"], "image_url": ""}, {"objectID": "87ed6f3653975a17927f01bcbe3f0385fb02c53b0860ded81236b9083dc9f890", "tool": "Text", "notebook": "Reformat Without Spaces", "action": "", "tags": ["#text", "#reformat", "#snippet", "#operations", "#spaces"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-10-10", "description": "This notebook reformats text by removing all spaces.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Text/Text_Reformat_Text_Without_Spaces.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Text/Text_Reformat_Text_Without_Spaces.ipynb", "imports": ["wordninja", "wordninja", "twotransactionswhichcameearlier,andfordecadesthisstymiedthedevelopmentofdecentralized digitalcurrency.Satoshi'sblockchainwasthefirstcredibledecentralizedsolution.Andnow,attentionis rapidlystartingtoshifttowardthissecondpartofBitcoin'stechnology,andhowtheblockchainconceptcanbe used for more than just money. Commonlycitedapplicationsincludeusingon-blockchaindigitalassetstorepresentcustomcurrenciesand financialinstruments(\"coloredcoins\"),theownershipofanunderlyingphysicaldevice(\"smartproperty\"), non-fungibleassetssuchasdomainnames(\"Namecoin\")aswellasmoreadvancedapplicationssuchas decentralizedexchange,financialderivatives,peer-to-peergamblingandon-blockchainidentityand reputationsystems.Another.antareaofinquiryis\"smartcontracts\"-systemswhichautomatically movedigitalassetsaccordingtoarbitrarypre-specifiedrules.Forexample,onemighthaveatreasurycontract oftheform\"AcanwithdrawuptoXcurrencyunitsperday,BcanwithdrawuptoYperday,AandBtogether canwithdrawanything,andAcanshutoffB'sabilitytowithdraw\".Thelogicalextensionofthisis decentralizedautonomousorganizations(DAOs)-long-termsmartcontractsthatcontaintheassetsand encodethebylawsofanentireorganization.WhatEthereumintendstoprovideisablockchainwithabuilt-in fullyfledgedTuring-completeprogramminglanguagethatcanbeusedtocreate\"contracts\"thatcanbeused toencodearbitrarystatetransitionfunctions,allowinguserstocreateanyofthesystemsdescribedabove,as well"], "image_url": ""}, {"objectID": "c547876f0d475350ad796940faaba28ebd0b65165eddb1123ebfb19116a70d35", "tool": "Thinkific", "notebook": "Get users", "action": "", "tags": ["#thinkific", "#education", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides a guide to acquiring and engaging users for the Thinkific platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Thinkific/Thinkific_Get_users.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Thinkific/Thinkific_Get_users.ipynb", "imports": ["naas_drivers.thinkific"], "image_url": ""}, {"objectID": "5b7aab31600212c5c3c1ebe3bde329691ef5e075e26bfad83e30b96a27406539", "tool": "Thinkific", "notebook": "Send users", "action": "", "tags": ["#thinkific", "#education", "#naas_drivers", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook allows you to send users automated emails from Thinkific.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Thinkific/Thinkific_Send_users.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Thinkific/Thinkific_Send_users.ipynb", "imports": ["naas_drivers.thinkific"], "image_url": ""}, {"objectID": "6e6ff26e13b5d362629eda7e97f100403c4263682ce83cd402f3e0fc0352fb3b", "tool": "TikTok", "notebook": "Get user stats", "action": "", "tags": ["#tiktok", "#user", "#stats", "#snippet", "#content"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-04-12", "description": "This notebook provides an analysis of user statistics on the popular social media platform, TikTok.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/TikTok/TikTok_Get_user_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/TikTok/TikTok_Get_user_stats.ipynb", "imports": ["TikTokAPI.TikTokAPI", "TikTokAPI.TikTokAPI", "nest_asyncio", "pandas"], "image_url": ""}, {"objectID": "35f614b16e2f264d1d38670c7ca5c0fe010e4c1cd828f2812e8a58faaeaee557", "tool": "TikTok", "notebook": "Get videos stats", "action": "", "tags": ["#tiktok", "#videos", "#stats", "#snippet", "#content"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-04-12", "description": "This notebook provides an analysis of video statistics on the popular social media platform, TikTok.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/TikTok/TikTok_Get_videos_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/TikTok/TikTok_Get_videos_stats.ipynb", "imports": ["TikTokAPI.TikTokAPI", "TikTokAPI.TikTokAPI", "nest_asyncio", "pandas"], "image_url": ""}, {"objectID": "bda97c0086e67e89ca713c307c134464ce0269066c8eb0398f343df74d61d809", "tool": "Trello", "notebook": "Create Card", "action": "", "tags": ["#trello", "#api", "#card", "#create", "#board", "#list"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-14", "created_at": "2023-07-14", "description": "This notebook would show you how to create a new card on a Trello board using the API. You could specify the board and list that you want the card to be created in, as well as its name, description, and any other relevant details, you can also create several cards.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Trello/Trello_Create_Card.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Trello/Trello_Create_Card.ipynb", "imports": ["requests", "naas", "ant\"},"], "image_url": ""}, {"objectID": "171b2e70749cf7235cefd7b019c057afa2196c1cdfdb0127320915d7609c3fc6", "tool": "Trello", "notebook": "Get Cards on a Board", "action": "", "tags": ["#trello", "#api", "#rest", "#cards", "#board", "#get"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-14", "created_at": "2023-07-14", "description": "This notebook get all cards from a board.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Trello/Trello_Get_Cards_on_a_Board.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Trello/Trello_Get_Cards_on_a_Board.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "e0c37b0b9b71eef4ba954737ebcf7889a1961540390e8d61dc9665188cdb9cc1", "tool": "Trello", "notebook": "Get Lists on a Board", "action": "", "tags": ["#trello", "#project", "#retrieve", "#snippet", "#operations", "#lists", "#board"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-14", "created_at": "2023-07-14", "description": "This notebook shows how to get the Lists on a Board.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Trello/Trello_Get_Lists_on_a_Board.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Trello/Trello_Get_Lists_on_a_Board.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "236ba6113e6987e489a54a8297398d0e66d2b9ee47911ef73dc0ad23a15df7c1", "tool": "Trello", "notebook": "Get board data", "action": "", "tags": ["#trello", "#project", "#board", "#snippet", "#operations", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides a way to access and analyze data from Trello boards.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Trello/Trello_Get_board_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Trello/Trello_Get_board_data.ipynb", "imports": ["trello_connector"], "image_url": ""}, {"objectID": "8bf5205524ae16d62ec58b8c3d98d25bf423d3cb87975758f7e440f537e38440", "tool": "Trello", "notebook": "List Boards", "action": "", "tags": ["#trello", "#api", "#boards", "#list", "#python", "#rest"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-11", "created_at": "2023-07-11", "description": "This notebook would allow you to retrieve a list of all the boards that you have access to in Trello. You could then use this information to perform further actions on the boards, such as listing the cards or updating their details.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Trello/Trello_List_Boards.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Trello/Trello_List_Boards.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "2eddf7c217470a6be61c299b0cd813d63d1c4f4786016a3b897ffcf20e36f628", "tool": "Twilio", "notebook": "Add SMS to Google Sheets spreadsheet", "action": "", "tags": ["#twilio", "#google", "#sheets", "#googlesheets", "#send"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-03-14", "description": "This notebook allows you to log all the messages sent through your Twilio Account into a Google Sheets document. Each new message will be added as a new row, along with the date, time, message ID, and message content. It's a convenient way to keep track of your Twilio activity and make sure you never miss an important message.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twilio/Twilio_Add_SMS_to_Google_Sheets_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twilio/Twilio_Add_SMS_to_Google_Sheets_spreadsheet.ipynb", "imports": ["datetime.datetime", "naas", "gspread", "gspread", "oauth2client.service_account.ServiceAccountCredentials", "oauth2client.service_account.ServiceAccountCredentials", "twilio.rest.Client", "twilio.rest.Client"], "image_url": ""}, {"objectID": "84f71a020625f18300825bd684ac0985e2fc5b45f88839cfd9c176d5271a0f8a", "tool": "Twilio", "notebook": "Make Call", "action": "", "tags": ["#twilio", "#project", "#call", "#mobile"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2022-10-05", "description": "This notebook allows us to make a phone call to a verified twilio number. It also has different parameters to customize the output of the voice call.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twilio/Twilio_Make_Call.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twilio/Twilio_Make_Call.ipynb", "imports": ["time", "naas", "twilio.rest.Client", "twilio.rest.Client"], "image_url": ""}, {"objectID": "cf796abab887f0c032b38c2ac5c95b86f4245e69d66aea9a8d7b7e5cc5dac186", "tool": "Twilio", "notebook": "Send SMS", "action": "", "tags": ["#twilio", "#project", "#send", "#sms", "#snippet", "#operations", "#dataframe"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows you to send SMS messages using the Twilio API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twilio/Twilio_Send_SMS.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twilio/Twilio_Send_SMS.ipynb", "imports": ["twilio.rest.Client", "twilio.rest.Client"], "image_url": ""}, {"objectID": "9a33bfd7731b24971b0629ffb86419d5e7e45605566c208ce2e82a5e93b81b10", "tool": "Twilio", "notebook": "Send SMS messages for Google Calendar Events", "action": "", "tags": ["#googlecalendar", "#twilio", "#notification", "#event"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil", "updated_at": "2023-06-20", "created_at": "2023-03-17", "description": "This notebook sends an SMS notification for upcoming the next event you're attending in your Google Calendar.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twilio/Twilio_Send_SMS_Google_Calendar_Events.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twilio/Twilio_Send_SMS_Google_Calendar_Events.ipynb", "imports": ["naas", "datetime.datetime", "pytz", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "twilio.rest.Client", "twilio.rest.Client", "pickle"], "image_url": ""}, {"objectID": "b83bc56ec2d52348e7769a349a95cffeda2100c29daae44ab84d3b54744bedfa", "tool": "Twitter", "notebook": "Add member to list", "action": "", "tags": ["#twitter", "#tweepy", "#pandas", "#twitterautomation", "#twitterlistmembers", "#snippet"], "author": "Kaushal Krishna", "author_url": "https://www.linkedin.com/in/kaushal-krishna-a48959153", "updated_at": "2023-04-12", "created_at": "2023-01-13", "description": "This notebook adds a member to the list of a particular user.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Add_member_to_list.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Add_member_to_list.ipynb", "imports": ["tweepy", "pandas", "naas"], "image_url": ""}, {"objectID": "ac4829f37f52f9554372ffdc6920da0099d83854bdd4d6e8e18efcc86af6fa37", "tool": "Twitter", "notebook": "Get followers list", "action": "", "tags": ["#twitter", "#api", "#followers", "#list", "#get", "#developer"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-05-23", "created_at": "2023-05-17", "description": "This notebook will demonstrate how to get a list of followers from Twitter using the API. This feature is only available on paid plan.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_followers_list.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_followers_list.ipynb", "imports": ["naas", "tweepy", "tweepy.Stream", "json", "pandas"], "image_url": ""}, {"objectID": "871bb71e3870638a5e7cbe6c68554487b055d3eadc0653cc0d229d556e7d6438", "tool": "Twitter", "notebook": "Get members of list", "action": "", "tags": ["#twitter", "#tweepy", "#pandas", "#twitterautomation", "#twitterlistmembers", "#snippet"], "author": "Kaushal Krishna", "author_url": "https://www.linkedin.com/in/kaushal-krishna-a48959153", "updated_at": "2023-04-12", "created_at": "2023-01-11", "description": "This notebook gets the members of a list of a particular user. Private list members will only be shown if the authenticated user owns the specified list. It can be used to enable people to curate and organize new Lists based on the membership information", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_members_of%20list.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_members_of%20list.ipynb", "imports": ["tweepy", "pandas", "naas"], "image_url": ""}, {"objectID": "2cfc5fc37a64737391240ba4c7ccac0fbee076d183decdeeec6480f97ec8ec20", "tool": "Twitter", "notebook": "Get posts stats", "action": "", "tags": ["#twitter", "#post", "#comments", "#naas_drivers", "#snippet", "#content"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-04-12", "description": "This notebook provides an analysis of Twitter posts, including statistics on user engagement and post performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_posts_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_posts_stats.ipynb", "imports": ["naas_drivers.linkedin, hubspot", "pandas", "numpy", "naas", "datetime.datetime, timedelta", "requests", "json", "tweepy"], "image_url": ""}, {"objectID": "d50dc5991bf4fe05f69298b0b37857587e63f47d21cab0b07fbf0c4f6d4bf0b7", "tool": "Twitter", "notebook": "Get tweets from search", "action": "", "tags": ["#twitter", "#ifttt", "#naas_drivers", "#snippet", "#content", "#dataframe"], "author": "Dineshkumar Sundaram", "author_url": "https://github.com/dineshh912", "updated_at": "2023-04-12", "created_at": "2021-09-29", "description": "This notebook allows users to search and retrieve tweets from Twitter.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_tweets_from_search.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_tweets_from_search.ipynb", "imports": ["tweepy", "pandas"], "image_url": ""}, {"objectID": "4414785952831aae6f4b0f2ac5664a5fe233cf83950b1b06ed30e869c59efbfb", "tool": "Twitter", "notebook": "Get tweets stats from profile", "action": "", "tags": ["#twitter", "#tweets", "#scrap", "#snippet", "#content", "#dataframe"], "author": "Tannia Dubon", "author_url": "https://www.linkedin.com/in/tanniadubon/", "updated_at": "2023-04-12", "created_at": "2021-12-27", "description": "This notebook allows users to retrieve and analyze statistics from a Twitter profile.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_tweets_stats_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_tweets_stats_from_profile.ipynb", "imports": ["os", "re", "pandas"], "image_url": ""}, {"objectID": "ebea8c3910c8f62394c5ff6901940b5e54a520d9531e84a90d22b61c23a8be00", "tool": "Twitter", "notebook": "Get user data", "action": "", "tags": ["#twitter", "#ifttt", "#naas_drivers", "#snippet", "#content", "#dataframe"], "author": "Dineshkumar Sundaram", "author_url": "https://github.com/dineshh912", "updated_at": "2023-04-12", "created_at": "2021-09-29", "description": "This notebook provides a way to access and analyze data from Twitter users.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_user_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_user_data.ipynb", "imports": ["tweepy", "pandas"], "image_url": ""}, {"objectID": "dfd78b97b964be28292a8cf054deb633939e1af86deb1831414ef29b59722f8f", "tool": "Twitter", "notebook": "Post text and image", "action": "", "tags": ["#twitter", "#ifttt", "#naas_drivers", "#snippet", "#content"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook allows users to post text and images to their Twitter account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Post_text_and_image.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Post_text_and_image.ipynb", "imports": ["naas", "naas_drivers"], "image_url": ""}, {"objectID": "d3bc43603e97ccc16cae1bc8045699ce7340ce42c481cd1502c91450da209673", "tool": "Twitter", "notebook": "Remove member from list", "action": "", "tags": ["#twitter", "#tweepy", "#pandas", "#twitterautomation", "#twitterlistmembers", "#snippet"], "author": "Kaushal Krishna", "author_url": "https://www.linkedin.com/in/kaushal-krishna-a48959153", "updated_at": "2023-04-12", "created_at": "2023-01-20", "description": "This notebook removes a single member from member list.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Remove_member_from_list.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Remove_member_from_list.ipynb", "imports": ["tweepy", "pandas", "naas"], "image_url": ""}, {"objectID": "f613ea52f869a50913e79cc1bf1af68d3f31d6ca2f3cd5af1c1d77cdaa48ba50", "tool": "Twitter", "notebook": "Schedule posts", "action": "", "tags": ["#twitter", "#automation", "#ifttt", "#naas_drivers", "#gsheet", "#content"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook allows you to plan and schedule posts to your Twitter account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Schedule_posts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Schedule_posts.ipynb", "imports": ["datetime.datetime", "naas_drivers", "naas"], "image_url": ""}, {"objectID": "49bb50d18a5fbfeb26b133b99b0f52e247e3ff104935fe78c1b7aad18334c7ff", "tool": "Twitter", "notebook": "Send posts stats to Notion", "action": "", "tags": ["#twitter", "#post", "#comments", "#naas_drivers", "#snippet", "#content", "#notion"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maixmejublou", "updated_at": "2023-04-12", "created_at": "2022-06-09", "description": "This notebook allows you to track and analyze your Twitter posts and send the stats to Notion for further analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Send_posts_stats_to_Notion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Send_posts_stats_to_Notion.ipynb", "imports": ["naas", "naas_drivers.notion", "re", "regex", "numpy.inf", "emoji", "emoji", "tweepy", "pandas", "json", "typing.List", "datetime", "pydash"], "image_url": ""}, {"objectID": "a02d4dd206c67190a9b400df37c1a99e3f8213b2108561f054f3d2707589f920", "tool": "Typeform", "notebook": "Log New Entries In Notion Databases", "action": "", "tags": ["#typeform", "#notion", "#operations", "#automation"], "author": "Sanjeet Attili", "author_url": "https://billowy-lemming-95e.notion.site/f8e44ff261564c76b3bb80e6edb171a9?v=1d2a506563fe4082b71e78695185962e, which has all the questions asked in the typeform as column names and their responses as entries.\n\nThis output database consists of only 5 responses collected over the sample typeform.", "updated_at": "2023-04-12", "created_at": "2022-03-31", "description": "## Input", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Typeform/Typeform_Log_New_Typeform_Entries_In_Notion_Databases.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Typeform/Typeform_Log_New_Typeform_Entries_In_Notion_Databases.ipynb", "imports": ["naas_drivers.notion", "typeform.Typeform", "naas, pandas", "requests", "datetime.datetime", "pydash"], "image_url": ""}, {"objectID": "34d7d038a426cecb7dc11a0dbedab7b790e8494adc94264826f3259f8979e919", "tool": "US Bureau of Labor Statistics", "notebook": "Follow CPI", "action": "", "tags": ["#inflation", "#us", "#BLS", "#naas", "#scheduler", "#asset", "#snippet", "#automation", "#ai", "#analytics"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/j%C3%A9r%C3%A9my-ravenel-8a396910/", "updated_at": "2023-04-12", "created_at": "2022-07-16", "description": "This notebook provides an analysis of the US Bureau of Labor Statistics Consumer Price Index (CPI) over time.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/US%20Bureau%20of%20Labor%20Statistics/US_Bureau_of_Labor_Statistics_Follow_CPI.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/US%20Bureau%20of%20Labor%20Statistics/US_Bureau_of_Labor_Statistics_Follow_CPI.ipynb", "imports": ["pandas", "cpi", "seaborn", "matplotlib.pyplot", "naas", "naas_drivers.plotly"], "image_url": ""}, {"objectID": "a83d4ed0c1d03a2da02745a16b4d98f9d5cc99d5c0130126ecd8d4f24961496f", "tool": "Vizzu", "notebook": "Create Animated Bar Chart", "action": "", "tags": ["#vizzu", "#animation", "#bar-chart", "#data-visualization", "#data-science", "#python"], "author": "Alexandre Petit", "author_url": "https://www.linkedin.com/in/alexandre-petit-24a87a219/", "updated_at": "2023-04-25", "created_at": "2023-04-18", "description": "This notebook would allow you to create an animated bar chart. It will show the oil production evolution by country year after year.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Animated_Bar_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Animated_Bar_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style, DisplayTarget", "ipyvizzu.Chart, Data, Config, Style, DisplayTarget"], "image_url": ""}, {"objectID": "6a458ee798291f3b3f7887e81b2068fe7be5b41fb8db37d7dcffcef94f1bb500", "tool": "Vizzu", "notebook": "Create Animated Pie Chart", "action": "", "tags": ["#vizzu", "#animation", "#piechart", "#data", "#visualization", "#python"], "author": "Alexandre Petit", "author_url": "https://www.linkedin.com/in/alexandre-petit-24a87a219/", "updated_at": "2023-05-10", "created_at": "2023-04-25", "description": "This notebook will show how to create an animated pie chart with Vizzu. An animated pie chart can be useful for visualizing changes or transitions in categorical data over time.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Animated_Pie_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Animated_Pie_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style, DisplayTarget", "ipyvizzu.Chart, Data, Config, Style, DisplayTarget"], "image_url": ""}, {"objectID": "830f9c8e609c3df8a57c70b327d9eb459a1082c8a588947645d08c7b6b1b6868", "tool": "Vizzu", "notebook": "Create Column Chart", "action": "", "tags": ["#vizzu", "#analytics", "#dataviz", "#chart", "#graph", "#columnchart"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-27", "description": "This notebook template on Vizzu is designed to help users create visually appealing column charts. Vizzu is a powerful data visualization tool that allows users to easily create interactive and engaging charts and graphs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Column_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Column_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style", "ipyvizzu.Chart, Data, Config, Style"], "image_url": ""}, {"objectID": "34436bb48b9455e15c60d687a2bb79c6e277c4a938966a5d87c5be2467bb22b2", "tool": "Vizzu", "notebook": "Create Grouped Column Chart", "action": "", "tags": ["#analytics", "#dataviz", "#chart", "#graph", "#groupedbarchart"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-27", "description": "This notebook template on Vizzu is designed to help users create visually appealing grouped column charts. Vizzu is a powerful data visualization tool that allows users to easily create interactive and engaging charts and graphs", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Grouped_Column_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Grouped_Column_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style", "ipyvizzu.Chart, Data, Config, Style"], "image_url": ""}, {"objectID": "9f4adb5f22c3959ac5b2c8004c963c98ea745b2d837e59960fc685f3844ca005", "tool": "Vizzu", "notebook": "Create Line Chart", "action": "", "tags": ["#analytics", "#dataviz", "#chart", "#graph", "#waterfallChart"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-03", "description": "This notebook template on Vizzu is designed to help users create visually appealing line charts. Vizzu is a powerful data visualization tool that allows users to easily create interactive and engaging charts and graphs", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Line_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Line_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style", "ipyvizzu.Chart, Data, Config, Style"], "image_url": ""}, {"objectID": "cc379f1a45e8d669d37d8156179c77eb989a3aad869dae103093651aedb99c62", "tool": "Vizzu", "notebook": "Create Stacked Column Chart", "action": "", "tags": ["#analytics", "#dataviz", "#chart", "#graph", "#stackedbarchart"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-27", "description": "This notebook template on Vizzu is designed to help users create visually appealing stacked column charts. Vizzu is a powerful data visualization tool that allows users to easily create interactive and engaging charts and graphs", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Stacked_Column_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Stacked_Column_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style", "ipyvizzu.Chart, Data, Config, Style"], "image_url": ""}, {"objectID": "c7522a696b863bf686badace2757c296a18d213491ddc905ae5edd1c2c547da6", "tool": "Vizzu", "notebook": "Create Waterfall Chart", "action": "", "tags": ["#analytics", "#dataviz", "#chart", "#graph", "#waterfallChart"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-03", "description": "This notebook template on Vizzu is designed to help users create visually appealing waterfall charts. Vizzu is a powerful data visualization tool that allows users to easily create interactive and engaging charts and graphs", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Waterfall_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Waterfall_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style", "ipyvizzu.Chart, Data, Config, Style"], "image_url": ""}, {"objectID": "78e0951d9b24d4a7bccd167a4af767b31a9916c4adbbdba076453909d87a7484", "tool": "WAQI", "notebook": "Display AQI on worldmap", "action": "", "tags": ["#waqi", "#airquality", "#api", "#data", "#city", "#stations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook displays AQI on worldmap.
\n\nAir Quality Index Scale:\n- 0 - 50: Good - Air quality is considered satisfactory, and air pollution poses little or no risk\n- 51 - 100: Moderate - Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to air pollution.\n- 101-150: Unhealthy for Sensitive Groups - Members of sensitive groups may experience health effects. The general public is not likely to be affected.\n- 151-200: Unhealthy - Everyone may begin to experience health effects; members of sensitive groups may experience more serious health effects.\n- 201-300: Very Unhealthy - Health warnings of emergency conditions. The entire population is more likely to be affected.\n- 300+: Hazardous - Health alert: everyone may experience more serious health effects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WAQI/WAQI_Display_AQI_on_worldmap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WAQI/WAQI_Display_AQI_on_worldmap.ipynb", "imports": ["requests", "naas", "pandas", "plotly.express"], "image_url": ""}, {"objectID": "1b1d23da1ea44c9fb55dfe63eddcbee38236d37467a51606381cfd20353906f4", "tool": "WAQI", "notebook": "Get daily air quality data by coordinates", "action": "", "tags": ["#waqi", "#airquality", "#api", "#data", "#city", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will demonstrate how to use the WAQI API to get daily air quality data for a city.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WAQI/WAQI_Get_daily_air_quality_data_by_coordinates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WAQI/WAQI_Get_daily_air_quality_data_by_coordinates.ipynb", "imports": ["requests", "naas", "pydash", "pprint.pprint"], "image_url": ""}, {"objectID": "71f15185e22b83a858312830275117c8f7e91e307ceb5b7d28a70d0629d73c63", "tool": "WAQI", "notebook": "Get daily air quality data for a city", "action": "", "tags": ["#waqi", "#airquality", "#api", "#data", "#city", "#python"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will demonstrate how to use the WAQI API to get daily air quality data for a city.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WAQI/WAQI_Get_daily_air_quality_data_for_a_city.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WAQI/WAQI_Get_daily_air_quality_data_for_a_city.ipynb", "imports": ["requests", "naas", "pydash", "pprint.pprint"], "image_url": ""}, {"objectID": "17d2397824593cc21b5d523eadcb2da7822e926c5cc0a4109deae7542ff97df7", "tool": "WAQI", "notebook": "Get stations by coordinates", "action": "", "tags": ["#waqi", "#airquality", "#api", "#data", "#city", "#stations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will demonstrate how to get stations within a given lat/lng bounds.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WAQI/WAQI_Get_stations_by_coordinates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WAQI/WAQI_Get_stations_by_coordinates.ipynb", "imports": ["requests", "naas", "pandas", "plotly.express"], "image_url": ""}, {"objectID": "3d0747d79e0168df75adfc3ed3b500e5308bda1d114f932c5972004833cef961", "tool": "WAQI", "notebook": "Search station by name", "action": "", "tags": ["#waqi", "#airquality", "#api", "#data", "#city", "#python", "#stations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will demonstrate how to search stations by name using AQI API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WAQI/WAQI_Search_station_by_name.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WAQI/WAQI_Search_station_by_name.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "7c5471bb20ca17ba8b8ca70d01df4a2b65aa88a1e0c7810949b9ae13d5735662", "tool": "WSR", "notebook": "WHI Create indicator", "action": "", "tags": ["#wsr", "#whi", "#indicators", "#opendata", "#worldsituationroom", "#analytics", "#dataframe", "#image"], "author": "Peter Turner", "author_url": "https://www.linkedin.com/in/peter-turner-0839aa116/", "updated_at": "2023-04-12", "created_at": "2022-03-10", "description": "This notebook creates an indicator to measure the performance of the WSR-WHI portfolio.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WSR/WHI_Create_indicator.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WSR/WHI_Create_indicator.ipynb", "imports": ["pandas", "PIL.Image, ImageDraw, ImageFont", "datetime.date"], "image_url": ""}, {"objectID": "cc4d4bf571af50f16896b07354de0083ff3fb16b3b12963460441fda9ea72ffe", "tool": "WSR", "notebook": "Get daily Covid19 active cases trend JHU", "action": "", "tags": ["#wsr", "#covid", "#active-cases", "#plotly", "#opendata", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "This notebook provides a daily trend of Covid19 active cases from the Johns Hopkins University (JHU) dataset.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WSR/WSR_Get_daily_Covid19_active_cases_trend_JHU.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WSR/WSR_Get_daily_Covid19_active_cases_trend_JHU.ipynb", "imports": ["pandas", "datetime.datetime", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "aab90eca5a5dad874fdf39c39fe60d29d579c385566f7156bea44d68c7d6f84b", "tool": "WSR", "notebook": "Get daily Covid19 active cases worldmap JHU", "action": "", "tags": ["#wsr", "#covid", "#active-cases", "#analytics", "#plotly", "#automation", "#naas", "#opendata", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides a daily world map of active Covid-19 cases based on data from the Johns Hopkins University.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WSR/WSR_Get_daily_Covid19_active_cases_worldmap_JHU.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WSR/WSR_Get_daily_Covid19_active_cases_worldmap_JHU.ipynb", "imports": ["pandas", "datetime.datetime", "dataprep.clean.clean_country", "dataprep.clean.clean_country", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "20d2d1915c03323426f0cc05b016a752a34555d15cd4f08ab70992b5c1b93ec4", "tool": "WhatsApp", "notebook": "Create heatmap of activities", "action": "", "tags": ["#whatsapp", "#naas_drivers", "#naas", "#visualisation", "#chatminers", "#heatmap"], "author": "Hamid Mukhtar", "author_url": "https://www.linkedin.com/in/mukhtar-hamid/", "updated_at": "2023-05-31", "created_at": "2023-05-31", "description": "This notebook creates a heatmap of your chat activities.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WhatsApp/WhatsApp_Create_heatmap_of_activities.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WhatsApp/WhatsApp_Create_heatmap_of_activities.ipynb", "imports": ["chatminer", "chatminer.chatparsers.WhatsAppParser", "chatminer.visualizations", "matplotlib.pyplot"], "image_url": ""}, {"objectID": "ec40932392f591f65891e1b562c477459f79dd9c603a6fec6aeb8a299504ba47", "tool": "WhatsApp", "notebook": "Transform chat txt to dataframe", "action": "", "tags": ["#python", "#pandas", "#regex", "#whatsapp", "#chats"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-05-31", "created_at": "2023-05-31", "description": "This notebook transforms your WhatsApp chat export from txt to a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WhatsApp/WhatsApp_Transform_chat_txt_to_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WhatsApp/WhatsApp_Transform_chat_txt_to_dataframe.ipynb", "imports": ["re", "pandas"], "image_url": ""}, {"objectID": "cbe5b94b80eae61d57207cec803c67f81a0575afcaed7275c80fc9d075f96727", "tool": "Wikipedia", "notebook": "List largest cities in the world", "action": "", "tags": ["#wikipedia", "#list", "#cities", "#largest", "#world", "#data"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook will show how to extract the list of the largest cities in the world using pandas.read_html() on Wikipedia.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Wikipedia/Wikipedia_List_largest_cities_in_the_world.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Wikipedia/Wikipedia_List_largest_cities_in_the_world.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "4db4cd15f329e1e7b0c097969fed6832b0cb73eb417217b92a97760ed9346872", "tool": "WindsorAI", "notebook": "Create Dash app to query AP", "action": "", "tags": ["#tool", "#naas_drivers", "#naas", "#dash", "#marketing", "#automation", "#ai", "#analytics"], "author": "Elia Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-04-12", "created_at": "2022-11-07", "description": "This notebook enable anyone with a [Windsor.ai](https://windsor.ai/) account to visualy query the API with a Dash app.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WindsorAI/WindsorAI_Create_Dash_app_to_query_AP.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WindsorAI/WindsorAI_Create_Dash_app_to_query_AP.ipynb", "imports": ["json", "os", "requests", "pandas", "plotly.express", "dash.Dash, html, dcc, Input, Output, State, callback", "dash.dash_table.DataTable", "dash.exceptions.PreventUpdate", "jupyter_dash.JupyterDash", "dash_bootstrap_components", "dash_bootstrap_templates.load_figure_template"], "image_url": ""}, {"objectID": "193771e0df5a14495539f0f8a08b45fd29dedf23a589f38b21a52cda9ef2c528", "tool": "WorldBank", "notebook": "GDP contributors", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides an analysis of the countries and sectors that contribute the most to the World Bank's Gross Domestic Product (GDP).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_GDP_contributors.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_GDP_contributors.ipynb", "imports": ["pandas", "pandas_datareader.wb", "plotly.graph_objects"], "image_url": ""}, {"objectID": "24fff5750f4dca229fa7019f91ec0b2298e646b23ee6db1ee2cbafc7ee510970", "tool": "WorldBank", "notebook": "GDP per capita and growth", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook provides an analysis of GDP per capita and growth data from the World Bank.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_GDP_per_capita_and_growth.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_GDP_per_capita_and_growth.ipynb", "imports": ["pandas", "numpy", "plotly.graph_objects", "pandas_datareader.wb", "naas_drivers.plotly"], "image_url": ""}, {"objectID": "56e6d83b1d5575e03cc57cf51cadc47b507a8be1e7159034e124b79ed8d3484d", "tool": "WorldBank", "notebook": "GDP per country and evolution", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "Objective : allows to visualize the distribution of GDP per capita and the GDP growth in the world. Click on the country on the map or select it to see the details info\n\nData :\nGDP PER CAPITA (CURRENT US$)\nGDP GROWTH (ANNUAL %)\n\nby countries, agregated by region\n\nSources:\n\nWorld Bank national accounts data,\nOECD National Accounts data files.\n\n\nProduction : Team Denver 2020/04/20 (MyDigitalSchool)", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_GDP_per_country_and_evolution.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_GDP_per_country_and_evolution.ipynb", "imports": ["pandas", "numpy", "plotly.graph_objects", "pandas_datareader.wb"], "image_url": ""}, {"objectID": "5bcd4bf5d4a562d15a90cc3079592749caa8cee07e3fc286953f7852b80f2daf", "tool": "WorldBank", "notebook": "Gini index", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides an analysis of the Gini index, a measure of income inequality, from the World Bank.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_Gini_index.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_Gini_index.ipynb", "imports": ["pandas", "pandas_datareader.wb", "plotly.graph_objects", "plotly.express"], "image_url": ""}, {"objectID": "9eff7cf860c115ac4cd5b982a41c4d7b8702252d797d1a3b2f40c5a45d1f01ab", "tool": "WorldBank", "notebook": "Most populated countries", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly", "#matplotlib"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "**Notebook d'exemple pour classer les pays les plus peupl\u00e9s**", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_Most_populated_countries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_Most_populated_countries.ipynb", "imports": ["pandas", "matplotlib.pyplot", "requests", "io", "numpy", "plotly.graph_objects", "plotly.express", "pydrive.auth.GoogleAuth", "pydrive.drive.GoogleDrive", "google.colab.auth", "oauth2client.client.GoogleCredentials", "pandas.DataFrame", "plotly.graph_objects"], "image_url": ""}, {"objectID": "8b8c44156453589069394ba1341397036c04752815f24e4b25755a89994eefd5", "tool": "WorldBank", "notebook": "Richest countries top10", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides a comparison of the top 10 wealthiest countries in the world according to the World Bank.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_Richest_countries_top10.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_Richest_countries_top10.ipynb", "imports": ["pandas", "pandas_datareader.wb", "plotly.graph_objects"], "image_url": ""}, {"objectID": "a21ffefc3ea5fbec9b0555ed60b73a5fc6e516ff98c5bb53dcf085114f512c6b", "tool": "WorldBank", "notebook": "World employment by sector", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "**Objective**\n\nThis graph compares the world distribution of employment by sector with the country distribution. Select the country to visualize which sector is dominant.\n\nData\nby countries, by region\n\nSource\nInternational Labour Organization, ILOSTAT database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_World_employment_by_sector.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_World_employment_by_sector.ipynb", "imports": ["math", "pandas", "datetime.datetime", "plotly.offline.iplot, plot, download_plotlyjs, init_notebook_mode", "plotly.graph_objects", "plotly.subplots.make_subplots"], "image_url": ""}, {"objectID": "115506753040f989d986e2a3e2f5e36b8bbe12f26be33950b4f3fd46d6334ab7", "tool": "WorldBank", "notebook": "World population and density", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides an analysis of the world population and population density data from the World Bank.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_World_population_and_density.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_World_population_and_density.ipynb", "imports": ["pandas", "numpy", "plotly.express"], "image_url": ""}, {"objectID": "0483468fa84c29572e8b9a896e59fad9278a3d1b600646b604c19328fde51ea1", "tool": "Worldometer", "notebook": "World population evolution and projections", "action": "", "tags": ["#worldometer", "#opendata", "#population", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-05", "description": "This notebook provides an overview of the current and projected population of the world, as tracked by Worldometer.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Worldometer/Worldometer_World_population_evolution_and_projections.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Worldometer/Worldometer_World_population_evolution_and_projections.ipynb", "imports": ["pandas", "plotly.express", "bs4.BeautifulSoup", "requests"], "image_url": ""}, {"objectID": "d53fcc695712505d6f768a768aaafc0bd1e79a5046278e1248620ddf40433a96", "tool": "XGBoost", "notebook": "Binary classification example with hyper-parameters optimization", "action": "", "tags": ["#xgboost", "#snippet", "#classification", "#tabular", "#cross-validation", "#optimization", "#modeling"], "author": "Oussama El Bahaoui", "author_url": "https://www.linkedin.com/in/oelbahaoui/", "updated_at": "2023-04-12", "created_at": "2022-11-02", "description": "This notebook provides an example of using XGBoost to perform binary classification with hyper-parameter optimization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/XGBoost/XGBoost_Binary_classification_example_with_hyper-parameters_optimization.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/XGBoost/XGBoost_Binary_classification_example_with_hyper-parameters_optimization.ipynb", "imports": ["pandas", "sklearn.datasets.load_breast_cancer", "sklearn.model_selection.train_test_split", "sklearn.model_selection.GridSearchCV", "sklearn.metrics.accuracy_score", "xgboost.XGBClassifier", "xgboost.Booster, DMatrix"], "image_url": ""}, {"objectID": "495b6a709d9e2db6eca221adee7ec474d35a3b288156890ae1de6f6ee4a07f92", "tool": "XML", "notebook": "Transform sitemap to dataframe", "action": "", "tags": ["#xml", "#file", "#tool", "#operations", "#automation", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook demonstrates how to convert an XML sitemap into a dataframe for further analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/XML/XML_Transform_sitemap_to_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/XML/XML_Transform_sitemap_to_dataframe.ipynb", "imports": ["naas", "json", "xmltodict", "xmltodict", "pandas", "requests"], "image_url": ""}, {"objectID": "a898dc1a3589c789666fbcc6e4c8c13fbabeba4972e66345fa8ce99f66167ca4", "tool": "YahooFinance", "notebook": "Candlestick chart", "action": "", "tags": ["#yahoofinance", "#trading", "#yfin", "#investors", "#snippet", "#plotly"], "author": "Carlo Occhiena", "author_url": "https://www.linkedin.com/in/carloocchiena/", "updated_at": "2023-04-12", "created_at": "2022-02-15", "description": "This notebook provides a visual representation of stock market data using a candlestick chart from YahooFinance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Candlestick_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Candlestick_chart.ipynb", "imports": ["datetime", "pandas_datareader", "mplfinance", "mplfinance", "yfinance", "yfinance"], "image_url": ""}, {"objectID": "137e04149304fa44a56b90ffdd1ae4135bed5ecf9d7a1af519b6a9719dbda2e7", "tool": "YahooFinance", "notebook": "Chat about ANSYS trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#anss"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for ANSYS. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_ANSYS_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_ANSYS_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "67d1435531a07c950b1034eedb278afd390cb91499210c3a5b6e372bd0909c05", "tool": "YahooFinance", "notebook": "Chat about ASML Holding N.V. New York Registry Shares trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#asml"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for ASML Holding N.V. New York Registry Shares. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_ASML_Holding_N.V._New_York_Registry_Shares_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_ASML_Holding_N.V._New_York_Registry_Shares_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "cfeee65d70f77082037e63eed71c1df927d6f474625dd21705735107f8caedf2", "tool": "YahooFinance", "notebook": "Chat about Adobe trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#adbe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Adobe. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Adobe_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Adobe_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "c12297fc39de90f732fdf6e8727dcee50d20309abd34aa0c5567b7e6ec0dbfd9", "tool": "YahooFinance", "notebook": "Chat about Advanced Micro Devices trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#amd"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Advanced Micro Devices. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Advanced_Micro_Devices_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Advanced_Micro_Devices_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "9b97c945f2437407a47bd3c57b695332090e77259b683d56ba77ae2829779bbf", "tool": "YahooFinance", "notebook": "Chat about Airbnb trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#abnb"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Airbnb. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Airbnb_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Airbnb_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a3ac6eeaac07c948b7136fc66fcd8d8b5b6ff19d8526bd4971d534ed7db8540b", "tool": "YahooFinance", "notebook": "Chat about Align Technology trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#algn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Align Technology. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Align_Technology_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Align_Technology_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "8712b081e23f2ec72cc749b6e163ff2a8ea02a58e4d2604f3480fe3760325d16", "tool": "YahooFinance", "notebook": "Chat about Alphabet trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#googl"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Alphabet. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Alphabet_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Alphabet_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "7442a91c5c92f0b2977cc8c63ebb89e6fc14b1eeffb74c140ae9019e41b949a8", "tool": "YahooFinance", "notebook": "Chat about Amazon trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#amzn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Amazon. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Amazon_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Amazon_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a35c22807ebe68c9343d8e68f3c9cdb5aae52f18c14e8768b8a7c32f63693aaa", "tool": "YahooFinance", "notebook": "Chat about American Electric Power Company trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#aep"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for American Electric Power Company. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_American_Electric_Power_Company_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_American_Electric_Power_Company_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "33b5fb710b3ab35effbacf6ca747ef7544f8018bbe23f9263d94e862d3ed9fdb", "tool": "YahooFinance", "notebook": "Chat about Amgen trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#amgn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Amgen. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Amgen_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Amgen_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "c0003ed1cef81656178f14fe01f3d4900e8b27b7ff09e5690b0f7df7c1013e43", "tool": "YahooFinance", "notebook": "Chat about Analog Devices trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#adi"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Analog Devices. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Analog_Devices_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Analog_Devices_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "55878e0bb39db7f7ec9d91383696db9cae1303a071708a3b69641496abe040f1", "tool": "YahooFinance", "notebook": "Chat about Applied Materials trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#amat"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Applied Materials. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Applied_Materials_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Applied_Materials_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "1d619046c14806a9c672847841c7e578a8c6d552c21bb23c2d1f02ca1233c9a4", "tool": "YahooFinance", "notebook": "Chat about AstraZeneca PLC American Depositary Shares trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#azn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for AstraZeneca PLC American Depositary Shares. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_AstraZeneca_PLC_American_Depositary_Shares_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_AstraZeneca_PLC_American_Depositary_Shares_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "4577fe5e924ca13d2708663e159f55caa969839e3ee60eb9f7128cdc84d94e3b", "tool": "YahooFinance", "notebook": "Chat about Atlassian Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#team"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Atlassian Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Atlassian_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Atlassian_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b77e6bea8afd054998edd60a9575cb7f4eb4f1892dc32bcf15c86bc383f7c314", "tool": "YahooFinance", "notebook": "Chat about Automatic Data Processing trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#adp"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Automatic Data Processing. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Automatic_Data_Processing_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Automatic_Data_Processing_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "1a78f98e507fb0f7d58e432604b0356801c72c976637ac9cf24bca82e55f48dd", "tool": "YahooFinance", "notebook": "Chat about Baker Hughes Company trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#bkr"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Baker Hughes Company. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Baker_Hughes_Company_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Baker_Hughes_Company_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "3fcc9d0b81420c95293ee3b9256bc3ba3d0c7d19f17cb2885585cc51038899ad", "tool": "YahooFinance", "notebook": "Chat about Biogen trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#biib"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Biogen. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Biogen_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Biogen_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b93ca207cc0d90cfb0098f8736b098162e23b2f9b3445b31a2edfc7a1aeadfa7", "tool": "YahooFinance", "notebook": "Chat about Broadcom trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#avgo"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Broadcom. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Broadcom_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Broadcom_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "6a5cd431c38902652eea214a15e9d794ffa74c375597df08d3fe7fe83d1ab47c", "tool": "YahooFinance", "notebook": "Chat about CSX Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#csx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for CSX Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_CSX_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_CSX_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "cab83cd9dbe7c71e0d929f902dfd749a72ebf0f7733d67e3870d6315a5fda09a", "tool": "YahooFinance", "notebook": "Chat about Cadence Design Systems trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#cdns"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Cadence Design Systems. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Cadence_Design_Systems_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Cadence_Design_Systems_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "d0b0c75e64a292c26ebcd750fa514e2ca247f8ecc5350f8c1370fc3daa05b808", "tool": "YahooFinance", "notebook": "Chat about Charter Communications New trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#chtr"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Charter Communications New. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Charter_Communications_New_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Charter_Communications_New_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "547f340cd1b93652c1ae40ebeae5f37ca1e461754823a20e5a771dbcce6ec85a", "tool": "YahooFinance", "notebook": "Chat about Cintas Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ctas"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Cintas Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Cintas_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Cintas_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "015bf4ca3350b1404278b0368261ca1222c6f592a41d066483c208706da73c64", "tool": "YahooFinance", "notebook": "Chat about Cisco Systems (DE) trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#csco"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Cisco Systems (DE). It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Cisco_Systems_%28DE%29_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Cisco_Systems_%28DE%29_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "107f4e5cb73f2c5b81c0e6475274751c6af6f14b19736f50dc276b4e51cc7d2e", "tool": "YahooFinance", "notebook": "Chat about CoStar Group trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#csgp"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for CoStar Group. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_CoStar_Group_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_CoStar_Group_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "ee99b1abd31b3fb8645c9dd8c138630b196fe4cd5721e597134a9219b5a05f88", "tool": "YahooFinance", "notebook": "Chat about Cognizant Technology Solutions Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ctsh"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Cognizant Technology Solutions Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Cognizant_Technology_Solutions_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Cognizant_Technology_Solutions_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "4a8a978bd1b54f6657ba1cd830060cd2b64787da8bc33617ade439ec0ff50112", "tool": "YahooFinance", "notebook": "Chat about Constellation Energy Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ceg"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Constellation Energy Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Constellation_Energy_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Constellation_Energy_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "447347f9c3f121c37c46d4eee677c043e5b682e3212f4dd4c0abc6a464110bf1", "tool": "YahooFinance", "notebook": "Chat about Copart (DE) trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#cprt"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Copart (DE). It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Copart_%28DE%29_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Copart_%28DE%29_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "fc8ebcb14dd4ef18e5225f97ae2a1fa5b6021c64df8c2e450f487db862366257", "tool": "YahooFinance", "notebook": "Chat about CrowdStrike Holdings trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#crwd"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for CrowdStrike Holdings. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_CrowdStrike_Holdings_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_CrowdStrike_Holdings_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "537b6a1495f7e34472a43bf762c6bae8b2784bcb86fc40238dd3da25c59f964c", "tool": "YahooFinance", "notebook": "Chat about Datadog trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ddog"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Datadog. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Datadog_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Datadog_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b6da0211691a90b7e285172167a44ede266655142d0efa21ee9c9e871684ea93", "tool": "YahooFinance", "notebook": "Chat about DexCom trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#dxcm"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for DexCom. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_DexCom_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_DexCom_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "e3b5fa5803456f044eac92f1f1eed584af84ec4ce15355711d6d9c32f175fc35", "tool": "YahooFinance", "notebook": "Chat about Diamondback Energy trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#fang"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Diamondback Energy. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Diamondback_Energy_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Diamondback_Energy_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "5513bf7405619286d7dd94cccd73c8e6f44fdf574e91647762f69f8d736b6103", "tool": "YahooFinance", "notebook": "Chat about Dollar Tree trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#dltr"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Dollar Tree. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Dollar_Tree_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Dollar_Tree_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "6f7f4725c55c953578a694de1fc755a069d8478bef875a0dc856a22934822b86", "tool": "YahooFinance", "notebook": "Chat about Electronic Arts trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ea"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Electronic Arts. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Electronic_Arts_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Electronic_Arts_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "c2ae19b4da5e590936adac028d3258d60b0a56eb878ca1d2fab0e09e54b5e3fd", "tool": "YahooFinance", "notebook": "Chat about Enphase Energy trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#enph"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Enphase Energy. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Enphase_Energy_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Enphase_Energy_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "240e62189bbb4510c941cfdcb981c9366c325b1beba64baaedfbb33df2969973", "tool": "YahooFinance", "notebook": "Chat about Exelon Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#exc"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Exelon Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Exelon_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Exelon_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "617b1c431c962cac8e3fff2f258b5469b3f4b6df9bb62899184a2c03c24cf214", "tool": "YahooFinance", "notebook": "Chat about Fastenal Company trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#fast"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Fastenal Company. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Fastenal_Company_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Fastenal_Company_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "4a6593ba0b7f8eeb0f0a018c55312c84a89be3285e76943fba8045f0b5200570", "tool": "YahooFinance", "notebook": "Chat about Fortinet trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ftnt"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Fortinet. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Fortinet_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Fortinet_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "46292fcce418d5dd9164b2fa10154c0e2f365ff0b50c8af907004542c80aedae", "tool": "YahooFinance", "notebook": "Chat about GE HealthCare Technologies trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#gehc"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for GE HealthCare Technologies. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_GE_HealthCare_Technologies_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_GE_HealthCare_Technologies_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "91c0ff92b60058940c7d6c509c1d9b0a08a1245bedf1018c5549ac86928d3392", "tool": "YahooFinance", "notebook": "Chat about Gilead Sciences trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#gild"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Gilead Sciences. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Gilead_Sciences_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Gilead_Sciences_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "0ab6db5174984a9d7d455d4709cc22cf491ec3ac8ad201bad080c5a0c190437e", "tool": "YahooFinance", "notebook": "Chat about GlobalFoundries Ordinary Shares trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#gfs"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for GlobalFoundries Ordinary Shares. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_GlobalFoundries_Ordinary_Shares_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_GlobalFoundries_Ordinary_Shares_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "4e2a2a01fabebad50d09483245e48b74977a610c36bd1737c8ebf0cfe3016f10", "tool": "YahooFinance", "notebook": "Chat about Honeywell International trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#hon"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Honeywell International. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Honeywell_International_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Honeywell_International_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "3d986c84f0125077ef63562648c5f4b83a93aa424559e05883d371f5582d5767", "tool": "YahooFinance", "notebook": "Chat about IDEXX Laboratories trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#idxx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for IDEXX Laboratories. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_IDEXX_Laboratories_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_IDEXX_Laboratories_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "3c17e25d613ad4c36f8ae297180d6857ad6601312c2941b4a8b74b06a3d70631", "tool": "YahooFinance", "notebook": "Chat about Illumina trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ilmn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Illumina. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Illumina_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Illumina_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b7a075b26170dba007791236caf121e8c4e70c660084d1852578db48498fba7b", "tool": "YahooFinance", "notebook": "Chat about Intel Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#intc"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Intel Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Intel_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Intel_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "8b67945087a2b87f28842129eb46b8819fc9949e69e758d96bd547a0712451bc", "tool": "YahooFinance", "notebook": "Chat about Intuit trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#intu"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Intuit. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Intuit_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Intuit_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "78063fe941e4aea1611b8edd59b8a5ef255534393fe50db58cba98b41ffe1799", "tool": "YahooFinance", "notebook": "Chat about JD.com American Depositary Shares trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#jd"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for JD.com American Depositary Shares. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_JD.com_American_Depositary_Shares_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_JD.com_American_Depositary_Shares_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "427bf682c422773d5ddd3918b64407ffd63f01c7ba288f70c1ac2963fa1f6e3c", "tool": "YahooFinance", "notebook": "Chat about KLA Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#klac"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for KLA Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_KLA_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_KLA_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a6bb9402e581a9b68a9590912e9233e8617d5e2b606e5c54857913b05f18934f", "tool": "YahooFinance", "notebook": "Chat about Keurig Dr Pepper trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#kdp"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Keurig Dr Pepper. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Keurig_Dr_Pepper_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Keurig_Dr_Pepper_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "7bdec616e0ad2a31ebffe3c74ea0278440d1bf2523a386b70e3e514b92e3793f", "tool": "YahooFinance", "notebook": "Chat about Lam Research Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#lrcx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Lam Research Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Lam_Research_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Lam_Research_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "c6ac96f819ac4f14ca7f93b40dfbb45dad2d0614ded16c12308de632edcfbfcf", "tool": "YahooFinance", "notebook": "Chat about Lucid Group trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#lcid"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Lucid Group. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Lucid_Group_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Lucid_Group_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "fcf41f4a1b7ae82f6e54a212027dd016471068a77094ce6ef1de9f9d82d45aca", "tool": "YahooFinance", "notebook": "Chat about Marriott International trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#mar"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Marriott International. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Marriott_International_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Marriott_International_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "263aba353d8f9357f95f43cdd0621cbb0cf45065685f52c79a679752a802a9ed", "tool": "YahooFinance", "notebook": "Chat about Marvell Technology trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#mrvl"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Marvell Technology. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Marvell_Technology_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Marvell_Technology_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "d8aeecd630bf684bfcd05bd4d00f20681cc70d3917f8532a2a1ec77161e5ba36", "tool": "YahooFinance", "notebook": "Chat about MercadoLibre trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#meli"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for MercadoLibre. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_MercadoLibre_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_MercadoLibre_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "1e3a1cef24e84c08dc8c83d087ba42e49610950d64e03788f5e52fcf00b9d750", "tool": "YahooFinance", "notebook": "Chat about Meta Platforms trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#meta"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Meta Platforms. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Meta_Platforms_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Meta_Platforms_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "cd5d64bded282ffa3d3842046291d82484ba8abf4f1faa1e9fd267d03e575053", "tool": "YahooFinance", "notebook": "Chat about Micron Technology trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#mu"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Micron Technology. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Micron_Technology_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Micron_Technology_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "74eab3bae5e86278e3ca13ca4f33990898eba59ce3f3d1c6d85f4190d2cf3aa1", "tool": "YahooFinance", "notebook": "Chat about Mondelez International trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#mdlz"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Mondelez International. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Mondelez_International_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Mondelez_International_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "6ba5fa95466a49f883d852b9ece1ab347a700093238041fedb9eba78acc74aaa", "tool": "YahooFinance", "notebook": "Chat about NVIDIA Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#nvda"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for NVIDIA Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_NVIDIA_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_NVIDIA_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "9bba3c154699bf08e2e262522536f7297e6312f8773fae23415f3ca24e258cdc", "tool": "YahooFinance", "notebook": "Chat about NXP Semiconductors N.V. trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#nxpi"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for NXP Semiconductors N.V.. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_NXP_Semiconductors_N.V._trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_NXP_Semiconductors_N.V._trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "960f588a34b9a35496a661f75eba990bf1a9552dba7741b7605728e7e02907f1", "tool": "YahooFinance", "notebook": "Chat about Netflix trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#nflx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Netflix. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Netflix_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Netflix_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "7a4daaf71c3c1e492adf8f18b2c4e9c72975bf50ba2f395e397ef8365b15ce8a", "tool": "YahooFinance", "notebook": "Chat about O'Reilly Automotive trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#orly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for O'Reilly Automotive. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_O%27Reilly_Automotive_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_O%27Reilly_Automotive_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "aaf6ff6f640bc6b47ebf6e7d6c9b499df33dd54e2bc50bd891f3ea11dc8542a8", "tool": "YahooFinance", "notebook": "Chat about ON Semiconductor Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#on"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for ON Semiconductor Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_ON_Semiconductor_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_ON_Semiconductor_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "4eaaea6f5d3f24a61f54aa9d899bb3c61f73dea314a0bf2512f17fabbdaf3b3b", "tool": "YahooFinance", "notebook": "Chat about Old Dominion Freight Line trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#odfl"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Old Dominion Freight Line. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Old_Dominion_Freight_Line_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Old_Dominion_Freight_Line_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b529dfa0c4badc909054307b3bc1f408eb06e6a04938f3d5498c5a8927e625d7", "tool": "YahooFinance", "notebook": "Chat about PDD Holdings American Depositary Shares trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#pdd"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for PDD Holdings American Depositary Shares. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_PDD_Holdings_American_Depositary_Shares_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_PDD_Holdings_American_Depositary_Shares_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "d2c9c91e8a399468f54f50783010ca1185cd87f31e353e7db89193a18702d20a", "tool": "YahooFinance", "notebook": "Chat about PayPal Holdings trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#pypl"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for PayPal Holdings. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_PayPal_Holdings_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_PayPal_Holdings_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "365c9341c4966218f330392186eb8fa0df14620e5e616b5402a626ea3fe8579c", "tool": "YahooFinance", "notebook": "Chat about Paychex trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#payx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Paychex. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Paychex_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Paychex_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "8821c967642c554155c4f8220840fd09a1c4ca43ef383be66a4b570d77b0b124", "tool": "YahooFinance", "notebook": "Chat about PepsiCo trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#pep"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for PepsiCo. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_PepsiCo_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_PepsiCo_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "9b1b3a5e86f9ac6a53af523f9e98dffe43ec646e4ba26fae584537255dd62334", "tool": "YahooFinance", "notebook": "Chat about QUALCOMM Incorporated trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#qcom"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for QUALCOMM Incorporated. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_QUALCOMM_Incorporated_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_QUALCOMM_Incorporated_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "fd1533db5680f347b4787081c34eb457fca5e7ced055c22a3876898eb7019108", "tool": "YahooFinance", "notebook": "Chat about Regeneron Pharmaceuticals trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#regn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Regeneron Pharmaceuticals. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Regeneron_Pharmaceuticals_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Regeneron_Pharmaceuticals_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a6467944df278b9d1b03ebbbe2aa332af03886cc927c4b977beefa807b2aada7", "tool": "YahooFinance", "notebook": "Chat about Ross Stores trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#rost"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Ross Stores. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Ross_Stores_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Ross_Stores_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "cfb36fc2149e1808cea1666e3545d905d39e158e314cf2cf0a6a93d089304130", "tool": "YahooFinance", "notebook": "Chat about Seagen trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#sgen"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Seagen. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Seagen_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Seagen_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "3ace2f2927d6767ded820491c2a354a4364e73a157b133d01171faa9b4bdbbd9", "tool": "YahooFinance", "notebook": "Chat about Sirius XM Holdings trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#siri"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Sirius XM Holdings. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Sirius_XM_Holdings_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Sirius_XM_Holdings_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "dac33469fa100d5f211ec46b0303f509510391b5bc3baebd678f94d5ddb8131e", "tool": "YahooFinance", "notebook": "Chat about Synopsys trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#snps"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Synopsys. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Synopsys_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Synopsys_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "ede9456621f68bbd2bf4205ac34222d0a931b1c0579d8e09565428d7fd51b51a", "tool": "YahooFinance", "notebook": "Chat about T-Mobile US trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#tmus"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for T-Mobile US. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_T-Mobile_US_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_T-Mobile_US_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a59201976348cd448a95b933eb1985c9141876cb20a1782ed0481a7acd9b9564", "tool": "YahooFinance", "notebook": "Chat about Tesla trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#tsla"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Tesla. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Tesla_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Tesla_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "436b31f6e6c4f53bfc314880c479f177cf4ca0f705f1dd7ea930400c45ab3f12", "tool": "YahooFinance", "notebook": "Chat about Texas Instruments Incorporated trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#txn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Texas Instruments Incorporated. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Texas_Instruments_Incorporated_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Texas_Instruments_Incorporated_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "52e5316fa76780f3764a5c6393c5ff4ac14224c0d465c9e75f51cc259c08c48d", "tool": "YahooFinance", "notebook": "Chat about The Trade Desk trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ttd"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for The Trade Desk. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_The_Trade_Desk_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_The_Trade_Desk_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "0d71238f0ddbffa48c968731586e26ef61c2f9a49832fd5b3a5f930a1185c3b4", "tool": "YahooFinance", "notebook": "Chat about Verisk Analytics trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#vrsk"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Verisk Analytics. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Verisk_Analytics_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Verisk_Analytics_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a3437a7718690ff3e7fd995e8e5a1d451ecbd6f16dcfe51a214815c79324ba3b", "tool": "YahooFinance", "notebook": "Chat about Vertex Pharmaceuticals Incorporated trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#vrtx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Vertex Pharmaceuticals Incorporated. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Vertex_Pharmaceuticals_Incorporated_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Vertex_Pharmaceuticals_Incorporated_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "ed1e147cb80c7cd2ad38b3640802addcfc9560be6029ae08188f3ba3b9ad47af", "tool": "YahooFinance", "notebook": "Chat about Walgreens Boots Alliance trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#wba"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Walgreens Boots Alliance. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Walgreens_Boots_Alliance_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Walgreens_Boots_Alliance_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "aacd9e914528ab2164bee48b3414c8549fb3898dd43b7bd485f086e284d4699e", "tool": "YahooFinance", "notebook": "Chat about Workday trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#wday"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Workday. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Workday_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Workday_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "dc78883dcf77261a79ea66d921472333e6d319110f1582e4112a0a853bd46582", "tool": "YahooFinance", "notebook": "Chat about Xcel Energy trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#xel"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Xcel Energy. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Xcel_Energy_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Xcel_Energy_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "9cb8ec1ce5db1edbfb0e638cea3e930afaf3a0051229aa266a444c43744ea32a", "tool": "YahooFinance", "notebook": "Chat about Zoom Video Communications trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#zm"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Zoom Video Communications. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Zoom_Video_Communications_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Zoom_Video_Communications_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "fb5e9cc3776ee111f5437f1bc60512d03ee2a518bf77fae1f52b787b237b416b", "tool": "YahooFinance", "notebook": "Chat about Zscaler trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#zs"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Zscaler. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Zscaler_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Zscaler_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "79ecd741c9e6b35b4dc307ebe6698fe774c8378c7cb4062e93613ec6c021f4d0", "tool": "YahooFinance", "notebook": "Chat about eBay trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ebay"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for eBay. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_eBay_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_eBay_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "dbcda358b6ff27edb6f4b4b3a38e00714efe3a2137bf3e9210e0d24d0b8629d5", "tool": "YahooFinance", "notebook": "Cryptocurrencies heatmap correlation graph", "action": "", "tags": ["#yahoofinance", "#cryptocurrency", "#eth", "#btc", "#heatmap", "#finance", "#trading", "#investors", "#snippet", "#matplotlib"], "author": "Carlo Occhiena", "author_url": "https://www.linkedin.com/in/carloocchiena/", "updated_at": "2023-04-12", "created_at": "2022-02-15", "description": "This notebook provides a graphical representation of the correlation between different cryptocurrencies using a heatmap from YahooFinance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Cryptocurrencies_heatmap_correlation_graph.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Cryptocurrencies_heatmap_correlation_graph.ipynb", "imports": ["datetime", "matplotlib.pyplot", "seaborn", "seaborn", "yfinance", "yfinance"], "image_url": ""}, {"objectID": "7c08faa1a4fa6c75084204d90c6879159bb412b0ce01e9b97d266d2ecacbac6a", "tool": "YahooFinance", "notebook": "Display chart from ticker", "action": "", "tags": ["#yahoofinance", "#trading", "#plotly", "#naas_drivers", "#investors", "#snippet", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-11-22", "description": "This notebook provides a graphical representation of stock market data from a given ticker symbol using the YahooFinance API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Display_chart_from_ticker.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Display_chart_from_ticker.ipynb", "imports": ["naas_drivers.yahoofinance, plotly"], "image_url": ""}, {"objectID": "1f6fb2f8e71d845ac2e577bfd652de2c88017889251c387d91c687840505a839", "tool": "YahooFinance", "notebook": "Find the stock with closest performance using KNN", "action": "", "tags": ["#tool", "#naas_drivers", "#naas", "#scheduler", "#asset", "#snippet", "#automation", "#ai", "#analytics", "#yahoo", "#clustering", "#stocks"], "author": "Abhinav Lakhani", "author_url": "https://www.linkedin.com/in/abhinav-lakhani/", "updated_at": "2023-04-12", "created_at": "2022-06-23", "description": "This notebook uses KNN to find the stock with the most similar performance to a given stock from YahooFinance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Find_the_stock_with_closest_performance_using_KNN.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Find_the_stock_with_closest_performance_using_KNN.ipynb", "imports": ["naas_drivers.yahoofinance", "naas", "pylab.plot, show", "numpy.vstack, array", "numpy.random.rand", "numpy", "scipy.cluster.vq.kmeans, vq", "pandas", "math.sqrt", "sklearn.cluster.KMeans", "matplotlib.pyplot"], "image_url": ""}, {"objectID": "e4faa959f82ec8398c2290f27c0a1297a4d02d32981e982ced4d1aa2fa89efc7", "tool": "YahooFinance", "notebook": "Get Brent Crude Oil trend and predictions", "action": "", "tags": ["#commodities", "#energy", "#petrol", "#oil", "#yahoofinance", "#trading", "#markdown", "#prediction", "#plotly", "#naas_drivers", "#notification", "#naas", "#investors", "#automation", "#analytics", "#ai", "#html", "#image"], "author": "Ayoub Berdeddouch", "author_url": "https://www.linkedin.com/in/ayoub-berdeddouch/", "updated_at": "2023-04-12", "created_at": "2022-11-03", "description": "This notebook provides an analysis of the current trend and predictions for Brent Crude Oil prices using data from YahooFinance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Get_Brent_Crude_Oil_trend_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Get_Brent_Crude_Oil_trend_and_predictions.ipynb", "imports": ["naas", "naas_drivers.prediction, yahoofinance, plotly", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML"], "image_url": ""}, {"objectID": "9452ee3b76b3da57b58787412419b2f1bb939f7830d1114e8e84a9ea739da137", "tool": "YahooFinance", "notebook": "Get Stock Update", "action": "", "tags": ["#yahoofinance", "#usdinr", "#plotly", "#investors", "#analytics", "#automation"], "author": "Megha Gupta", "author_url": "https://github.com/megha2907", "updated_at": "2023-04-12", "created_at": "2022-01-27", "description": "This notebook provides a convenient way to access up-to-date stock information from Yahoo Finance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Get_Stock_Update.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Get_Stock_Update.ipynb", "imports": ["naas", "naas_drivers.yahoofinance, plotly", "markdown2", "IPython.display.Markdown", "naas"], "image_url": ""}, {"objectID": "5296f754c8c0b510e03f2bff45b3f988f676c51e6e82fe4b042cb712b99ae73c", "tool": "YahooFinance", "notebook": "Get USDEUR data and chart", "action": "", "tags": ["#yahoofinance", "#trading", "#plotly", "#naas_drivers", "#investors", "#analytics"], "author": "Carlo Occhiena", "author_url": "https://www.linkedin.com/in/carloocchiena/", "updated_at": "2023-04-12", "created_at": "2022-02-08", "description": "This notebook provides a way to access and visualize the current exchange rate between the US Dollar and the Euro.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Get_USDEUR_data_and_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Get_USDEUR_data_and_chart.ipynb", "imports": ["naas_drivers.yahoofinance, plotly"], "image_url": ""}, {"objectID": "c56ffadc687c98b7845b537fb4fffb768d7e122a3fee299688159595acda7bf3", "tool": "YahooFinance", "notebook": "Get data from ticker", "action": "", "tags": ["#yahoofinance", "#trading", "#naas_drivers", "#investors", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-14", "created_at": "2021-11-22", "description": "This notebook provides a way to access financial data from a given ticker symbol using the YahooFinance API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Get_data_from_ticker.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Get_data_from_ticker.ipynb", "imports": ["naas_drivers.yahoofinance"], "image_url": ""}, {"objectID": "705946d5a30b03afbb6b0aa8cafddce513528727663b25c55d30c2870407c02c", "tool": "YahooFinance", "notebook": "Send daily prediction to Email", "action": "", "tags": ["#yahoofinance", "#trading", "#markdown", "#prediction", "#plotly", "#slack", "#naas_drivers", "#notification", "#naas", "#investors", "#automation", "#analytics", "#email", "#html", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-12-02", "description": "This notebook sends daily predictions from YahooFinance to an email address.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Email.ipynb", "imports": ["naas", "naas_drivers.prediction, yahoofinance, plotly", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML"], "image_url": ""}, {"objectID": "ec092922ecd04f252b65058b599ac56f50a0cc7abccc6cb2b8942b9a3fba465b", "tool": "YahooFinance", "notebook": "Send daily prediction to Notion", "action": "", "tags": ["#yahoofinance", "#trading", "#markdown", "#prediction", "#plotly", "#slack", "#naas_drivers", "#scheduler", "#notification", "#asset", "#webhook", "#dependency", "#naas", "#investors", "#automation", "#analytics", "#html", "#image", "#notion"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-05-06", "description": "This notebook sends daily stock market predictions from YahooFinance to Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Notion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Notion.ipynb", "imports": ["naas", "naas_drivers.prediction, yahoofinance, plotly, notion", "datetime.datetime", "naas_drivers.tools.notion.Link, BlockEmbed", "pytz"], "image_url": ""}, {"objectID": "e56f3194ca88ec903b95cb38754d2c16cce3da81e9a7583bd206ff177083020c", "tool": "YahooFinance", "notebook": "Send daily prediction to Slack", "action": "", "tags": ["#yahoofinance", "#trading", "#markdown", "#prediction", "#plotly", "#slack", "#naas_drivers", "#scheduler", "#naas", "#investors", "#automation", "#analytics"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-09-16", "description": "This notebook sends daily stock market predictions from YahooFinance to Slack.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Slack.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Slack.ipynb", "imports": ["naas", "naas_drivers.prediction, yahoofinance, plotly, slack", "markdown2", "datetime.datetime", "naas"], "image_url": ""}, {"objectID": "2ded78b09046383b0f26f14bae6ea2b48834e06dc5f192d334ad9a604a24ac2f", "tool": "YouTube", "notebook": "Download video", "action": "", "tags": ["#youtube", "#download", "#video", "#content", "#snippet", "#naas"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-06-03", "created_at": "2022-03-18", "description": "This notebook allows users to download videos from YouTube.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Download_video.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Download_video.ipynb", "imports": ["pytube.YouTube", "pytube.YouTube"], "image_url": ""}, {"objectID": "da5c2903e57893dad62f8502805f51e26481cd2488d6c8dbd122e2db4b23f38e", "tool": "YouTube", "notebook": "Extract and summarize transcript", "action": "", "tags": ["#youtube", "#transcript", "#video", "#summarize", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a method to extract and summarize the transcript of a YouTube video.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Extract_and_summarize_transcript.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Extract_and_summarize_transcript.ipynb", "imports": ["youtube_transcript_api.YouTubeTranscriptApi", "naas_drivers.huggingface"], "image_url": ""}, {"objectID": "dee84b001ccaccc3f883887549c5cd1c875c53528fac1004ffc8fbdcf0fb6c03", "tool": "YouTube", "notebook": "Extract transcript from video", "action": "", "tags": ["#youtube", "#transcript", "#video", "#naas_drivers", "#content", "#snippet", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a guide to extracting transcripts from YouTube videos.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Extract_transcript_from_video.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Extract_transcript_from_video.ipynb", "imports": ["pandas", "naas_drivers.youtube"], "image_url": ""}, {"objectID": "429ba3a376300f201bef648d8098ded0e3912f0d2c893732c709dea771746cca", "tool": "YouTube", "notebook": "Get statistics from channel", "action": "", "tags": ["#youtube", "#channel", "#statistics", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a way to access and analyze data from a YouTube channel to gain insights into its performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Get_statistics_from_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Get_statistics_from_channel.ipynb", "imports": ["naas", "naas_drivers.youtube"], "image_url": ""}, {"objectID": "0aa4588cbaaf7815d2de3c8fcec9b1bb0641760a255998dc86a3c5e8e4c9739f", "tool": "YouTube", "notebook": "Get statistics from video", "action": "", "tags": ["#youtube", "#video", "#statistics", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a way to get detailed statistics from YouTube videos.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Get_statistics_from_video.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Get_statistics_from_video.ipynb", "imports": ["naas", "naas_drivers.youtube"], "image_url": ""}, {"objectID": "8776b7a1311600362f191c19e9610009af2567a3a84141c76365b95eadef593d", "tool": "YouTube", "notebook": "Get uploads from channel", "action": "", "tags": ["#youtube", "#channel", "#videos", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows you to retrieve all the videos uploaded to a specific YouTube channel.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Get_uploads_from_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Get_uploads_from_channel.ipynb", "imports": ["naas", "naas_drivers.youtube"], "image_url": ""}, {"objectID": "6d4cc03eb6e8b18900cb63af0ab5a97cd17be85547cff41eb2a6e32d95a78b8f", "tool": "YouTube", "notebook": "Send track to Spotify", "action": "", "tags": ["#youtube", "#spotify", "#snippet"], "author": "Josef", "author_url": "https://www.linkedin.com/in/joseftrchalik/", "updated_at": "2023-04-12", "created_at": "2022-06-03", "description": "This notebook allows users to easily send tracks from YouTube to their Spotify account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Send_track_to_Spotify.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Send_track_to_Spotify.ipynb", "imports": ["spotipy", "spotipy", "spotipy.util", "spotipy.oauth2.SpotifyClientCredentials", "spotipy.SpotifyOAuth", "youtube_dl", "youtube_dl", "google_auth_oauthlib.flow", "google_auth_oauthlib.flow", "googleapiclient.discovery", "googleapiclient.errors", "googleapiclient.discovery", "googleapiclient.errors", "requests, json, os, re, time", "urllib.parse.parse_qs, urlparse", "subprocess.Popen, PIPE", "signal.SIGTERM, SIGKILL", "ant information"], "image_url": ""}, {"objectID": "fd09a21e12b5b8e8d4792169756d6cedf4d8dcc08c7c317062acdadd85f545a8", "tool": "YouTube", "notebook": "Send video stats to Notion", "action": "", "tags": ["#youtube", "#video", "#statistics", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-06-07", "description": "This notebook allows you to easily track and analyze your YouTube video performance by automatically sending video stats to Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Send_video_stats_to_Notion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Send_video_stats_to_Notion.ipynb", "imports": ["naas", "naas_drivers.youtube, notion", "pandas", "pydash", "re", "regex", "emoji", "emoji"], "image_url": ""}, {"objectID": "b451c356f8536123376b8e3ed3e9841ff3ad49a0ad1eb9577952270b63e6e15b", "tool": "YouTube", "notebook": "Summarize video", "action": "", "tags": ["#youtube", "#transcript", "#video", "#npl", "#naas_drivers", "#content", "#snippet", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a summary of a YouTube video, allowing users to quickly understand the content of the video.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Summarize_video.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Summarize_video.ipynb", "imports": ["naas_drivers.youtube"], "image_url": ""}, {"objectID": "e62887290cc7a4c0b82ec67c82df44f9f6236be9992da26426b64649630170c0", "tool": "ZIP", "notebook": "Extract files", "action": "", "tags": ["#zip", "#extract", "#file", "#operations", "#snippet", "#naas"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook allows users to extract files from a ZIP archive.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/ZIP/ZIP_Extract_files.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/ZIP/ZIP_Extract_files.ipynb", "imports": ["zipfile", "os", "pprint.pprint"], "image_url": ""}, {"objectID": "86607d1e05a7be9ceac61f0f3b044a650e57614b93b448afc38002e40ae92ade", "tool": "Zapier", "notebook": "Trigger workflow", "action": "", "tags": ["#zapier", "#nocode", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook allows you to create automated workflows that are triggered by specific events.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Zapier/Zapier_Trigger_workflow.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Zapier/Zapier_Trigger_workflow.ipynb", "imports": ["naas_drivers"], "image_url": ""}, {"objectID": "1a4862f36ffb7a7c2766294894d690900fe245a354ba9b805fde9d40460f92c9", "tool": "ZeroBounce", "notebook": "Validate Single Email", "action": "", "tags": ["#zerobounce", "#email", "#validation", "#java", "#sdk", "#setup"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-27", "description": "This notebook will demonstrate how to validate a single email address using ZeroBounce API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/ZeroBounce/ZeroBounce_Validate_Single_Email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/ZeroBounce/ZeroBounce_Validate_Single_Email.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "9393d951ab135f69cd1aadae8c73b1974891c6586136f3e62aa631501ed53fab", "tool": "gTTS", "notebook": "Save Text to Speech to MP3", "action": "", "tags": ["#gTTS", "#texttospeech", "#mp3", "#python", "#library", "#audio"], "author": "Sriniketh Jayasendil", "author_url": "http://linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-03-02", "description": "This notebook will demonstrate how to use the gTTS library to save text to speech as an MP3 file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/gTTS/gTTS_Save_Text_to_Speech_to_MP3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/gTTS/gTTS_Save_Text_to_Speech_to_MP3.ipynb", "imports": ["gtts.gTTS", "gtts.gTTS"], "image_url": ""}, {"objectID": "b296fdda5aa3884bc9a78e50364dd2532992013a7fb54012c2d9751aa4a5b15f", "tool": "spaCy", "notebook": "SpaCy Build a sentiment analysis model using Twitter", "action": "", "tags": ["#twitter", "#spaCy", "#data", "#nlp", "#sentiment", "#classification"], "author": "Tannia Dubon", "author_url": "https://www.linkedin.com/in/tanniadubon/", "updated_at": "2023-04-12", "created_at": "2022-05-12", "description": "This notebook demonstrates how to use spaCy to build a sentiment analysis model using Twitter data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/spaCy/SpaCy_Build_a_sentiment_analysis_model_using_Twitter.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/spaCy/SpaCy_Build_a_sentiment_analysis_model_using_Twitter.ipynb", "imports": ["os", "requests", "pandas", "json", "ast", "yaml", "numpy", "datetime.datetime, date", "matplotlib.pyplot", "matplotlib", "wordcloud.WordCloud, STOPWORDS, ImageColorGenerator", "re", "seaborn", "string", "warnings", "random", "spacy", "spacy.training.Example", "spacy.pipeline.textcat.DEFAULT_SINGLE_TEXTCAT_MODEL", "spacy.matcher.PhraseMatcher", "pathlib.Path"], "image_url": ""}] \ No newline at end of file +[{"objectID": "3e342697d70a5fc4884c84d82b7b2d1efc9f8dde26b142ec2e63c2246dbfd05b", "tool": "AWS", "notebook": "Daily biling notification to slack", "action": "", "tags": ["#aws", "#cloud", "#storage", "#S3bucket", "#slack", "#operations", "#automation"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2021-09-14", "description": "This notebook sends a daily notification to a Slack channel with the billing information from an AWS account. It allows users to easily keep track of their AWS spending.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AWS/AWS_Daily_biling_notification_to_slack.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AWS/AWS_Daily_biling_notification_to_slack.ipynb", "imports": ["datetime", "boto3", "naas", "dateutil.relativedelta", "pandas", "naas_drivers"], "image_url": ""}, {"objectID": "e5cc5c59cca0de48fbaf2a7d65708d416a50968635cadc60e18a669fd52c075a", "tool": "AWS", "notebook": "Get files from S3 bucket", "action": "", "tags": ["#aws", "#cloud", "#storage", "#S3bucket", "#operations", "#snippet", "#url"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2021-09-20", "description": "This notebook provides a step-by-step guide to retrieving files from an Amazon Web Services (AWS) S3 bucket, allowing users to easily access their data stored in the cloud.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AWS/AWS_Get_files_from_S3_bucket.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AWS/AWS_Get_files_from_S3_bucket.ipynb", "imports": ["boto3"], "image_url": ""}, {"objectID": "db1e517c78d01b715869cb9f08c6c818cd09715bf0134dd92c4440869d176e77", "tool": "AWS", "notebook": "Read dataframe from S3", "action": "", "tags": ["#aws", "#cloud", "#storage", "#S3bucket", "#operations", "#snippet", "#dataframe"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-04-28", "description": "This notebook demonstrates how to read a dataframe from an Amazon Web Services (AWS) Simple Storage Service (S3) bucket.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AWS/AWS_Read_dataframe_from_S3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AWS/AWS_Read_dataframe_from_S3.ipynb", "imports": ["awswrangler", "awswrangler"], "image_url": ""}, {"objectID": "0d5fe4330975af3c53c528f914bd8d0124c25dea14afe09df1119b430a9bb2b2", "tool": "AWS", "notebook": "Send dataframe to S3", "action": "", "tags": ["#aws", "#cloud", "#storage", "#S3bucket", "#operations", "#snippet", "#dataframe"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-04-28", "description": "This notebook demonstrates how to use AWS to send a dataframe to an S3 bucket.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AWS/AWS_Send_dataframe_to_S3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AWS/AWS_Send_dataframe_to_S3.ipynb", "imports": ["awswrangler", "awswrangler", "pandas", "datetime.date"], "image_url": ""}, {"objectID": "f5955b1a7c1209b77d470bfeb5eb20bcdf6ecf7fcba22a304dd0ea03164a0539", "tool": "AWS", "notebook": "Upload file to S3 bucket", "action": "", "tags": ["#aws", "#cloud", "#storage", "#S3bucket", "#snippet", "#operations", "#AWS - Upload file to S3 bucket"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2021-08-03", "description": "This notebook provides instructions on how to upload a file to an Amazon Web Services (AWS) S3 bucket, allowing for secure storage and easy access to the file. It is a simple and efficient way to store and manage data in the cloud.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AWS/AWS_Upload_file_to_S3_bucket.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AWS/AWS_Upload_file_to_S3_bucket.ipynb", "imports": ["boto3", "boto3"], "image_url": ""}, {"objectID": "5916af637e577797931145d971b180db20f2a1d595fec71b99bc547da2ee8dbd", "tool": "Abstract API", "notebook": "Check Email Validation", "action": "", "tags": ["#abstractapi", "#email", "#validation", "#api", "#check", "#tester"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-23", "description": "This notebook will demonstrate how to use Abstract API to check if an email is valid.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Abstract%20API/Abstract_API_Check_Email_Validation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Abstract%20API/Abstract_API_Check_Email_Validation.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "8d77689e05cc016ea0eed7a995b0ef55adc9998684802cc44b3cccf702baed41", "tool": "Abstract API", "notebook": "Get IP Geolocation", "action": "", "tags": ["#api", "#abstract-api", "#ip", "#geolocation", "#stream", "#multithread", "#queues", "#operations", "#dataprocessing", "#automation"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook provides a way to get the geolocation of an IP address using the AbstractAPI service.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Abstract%20API/Abstract_API_Get_IP_Geolocation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Abstract%20API/Abstract_API_Get_IP_Geolocation.ipynb", "imports": ["threading", "queue", "time", "requests", "pandas", "json", "ratelimiter.RateLimiter", "ratelimiter.RateLimiter"], "image_url": ""}, {"objectID": "1fc79d1caf15ef3a1adf0874fa85f6a8b05e172f5e45f0fc6ce7ee40e5c54cae", "tool": "Advertools", "notebook": "Analyze website content using XML sitemap", "action": "", "tags": ["#advertools", "#xml", "#sitemap", "#website", "#analyze", "#seo"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-05-23", "created_at": "2023-05-09", "description": "This notebook helps you get an overview of a website's content by analyzing and visualizing its XML sitemap. It's also an important SEO audit process that can uncover some potential issues that might affect the website.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Analyze_website_content_using_XML_sitemap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Analyze_website_content_using_XML_sitemap.ipynb", "imports": ["advertools", "adviz", "urllib.parse.urlsplit", "IPython.display.display"], "image_url": ""}, {"objectID": "2733269de8aa4a8a013af03ae7af3ac21d9d860849af4b06adb3b31fbfc13ad2", "tool": "Advertools", "notebook": "Audit robots txt and xml sitemap issues", "action": "", "tags": ["#advertools", "#xml", "#sitemap", "#website", "#audit", "#seo", "#robots.txt", "#google"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-05-30", "created_at": "2023-05-29", "description": "This notebook helps you check if there are any conflicts between robots.txt rules and your XML sitemap.\n\n* Are you disallowing URLs that you shouldn't?\n* Test and make sure you don't publish new pages with such conflicts.\n* Do this in bulk: for all URL/rule/user-agent combinations run all tests with one command.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Audit_robots_txt_and_xml_sitemap_issues.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Audit_robots_txt_and_xml_sitemap_issues.ipynb", "imports": ["advertools"], "image_url": ""}, {"objectID": "65fcbc3f91ea08c6a2feb69f5b9f702c91e1da37e5faa0f20f1b1d19f85ade58", "tool": "Advertools", "notebook": "Check status code and Send report by email", "action": "", "tags": ["#advertools", "#website", "#analyze", "#audit", "#seo", "#status_code", "#response_headers", "#naas", "#notification", "#scheduler"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook runs an automated status code checker with response headers using the HTTP `HEAD` method and send a report by email.\n\nNB:\n* Bulk and concurrent checking of status codes for a known list of URLs\n* Get all available response headers from all URLs\n* Set speed, number of concurent request and various other crawling options\n* Does NOT download the full HTML of a page, saving a lot of time, energy, and resources, and enabling an extreemely fast and light process", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Check_status_code_and_Send_notifications.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Check_status_code_and_Send_notifications.ipynb", "imports": ["advertools", "advertools", "datetime.datetime", "naas", "naas_drivers.emailbuilder", "plotly.express", "pandas"], "image_url": ""}, {"objectID": "3c5612a68165853c27d59d0068f4ee37bc3ca2172bb0a1383abe8544664b9524", "tool": "Advertools", "notebook": "Check status code in bulk", "action": "", "tags": ["#advertools", "#adviz", "#website", "#analyze", "#audit", "#seo", "#status_code", "#response_headers"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook runs an automated status code checker with response headers using the HTTP `HEAD` method.\n\n* Bulk and concurrent checking of status codes for a known list of URLs\n* Get all available response headers from all URLs\n* Set speed, number of concurent request and various other crawling options\n* Does NOT download the full HTML of a page, saving a lot of time, energy, and resources, and enabling an extreemely fast and light process", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Check_status_code_in_bulk.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Check_status_code_in_bulk.ipynb", "imports": ["adviz", "adviz", "advertools", "advertools", "datetime.datetime", "plotly.express", "pandas", "IPython.display.display"], "image_url": ""}, {"objectID": "09c6603c1e23892e966a1e1a19a577d94d56c38695e3e2ca640728e81024f848", "tool": "Advertools", "notebook": "Check website pages status code", "action": "", "tags": ["#advertools", "#website", "#status", "#code", "#check", "#pages"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-04", "created_at": "2023-08-04", "description": "This notebook crawls your website and checks the status code of all pages. It starts from the home page and discovers URLs by following links within the website. It is a useful tool for quickly checking the status of your website and generating a report to take necessary actions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Check_website_pages_status_code.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Check_website_pages_status_code.ipynb", "imports": ["advertools", "advertools", "datetime.datetime", "naas", "naas_drivers.emailbuilder, naasauth", "plotly.express", "pandas", "adviz", "adviz", "os"], "image_url": ""}, {"objectID": "1b68edcb30da94c5c5b1f9eece671a36a1cc832aa557bd6302f2b647aac96ba7", "tool": "Advertools", "notebook": "Crawling a website", "action": "", "tags": ["#advertools", "#adviz", "#crawling", "#website", "#analyze", "#seo", "#URL", "#audit", "#scraping", "#scrapy"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-07-20", "created_at": "2023-07-20", "description": "This notebook demonstrates how to crawl a website, starting with one of its pages, and discover and follow all links as well.\n\n* Convert a website to a CSV file\n* Follow links with certain conditions:\n * Whether or not a link matches a certain regex\n * Whether or not a link contains a certain query parameter(s)\n* Extract special elements from pages using CSS/XPath selectors\n* Manage your crawling process with advanced settings (number of concurrent requests, when to stop crawling, proxies, and much more)", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Crawl_a_website.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Crawl_a_website.ipynb", "imports": ["advertools", "advertools", "pandas"], "image_url": ""}, {"objectID": "5fc4529ca8156fe747658753b23728aa1f18141cf3f39703276b7fa6f028e7a6", "tool": "Advertools", "notebook": "Visualize status codes OK and KO", "action": "", "tags": ["#advertools", "#adviz", "#status_code", "#asset", "#plotly", "#naas"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-07-20", "created_at": "2023-07-20", "description": "This notebook creates a plotly treemap to visualize status code OK and KO from list.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Visualize_status_codes_OK_KO.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Visualize_status_codes_OK_KO.ipynb", "imports": ["adviz", "adviz", "naas"], "image_url": ""}, {"objectID": "b81f17379adfb8f806c07e73b25c89b733a11511e8fbf04be7cd54b6faa5ceac", "tool": "Advertools", "notebook": "Visualize status codes count", "action": "", "tags": ["#advertools", "#adviz", "#status_code", "#asset", "#plotly", "#naas"], "author": "Elias Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-07-20", "created_at": "2023-07-20", "description": "This notebook creates a chat to visualize status code count.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Advertools/Advertools_Visualize_status_codes_count.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Advertools/Advertools_Visualize_status_codes_count.ipynb", "imports": ["adviz", "adviz", "naas"], "image_url": ""}, {"objectID": "3d3224a30d88e19593b49386c00bef0933deb4e3cbc16d8e9da64a102989a235", "tool": "Affinity", "notebook": "Sync with Notion database", "action": "", "tags": ["#automation", "#notification", "#Affinity", "#Notion"], "author": "Maxime Jublou", "author_url": "https://linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-05-18", "description": "This notebook allows users to easily sync their Notion database with their Affinity account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Affinity/Affinity_Sync_with_Notion_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Affinity/Affinity_Sync_with_Notion_database.ipynb", "imports": ["naas", "rich.print", "pandas", "pandas.DataFrame", "naas_drivers.notion", "notion_client.APIResponseError", "requests", "pydash", "requests.auth.HTTPBasicAuth", "string.Template"], "image_url": ""}, {"objectID": "fde19b055488d7f318ec541fd38a5195fe025974bb22c1cb2fbf869fbb2ac7c6", "tool": "Agicap", "notebook": "Export treasury plan", "action": "", "tags": ["#agicap", "#treasury", "#export", "#plan", "#finance", "#data", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-27", "created_at": "2023-04-26", "description": "This notebook will export the Excel treasury plan consolidated by month from Agicap and return a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Export_treasury_plan.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Export_treasury_plan.ipynb", "imports": ["requests", "naas", "pandas", "datetime.datetime", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "6e8192ab022b4bd38167bcad47bf5361f21f97d197b712c9c324fbc22e34c1a3", "tool": "Agicap", "notebook": "Export treasury plan by account", "action": "", "tags": ["#agicap", "#treasury", "#export", "#plan", "#finance", "#data", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-27", "created_at": "2023-04-27", "description": "This notebook will export the Excel treasury plan by account by month from Agicap and return a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Export_treasury_plan_by_account.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Export_treasury_plan_by_account.ipynb", "imports": ["requests", "naas", "pandas", "datetime.datetime", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "60ccdeaf932ef6f8fca9165c7451786434f49f667476e71971ae5eec00a549ea", "tool": "Agicap", "notebook": "Get banks accounts from company", "action": "", "tags": ["#agicap", "#bankaccount", "#company", "#finance", "#data", "#api"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-12", "created_at": "2023-07-12", "description": "This notebook will show how to get bank account from a company using Agicap API. It is usefull for organizations to quickly get the bank account of a company.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Get_banks_accounts_from_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Get_banks_accounts_from_company.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "71d55f60d4a6651a4020659b3bfa10cdbb7140d2eecf5287e21df984c3870670", "tool": "Agicap", "notebook": "Get inflow categories from company", "action": "", "tags": ["#agicap", "#categories", "#company", "#data", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-12", "created_at": "2023-07-12", "description": "This notebook will get inflow categories from a company in Agicap and return a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Get_inflow_categories_from_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Get_inflow_categories_from_company.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "00feab61f04c827086dcafd75d0532814272be3ecbef5608861024364dd1d02a", "tool": "Agicap", "notebook": "Get outflow categories from company", "action": "", "tags": ["#agicap", "#categories", "#company", "#data", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-12", "created_at": "2023-07-12", "description": "This notebook will get outflow categories from a company in Agicap and return a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Get_outflow_categories_from_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Get_outflow_categories_from_company.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "3d1b2dd49f1d4066bac81a72f725227fdfce1e44d69e304ec9dfae39cbfdbe4d", "tool": "Agicap", "notebook": "Get transactions by account", "action": "", "tags": ["#agicap", "#forecast", "#company", "#data", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-18", "created_at": "2023-09-18", "description": "This notebook is designed to retrieve all transactions for a specified company and account from Agicap. It will then organize this data into a structured DataFrame for easy analysis. \nThe DataFrame returned contains the following columns:\n- 'ENTREPRISE_ID': This column represents the unique identifier of the company.\n- 'COMPTE_ID': This column indicates the specific account ID related to the transaction.\n- 'TRANSACTION_ID': This column holds the unique transaction ID.\n- 'TRANSACTION_NAME': This column contains the name or description of the transaction.\n- 'CATEGORY_ID': This column represents the unique identifier of the transaction category.\n- 'CATEGORY_NAME': This column contains the name of the transaction category.\n- 'PROJECTS': This column is intended for any project-related information linked with the transaction.\n- 'CURRENCY': This column indicates the currency in which the transaction was made.\n- 'DATE_ORDER': This column holds the order date of the transaction in Unix timestamp format.\n- 'DATE': This column contains the date of the transaction in 'DD/MM/YYYY' format.\n- 'VALUE': This column represents the monetary value of the transaction.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_Get_transactions_by_account.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_Get_transactions_by_account.ipynb", "imports": ["requests", "naas", "pandas", "json"], "image_url": ""}, {"objectID": "5b0eeb327eb1d95fe850ad247b10ac8fb597a92887acf64a29dc564086e889e4", "tool": "Agicap", "notebook": "List companies", "action": "", "tags": ["#agicap", "#companies", "#accountingsoftware", "#financialmanagement", "#businessmanagement", "#financetracking", "#budgetplanning", "#invoicing", "#expensetracking", "#businessinsights", "#dataanalysis"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-10", "description": "This notebook lists all the companies within Agicap with their IDs. Agicap is a powerful accounting software for managing your company's finances. It offers features such as expense tracking, budget planning, invoicing, and data analysis to help you make informed business decisions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Agicap/Agicap_List_companies.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Agicap/Agicap_List_companies.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "32269a4228bf817ab1b2d51b7a5771d41e0381627b8e07487e9c7afa0ee0bf37", "tool": "Airtable", "notebook": "Delete data", "action": "", "tags": ["#airtable", "#database", "#productivity", "#spreadsheet", "#naas_drivers", "#operations", "#snippet", "#text"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides instructions on how to delete data from an Airtable database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Airtable/Airtable_Delete_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Airtable/Airtable_Delete_data.ipynb", "imports": ["naas_drivers.airtable"], "image_url": ""}, {"objectID": "f93453cccd04f72d5ec42afc790f102a05e6695c5b7d46347e25d1ac9bd3e67c", "tool": "Airtable", "notebook": "Get data", "action": "", "tags": ["#airtable", "#database", "#productivity", "#spreadsheet", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides an introduction to Airtable, a cloud-based database platform that allows users to easily access and manage data. It provides step-by-step instructions on how to get data from Airtable into a notebook for further analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Airtable/Airtable_Get_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Airtable/Airtable_Get_data.ipynb", "imports": ["naas_drivers.airtable"], "image_url": ""}, {"objectID": "718782ca423ea8e69fc7a4d05b5a28ebecc61ce558bff968d6466fe6279c0e3a", "tool": "Airtable", "notebook": "Insert data", "action": "", "tags": ["#airtable", "#database", "#productivity", "#spreadsheet", "#naas_drivers", "#operations", "#snippet", "#text"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides a step-by-step guide on how to insert data into an Airtable database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Airtable/Airtable_Insert_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Airtable/Airtable_Insert_data.ipynb", "imports": ["naas_drivers.airtable"], "image_url": ""}, {"objectID": "8f01544918dbd4ddadf8d4079fc2e2b7eee3af9b45a3baa3af433f2404df5bb2", "tool": "Airtable", "notebook": "Search data", "action": "", "tags": ["#airtable", "#database", "#productivity", "#spreadsheet", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook allows users to search through data stored in Airtable, making it easy to find the information they need quickly and efficiently.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Airtable/Airtable_Search_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Airtable/Airtable_Search_data.ipynb", "imports": ["naas_drivers.airtable"], "image_url": ""}, {"objectID": "f529085c0f2d4f78142501e664c14ab66edf02fb933d2d7c8bd49721d43a90df", "tool": "Algolia", "notebook": "Add or Replace all attributes in existing records", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#object", "#save", "#update", "#add"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-15", "description": "This notebook shows how to add new records (objects) to an index or replace existing records with an updated set of attributes.\nThis method redefines all of a record\u2019s attributes (except its objectID). In other words, it fully replaces an existing record.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_Add_or_Replace_all_attributes_in_existing_records.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_Add_or_Replace_all_attributes_in_existing_records.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "5d2df023819411f69ec17f94b0bfde745eb6a1292e39f5cded170e4c053333f6", "tool": "Algolia", "notebook": "Add or Replace all attributes in a single record", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#object", "#save", "#update", "#add"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-15", "description": "This notebook shows how to add new record (object) to an index or replace existing record with an updated set of attributes.\nThis method redefines all of a record\u2019s attributes (except its objectID). In other words, it fully replaces an existing record.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_Add_or_Replace_all_attributes_in_single_record.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_Add_or_Replace_all_attributes_in_single_record.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "bb72a24111a186d70f016c346ba1f037125524cba143537d2c214a354f1d3308", "tool": "Algolia", "notebook": "Delete multiples objects", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#object", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-15", "description": "This notebook shows how to delete multiples objects from an Algolia index using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_Delete_multiples_objects.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_Delete_multiples_objects.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "8d7294cbf8b3918f28680d17d1a9bb6465e72fb8129f2c7d2ff91b571a2de4d7", "tool": "Algolia", "notebook": "Delete a single object", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#object", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-15", "description": "This notebook shows how to delete a single object from an Algolia index using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_Delete_single_object.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_Delete_single_object.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "815211fb3ee83348a3785424987de3ef51856933b6fddbd4c2beea49609ffbe2", "tool": "Algolia", "notebook": "Get all records from an index", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#records", "#browse"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-14", "description": "This notebook shows how to get all records from an Algolia index using Python. It is usefull for organizations that need to access and manipulate data stored in Algolia.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_Get_all_records_from_an_index.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_Get_all_records_from_an_index.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "f5ee3a4a99ee8df9d2b7751ff23b22e1813c83a7c0eb3aae1d3ea0995563ccf2", "tool": "Algolia", "notebook": "List indices", "action": "", "tags": ["#algolia", "#python", "#api", "#index", "#list"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-15", "description": "This notebook shows how to get a list of indices with their associated metadata from Algolia using Python. This method retrieves a list of all indices associated with a given Application ID.\nThe returned list includes the names of the indices as well as their associated metadata, such as the number of records, size, and last build time.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Algolia/Algolia_List%20indices.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Algolia/Algolia_List%20indices.ipynb", "imports": ["algoliasearch.search_client.SearchClient", "algoliasearch.search_client.SearchClient", "naas"], "image_url": ""}, {"objectID": "d18163bf41ff8dd85cbae1e18aa4d976a3244f48089b3cd6c9058b1fd3523720", "tool": "AlphaVantage", "notebook": "Get balance sheet", "action": "", "tags": ["#alphavantage", "#trading", "#market_data", "#investors", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides a way to access financial data from AlphaVantage, specifically balance sheet information for a given company. It allows users to quickly and easily access up-to-date financial information for their analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AlphaVantage/AlphaVantage_Get_balance_sheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AlphaVantage/AlphaVantage_Get_balance_sheet.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "44205360daf5879c2a0eeecd80a0dfc2f4c502dd671b5247ce5234287cddadff", "tool": "AlphaVantage", "notebook": "Get cashflow statement", "action": "", "tags": ["#alphavantage", "#trading", "#market_data", "#investors", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides a way to access financial data from AlphaVantage, including cashflow statements.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AlphaVantage/AlphaVantage_Get_cashflow_statement.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AlphaVantage/AlphaVantage_Get_cashflow_statement.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "03196420b0ecd1331f5511875ff18643e432128254644221a0b139019b1c42cd", "tool": "AlphaVantage", "notebook": "Get company overview", "action": "", "tags": ["#alphavantage", "#trading", "#market_data", "#investors", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides an overview of the AlphaVantage API, which allows users to access real-time and historical financial data for global equities, commodities, and currencies. It provides a comprehensive set of tools to analyze and visualize financial data for a variety of purposes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AlphaVantage/AlphaVantage_Get_company_overview.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AlphaVantage/AlphaVantage_Get_company_overview.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "759fbfe0ce1a7a0c043f30bf8ba8539d3a446058a8f88dee12063444ac6ba3c4", "tool": "AlphaVantage", "notebook": "Get income statement", "action": "", "tags": ["#alphavantage", "#trading", "#market_data", "#investors", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook provides a way to access income statement data from AlphaVantage, a financial data provider. It allows users to quickly and easily access financial information to make informed decisions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/AlphaVantage/AlphaVantage_Get_income_statement.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/AlphaVantage/AlphaVantage_Get_income_statement.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "e51bed9276f9ce9924e82646245d4ed0e8815cd7992187fdf8715a68a7bb8a46", "tool": "Azure Blob Storage", "notebook": "List blobs", "action": "", "tags": ["#azure", "#blob", "#storage", "#list", "#blobs"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-14", "created_at": "2023-07-14", "description": "This notebook will demonstrate how to use the List Blobs operation to return a list of the blobs under the specified container. This is usefull for organizations that need to store and access large amounts of data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Azure%20Blob%20Storage/Azure_Blob_Storage_List_blobs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Azure%20Blob%20Storage/Azure_Blob_Storage_List_blobs.ipynb", "imports": ["azure.storage.blob.BlobServiceClient", "azure.storage.blob.BlobServiceClient", "naas"], "image_url": ""}, {"objectID": "5211f802b4119d49640d75844e0de08b997cd5ec85ee5d76e9af6fa027925578", "tool": "Azure Blob Storage", "notebook": "Upload files", "action": "", "tags": ["#azure", "#datalake", "#naas", "#snippet"], "author": "Alexandre Stevens", "author_url": "https://www.linkedin.com/in/
", "updated_at": "2023-04-12", "created_at": "2023-02-06", "description": "This notebook explains how to upload files to Azure Blob Storage using the Azure Python SDK.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Azure%20Blob%20Storage/Azure_Blob_Storage_Upload_files.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Azure%20Blob%20Storage/Azure_Blob_Storage_Upload_files.ipynb", "imports": ["azure.storage.blob.BlobServiceClient", "azure.storage.blob.ContentSettings", "azure.storage.blob.BlobServiceClient", "azure.storage.blob.ContentSettings"], "image_url": ""}, {"objectID": "94f5a9a6634caea4d03c1756a001a4f834c1fd06920b6183b034b0b60c449401", "tool": "Azure Machine Learning", "notebook": "Univariate Timeseries Inference", "action": "", "tags": ["#azure", "#machinelearning", "#univariate", "#timeseries", "#inference", "#ml"], "author": "Tobias Zwingmann", "author_url": "https://www.linkedin.com/in/tobias-zwingmann/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook provides an example of how to use Azure Machine Learning to perform univariate timeseries inference. It is useful for organizations that need to analyze and predict future trends in their data. It requires a timeseries forecasting model hosted on Microsoft Azure and deployed as a web service. (See references below).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Azure%20Machine%20Learning/Azure_Machine_Learning_Univariate_Timeseries_Inference.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Azure%20Machine%20Learning/Azure_Machine_Learning_Univariate_Timeseries_Inference.ipynb", "imports": ["pandas", "requests", "json", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "70cdbff79ec94526b10df7cf0dde2e985f5507c53ef94d0f3c7dd5a925a1c454", "tool": "Bazimo", "notebook": "Get export Actifs", "action": "", "tags": ["#bazimo", "#pm", "#naas_drivers", "#asset", "#scheduler", "#naas", "#csv", "#operations", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-02", "description": "This notebook provides an easy way to export active assets from Bazimo, allowing users to quickly and efficiently manage their assets. It is a great tool for keeping track of assets and ensuring that they are up to date.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bazimo/Bazimo_Get_export_Actifs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bazimo/Bazimo_Get_export_Actifs.ipynb", "imports": ["naas_drivers.bazimo", "naas"], "image_url": ""}, {"objectID": "57013d1c1890e25d5d71579c29c5fd1136a0f99afd6c302de27830221b68f816", "tool": "Bazimo", "notebook": "Get export Baux", "action": "", "tags": ["#bazimo", "#pm", "#naas_drivers", "#asset", "#scheduler", "#naas", "#csv", "#operations", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-02", "description": "This notebook provides an easy way to export data from Baux, allowing users to quickly and efficiently access their data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bazimo/Bazimo_Get_export_Baux.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bazimo/Bazimo_Get_export_Baux.ipynb", "imports": ["naas_drivers.bazimo", "naas"], "image_url": ""}, {"objectID": "f427f26405a8fcd2677cd6850508051cbfae87c2590c8d8f6932f742c88c0e73", "tool": "Bazimo", "notebook": "Get export Factures", "action": "", "tags": ["#bazimo", "#pm", "#naas_drivers", "#asset", "#scheduler", "#naas", "#csv", "#operations", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-02", "description": "This notebook allows you to easily export invoices from Bazimo, making it easy to keep track of your finances.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bazimo/Bazimo_Get_export_Factures.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bazimo/Bazimo_Get_export_Factures.ipynb", "imports": ["naas_drivers.bazimo", "naas"], "image_url": ""}, {"objectID": "075f91fbf86042edf26814810f71ebdf1ce1f37dcd9cd8ebf960c548f0d87f64", "tool": "Bazimo", "notebook": "Get export Locataires", "action": "", "tags": ["#bazimo", "#pm", "#naas_drivers", "#asset", "#scheduler", "#naas", "#csv", "#operations", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-02", "description": "This notebook provides an easy way to export tenant information from Bazimo.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bazimo/Bazimo_Get_export_Locataires.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bazimo/Bazimo_Get_export_Locataires.ipynb", "imports": ["naas_drivers.bazimo", "naas"], "image_url": ""}, {"objectID": "fec0b2c09dbb0faa29db645a2802320abbfadc22f77dea4fac1a5c75d7b6cb30", "tool": "Bazimo", "notebook": "Get export Lots", "action": "", "tags": ["#bazimo", "#pm", "#naas_drivers", "#asset", "#scheduler", "#naas", "#csv", "#operations", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-02", "description": "This notebook allows you to quickly and easily export large amounts of data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bazimo/Bazimo_Get_export_Lots.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bazimo/Bazimo_Get_export_Lots.ipynb", "imports": ["naas_drivers.bazimo", "naas"], "image_url": ""}, {"objectID": "200a5dcebfc9ff32f08e84aaba44cb6125fbc8bbde5f686f467b8626c7ef5f78", "tool": "BeautifulSoup", "notebook": "List social network links from website", "action": "", "tags": ["#beautifulsoup", "#webscraping", "#python", "#html", "#css", "#url"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-02", "created_at": "2023-05-02", "description": "This notebook will use BeautifulSoup to list all the social network links from a website. It is usefull for organizations to quickly get a list of all the social networks they are present on.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/BeautifulSoup/BeautifulSoup_List_social_network_links_from_website.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/BeautifulSoup/BeautifulSoup_List_social_network_links_from_website.ipynb", "imports": ["requests", "bs4.BeautifulSoup"], "image_url": ""}, {"objectID": "12ef03c9788da13b430b0d23171c6c0949ff23c86a70281d36e19d8a6237b135", "tool": "BeautifulSoup", "notebook": "Scrape emails from URL", "action": "", "tags": ["#beautifulsoup", "#python", "#scraping", "#emails", "#url", "#webscraping", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-16", "description": "This notebook will show how to scrape emails stored in HTML webpage using BeautifulSoup.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/BeautifulSoup/BeautifulSoup_Scrape_emails_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/BeautifulSoup/BeautifulSoup_Scrape_emails_from_URL.ipynb", "imports": ["re", "requests", "urllib.parse.urlsplit", "collections.deque", "bs4.BeautifulSoup", "pandas"], "image_url": ""}, {"objectID": "b8dae3c0c48ff11cf99e98ae8c12001027c397f0898d06da9154692ec1a16e62", "tool": "BigQuery", "notebook": "Create table from csv", "action": "", "tags": ["#bigquery", "#database", "#snippet", "#operations", "#dataframe"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-08-08", "description": "This notebook demonstrates how to create a BigQuery table from a CSV file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/BigQuery/BigQuery_Create_table_from_csv.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/BigQuery/BigQuery_Create_table_from_csv.ipynb", "imports": ["naas_drivers.bigquery"], "image_url": ""}, {"objectID": "752be3434483e20df49126952868c6537832491976d513a39ebaa74913771f35", "tool": "BigQuery", "notebook": "Read Table", "action": "", "tags": ["#bigquery", "#database", "#snippet", "#operations", "#dataframe"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-08-08", "description": "This notebook provides an example of how to read data from a BigQuery table.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/BigQuery/BigQuery_Read_Table.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/BigQuery/BigQuery_Read_Table.ipynb", "imports": ["naas_drivers.bigquery"], "image_url": ""}, {"objectID": "9f9713992be8f9af16d3e66e5ea4486c72b84576fa7353df24f29f45ca8331aa", "tool": "Bitly", "notebook": "Create Links", "action": "", "tags": ["#bitly", "#link", "#shorten", "#url", "#create", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-16", "description": "This notebook will show how to create short links with Bitly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Create_Links.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Create_Links.ipynb", "imports": ["requests", "json"], "image_url": ""}, {"objectID": "cd555eb47a32680c309420899038ccaaf7d29a82018a807210599465b6a69fdd", "tool": "Bitly", "notebook": "Delete a Bitlink", "action": "", "tags": ["#bitly", "#api", "#delete", "#bitlink", "#hash", "#unedited"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will show how to delete an unedited hash Bitlink.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Delete_a_Bitlink.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Delete_a_Bitlink.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "3eabe9ed9dcfdcd75e1a510995d981dfc8bd4c2b98f24591b46f59ef5b7a9e18", "tool": "Bitly", "notebook": "Get Clicks for a Bitlink", "action": "", "tags": ["#bitly", "#api", "#getclicks", "#bitlink", "#python", "#dev"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will show how to use the Bitly API to get the click counts for a specified link in an array based on a date.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_Clicks_for_a_Bitlink.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_Clicks_for_a_Bitlink.ipynb", "imports": ["requests", "naas", "json"], "image_url": ""}, {"objectID": "d4eda72f6942beabed764b0411c2d70a3d2841d82e9d26386ee0e3b185c99186", "tool": "Bitly", "notebook": "Get Metrics for a Bitlink by City", "action": "", "tags": ["#bitly", "#api", "#metrics", "#city", "#bitlink", "#dev"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will return the city origins of click traffic for the specified link. This feature is only available for paid account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_City.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_City.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "59334b21ea4228991b77a580a1aaae1c1630d7f1386a8c933d06ca7ac3c459d9", "tool": "Bitly", "notebook": "Get Metrics for a Bitlink by Country", "action": "", "tags": ["#bitly", "#api", "#metrics", "#bitlink", "#country", "#reference"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-23", "description": "This notebook will demonstrate how to use the Bitly API to get metrics for a Bitlink by Country.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Country.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Country.ipynb", "imports": ["requests", "naas", "pandas", "plotly.graph_objects", "dataprep.clean.clean_country", "dataprep.clean.clean_country", "json", "warnings"], "image_url": ""}, {"objectID": "495e8ac289e12e30a84012c1ce626f510ef6a88551618416ab311a12ddd18040", "tool": "Bitly", "notebook": "Get Metrics for a Bitlink by Devices", "action": "", "tags": ["#bitly", "#api", "#metrics", "#devices"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-28", "description": "This notebook will show how to use the Bitly API to get metrics for a Bitlink by devices. This endpoint is only available for paid account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Devices.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Devices.ipynb", "imports": ["requests", "pprint.pprint", "naas"], "image_url": ""}, {"objectID": "27fe513fb49fdd22a120381d7c1a4f927b39395cf488ecce01bedb545a23f099", "tool": "Bitly", "notebook": "Get Metrics for a Bitlink by Referrers", "action": "", "tags": ["#bitly", "#api", "#metrics", "#bitlink", "#referrers", "#dev"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will show how to use the Bitly API to get metrics for a Bitlink by Referrers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Referrers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_Metrics_for_a_Bitlink_by_Referrers.ipynb", "imports": ["requests", "pprint.pprint", "naas"], "image_url": ""}, {"objectID": "b3fa30866ed0675034945aa524ab4cf0cdd9935b491ef7df58d789a7aa1717c4", "tool": "Bitly", "notebook": "Get a Clicks Summary for a Bitlink", "action": "", "tags": ["#bitly", "#api", "#clicks", "#summary", "#bitlink", "#reference"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-23", "description": "This notebook will show how to get a Clicks Summary for a Bitlink using the Bitly API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Get_a_Clicks_Summary_for_a_Bitlink.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Get_a_Clicks_Summary_for_a_Bitlink.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "40ce36dc1641790e5117bdab22021f520604f1c26bee66d5fe6d6fd685ed8ee3", "tool": "Bitly", "notebook": "Retrieve Bitlink", "action": "", "tags": ["#bitly", "#api", "#list", "#active", "#links", "#python", "#bitlink"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-23", "description": "This notebook will return information for a specified bitlink using the Bitly API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Retrieve_Bitlink.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Retrieve_Bitlink.ipynb", "imports": ["requests", "json", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "aa9e096cfaf039d08eaa4194d361639e661083ff97b300d6fd2d9d4749c60eef", "tool": "Bitly", "notebook": "Update a Bitlink", "action": "", "tags": ["#bitly", "#api", "#update", "#bitlink", "#reference", "#dev"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will show how to update fields in the specified link using Bitly API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bitly/Bitly_Update_a_Bitlink.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bitly/Bitly_Update_a_Bitlink.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "bfc8dd18a5cb62ba07ffe255ff507cbb6e7d09de0f14feab596ad7718e28b7f1", "tool": "Boursorama", "notebook": "Get CDS", "action": "", "tags": ["#boursorama", "#finance", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-09", "description": "This notebook provides a way to access and analyze CDS data from Boursorama.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Boursorama/Boursorama_Get_CDS.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Boursorama/Boursorama_Get_CDS.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "916217867d00e933791e4bd89337ec26ce052f7e856663b80b8707fb16257d4e", "tool": "Boursorama", "notebook": "Get EURIBOR 3 MOIS", "action": "", "tags": ["#boursorama", "#euribor", "#pandas", "#read_html", "#finance", "#data"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will show how to get EURIBOR 3 MOIS using pandas.read_html().", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Boursorama/Boursorama_Get_EURIBOR_3_MOIS.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Boursorama/Boursorama_Get_EURIBOR_3_MOIS.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "f969028b22c1a3a446445dd979298e843d9b00e67cfcdc6d9f0e0ca94ed9e8fa", "tool": "Bubble", "notebook": "Send data", "action": "", "tags": ["#bubble", "#naas_drivers", "#operations", "#snippet"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "This notebook allows users to easily send data through a secure, cloud-based platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Bubble/Bubble_Send_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Bubble/Bubble_Send_data.ipynb", "imports": ["naas_drivers.bubble"], "image_url": ""}, {"objectID": "d32e84a4975bcf6f6343720e6e7ab190036193ef0512dd09ce63387dcee3bfce", "tool": "CCXT", "notebook": "Calculate Support and Resistance", "action": "", "tags": ["#ccxt", "#bitcoin", "#trading", "#investors", "#analytics", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a guide to using the CCXT library to calculate support and resistance levels for cryptocurrency trading.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/CCXT/CCXT_Calculate_Support_and_Resistance.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/CCXT/CCXT_Calculate_Support_and_Resistance.ipynb", "imports": ["naas", "ccxt", "pandas", "datetime.datetime", "naas_drivers", "trendln", "plotly.tools", "plotly.graph_objects"], "image_url": ""}, {"objectID": "f91ca561288c0eb0c1d84e6a165300ce2af7db52fca7389f551767b209a2de24", "tool": "CCXT", "notebook": "Predict Bitcoin from Binance", "action": "", "tags": ["#ccxt", "#bitcoin", "#trading", "#investors", "#ai", "#analytics", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook uses the CCXT library to predict Bitcoin prices on the Binance exchange.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/CCXT/CCXT_Predict_Bitcoin_from_Binance.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/CCXT/CCXT_Predict_Bitcoin_from_Binance.ipynb", "imports": ["naas", "ccxt", "pandas", "datetime.datetime", "naas_drivers.plotly, prediction"], "image_url": ""}, {"objectID": "2fac04a0e47274af3af50087ce42c66a7c88cdc4d2187f530ae968310c7cefe9", "tool": "Canny", "notebook": "Create", "action": "", "tags": ["#canny", "#product", "#operations", "#snippet"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu", "updated_at": "2023-04-12", "created_at": "2021-01-26", "description": "This notebook provides an easy-to-use interface for creating custom Canny edge detection filters.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Canny/Canny_Create.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Canny/Canny_Create.ipynb", "imports": ["requests", "json", "pandas"], "image_url": ""}, {"objectID": "e99b960cfb98cd5fe1eefc5ab9734d32cd7328846af6b8258321e40463768645", "tool": "Canny", "notebook": "Github issue update", "action": "", "tags": ["#canny", "#product", "#operations", "#snippet", "#github"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu", "updated_at": "2023-04-12", "created_at": "2021-01-26", "description": "This notebook provides an automated way to keep track of Github issues and their updates.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Canny/Canny_Github_issue_update.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Canny/Canny_Github_issue_update.ipynb", "imports": ["requests", "json", "github.Github", "pandas"], "image_url": ""}, {"objectID": "5f7c655a1a23609d607d4d123f44853440b27a11ac985de645279ef85c92db1a", "tool": "Canny", "notebook": "Read", "action": "", "tags": ["#canny", "#product", "#operations", "#snippet"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu", "updated_at": "2023-04-12", "created_at": "2021-01-26", "description": "This notebook is a comprehensive guide to understanding and applying the Canny edge detection algorithm.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Canny/Canny_Read.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Canny/Canny_Read.ipynb", "imports": ["requests", "json", "pandas"], "image_url": ""}, {"objectID": "b5d3fc12c82fbcc5bfc6f310e38b0d4fd5270da588df0c8926fbacb000c99f54", "tool": "Celestrak", "notebook": "Satellites over time", "action": "", "tags": ["#celestrak", "#opendata", "#satellites", "#analytics", "#plotly"], "author": "Dumorya", "author_url": "https://github.com/Dumorya", "updated_at": "2023-04-12", "created_at": "2021-06-11", "description": "This notebook provides a visual representation of the changing number of satellites in Earth's orbit over time.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Celestrak/Celestrak_Satellites_over_time.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Celestrak/Celestrak_Satellites_over_time.ipynb", "imports": ["pandas", "plotly.express", "plotly.graph_objects", "numpy"], "image_url": ""}, {"objectID": "688e1d955c26c14cf79153c9ba1bfaf124451cc614bd2e48229eb64ef5534683", "tool": "Cityfalcon", "notebook": "Get data from API", "action": "", "tags": ["#cityfalcon", "#news", "#opendata", "#snippet", "#investors", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-23", "description": "This notebook provides a guide to using the Cityfalcon API to access data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Cityfalcon/Cityfalcon_Get_data_from_API.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Cityfalcon/Cityfalcon_Get_data_from_API.ipynb", "imports": ["naas_drivers.cityfalcon"], "image_url": ""}, {"objectID": "0aa8bc599e4d5c5ed18242a663e9bddbcb379065d173c33908fa9d29cf0d7085", "tool": "Clockify", "notebook": "Add a new client", "action": "", "tags": ["#clockify", "#client", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to add a new client using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Add_a_new_client.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Add_a_new_client.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "e1eded982d49f9a550f7db5cfbf935d98e51bfed0d93c90121ddc84e4dac2b03", "tool": "Clockify", "notebook": "Add a new project", "action": "", "tags": ["#clockify", "#project", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-17", "created_at": "2023-05-17", "description": "This notebook will show how to add a new project using Clockify API to a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Add_a_new_project.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Add_a_new_project.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "77854836bd7b25aefc0458b51b50db3432c4fffbeb389be924bb4df7ef2ecd0f", "tool": "Clockify", "notebook": "Create time entries database on a workspace", "action": "", "tags": ["#clockify", "#timeentry", "#database", "#workspace", "#user", "#create"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-26", "created_at": "2023-07-26", "description": "This notebook creates a time entries database on a specific timeframe, adding client, project and task name. It is usefull for organizations to track time entries and optimize their workflow.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Create_time_entries_database_on_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Create_time_entries_database_on_workspace.ipynb", "imports": ["requests", "naas", "pandas", "datetime.datetime"], "image_url": ""}, {"objectID": "fb1e32f0bf0dae62327dfc4282ebd8b8b3102727e3484a5ac9ec5c47cb78e959", "tool": "Clockify", "notebook": "Delete client", "action": "", "tags": ["#clockify", "#client", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to delete an existing client using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Delete_client.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Delete_client.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "d57352246f90d2636fbe59bbd56770cd15f64252f8f7f9d0495f907809369af8", "tool": "Clockify", "notebook": "Delete project", "action": "", "tags": ["#clockify", "#project", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-17", "created_at": "2023-05-17", "description": "This notebook will show how to delete an existing project using Clockify API from a specific workspace. You can only delete archived project. Active project can not be deleted.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Delete_project.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Delete_project.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "889fc1d9060a7d6797b56f68349eabd2bedb1e4e9627fcb1ebac0236ceca3330", "tool": "Clockify", "notebook": "Find all users on workspace", "action": "", "tags": ["#clockify", "#workspace", "#users", "#find", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to find all users on a workspace using Clockify API.\nIt will return a dataframe with columns as follow:\n- id: This column stores an identifier or unique identifier associated with a user. It likely contains alphanumeric values that uniquely identify each user in the DataFrame.\n- email: This column stores the email addresses associated with the users in the DataFrame. It likely contains text values representing the email addresses of the users.\n- name: This column stores the names or titles associated with the users in the DataFrame. It likely contains text values representing the names of the users.\n- memberships: This column represents the memberships or group affiliations of the users. It likely contains a list or nested data structure that indicates the groups or memberships the users belong to.\n- profilePicture: This column stores the URLs or paths to the profile pictures of the users. It likely contains text values representing the image URLs or file paths.\n- activeWorkspace: This column represents the identifier or unique identifier of the active workspace for each user. It likely contains alphanumeric values that uniquely identify the active workspace.\n- defaultWorkspace: This column stores the identifier or unique identifier of the default workspace for each user. It likely contains alphanumeric values that uniquely identify the default workspace.\n- settings: This column stores user-specific settings or configurations. It likely contains nested data structures or dictionaries that hold various settings related to the user, such as the week start day and timezone.\n- status: This column indicates the status of the users, whether they are active or inactive. It likely contains text values such as \"ACTIVE\" or \"INACTIVE\".\n- customFields: This column stores custom fields or additional information specific to each user. It may contain nested data structures or lists that hold user-specific custom field values.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Find_all_users_on_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Find_all_users_on_workspace.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "27f82b7d0a5b14067a0ddf876dab8649394f189567eecf8a87d260783e7b44d8", "tool": "Clockify", "notebook": "Find clients on workspace", "action": "", "tags": ["#clockify", "#workspace", "#client", "#api", "#python", "#find"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to find clients on a workspace using the Clockify API. It will return a dataframe with columns as follow:\n- id: This column represents an identifier or unique identifier associated with a record or entity. It contains alphanumeric values that uniquely identify each row in the DataFrame.\n- name: This column stores the name or title associated with a particular record or entity. It likely contains text values representing the name of a person, object, or entity.\n- email: This column stores email addresses associated with the records in the DataFrame. It likely contains text values representing the email addresses of individuals or entities.\n- workspaceId: This column represents an identifier or unique identifier associated with a workspace. It likely contains alphanumeric values that uniquely identify each workspace.\n- archived: This column indicates whether a record or entity is archived or not. It likely contains boolean values (True or False), with True indicating that the record is archived and False indicating that it is not.\n- address: This column stores addresses associated with the records in the DataFrame. It likely contains text values representing physical or postal addresses.\n- note: This column stores additional notes or comments related to the records in the DataFrame. It may contain text values providing extra information or details about a particular record or entity.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Find_clients_on_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Find_clients_on_workspace.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "78681e3bc7de22fcb89133eb27fcb13afb59ba5dc01a777f4b0fafb2fda819de", "tool": "Clockify", "notebook": "Find tasks on project", "action": "", "tags": ["#clockify", "#task", "#project", "#find", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will help you find tasks on a project using Clockify API. It will return a dataframe with columns as follow:\n- id: This column stores an identifier or unique identifier associated with a task. It likely contains alphanumeric values that uniquely identify each task in the DataFrame.\n- name: This column stores the names or titles associated with the tasks. It likely contains text values representing the names or titles of the tasks.\n- projectId: This column represents the identifier or unique identifier of the project to which each task belongs. It likely contains alphanumeric values that uniquely identify the project.\n- assigneeIds: This column stores the identifiers or unique identifiers of the assignees assigned to the tasks. It likely contains a list or nested data structure that indicates the assignees associated with each task.\n- assigneeId: This column stores the identifier or unique identifier of a single assignee assigned to the task. It likely contains a single value indicating the assignee for the task.\n- userGroupIds: This column stores the identifiers or unique identifiers of the user groups associated with the tasks. It likely contains a list or nested data structure that indicates the user groups associated with each task.\n- estimate: This column stores the estimate or estimated duration for each task. It likely contains a time duration format, such as \"PT0S\" (indicating zero duration).\n- status: This column indicates the status of the tasks, whether they are active or inactive. It likely contains text values such as \"ACTIVE\" or \"INACTIVE\".\n- duration: This column stores the actual duration or time taken for each task. It likely contains a time duration format, such as \"PT2H42M1S\" (indicating a duration of 2 hours, 42 minutes, and 1 second).\n- billable: This column indicates whether the task is billable or not. It likely contains boolean values (True or False), with True indicating that the task is billable and False indicating that it is not.\n- hourlyRate: This column stores the hourly rate associated with the task. It likely contains numerical values representing the rate for the task, such as an hourly billing rate.\n- costRate: This column stores the cost rate associated with the task. It likely contains numerical values representing the cost rate for the task, such as the rate at which the task incurs costs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Find_tasks_on_project.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Find_tasks_on_project.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "a0b6e7901a2279ecf1696d79f06b9f10b174ad1d6e1af1afdf173c4aefe92635", "tool": "Clockify", "notebook": "Get all my workspaces", "action": "", "tags": ["#clockify", "#api", "#workspace", "#get", "#python", "#rest"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-04-05", "description": "This notebook will show how to get all workspaces of a user using the Clockify API and return a dict.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Get_all_my_workspaces.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Get_all_my_workspaces.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "26994336a93d1f5c9ce8b985beda6b15c3739af1bb21802a977f33b5083da2a5", "tool": "Clockify", "notebook": "Get all projects on workspace", "action": "", "tags": ["#clockify", "#api", "#projects", "#workspace", "#get", "#python"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-05-17", "created_at": "2023-04-05", "description": "This notebook will show how to get all projects on a workspace using the Clockify API and return a dict.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Get_all_projects_on_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Get_all_projects_on_workspace.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "dde1e297a4f5047b497f5ff860a3d36770571578f3c400c2528091607ce82058", "tool": "Clockify", "notebook": "Get client by ID", "action": "", "tags": ["#clockify", "#client", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to get a client using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Get_client_by_ID.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Get_client_by_ID.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "e0be8e4e76433300e789b377ab059f135ee55e69afac5dddbe0d479c67696650", "tool": "Clockify", "notebook": "Get project by ID", "action": "", "tags": ["#clockify", "#project", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-17", "created_at": "2023-05-17", "description": "This notebook will show how to get a project using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Get_project_by_ID.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Get_project_by_ID.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "b40e1e0366358c58a01662a2ec775ec47ecfb7a75fb0790826c477378b0e6657", "tool": "Clockify", "notebook": "Get time entries for a user on workspace", "action": "", "tags": ["#clockify", "#timeentry", "#api", "#python", "#workspace", "#user"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to get time entries for a user on a workspace using Clockify API. It will return a dataframe with columns as follow:\n- id: This column stores an identifier or unique identifier associated with a time entry. It likely contains alphanumeric values that uniquely identify each time entry in the DataFrame.\n- description: This column stores the description or details associated with the time entry. It likely contains text values representing a description of the activity or task performed during the time entry.\n- tagIds: This column stores the identifiers or unique identifiers of the tags associated with the time entry. It likely contains a list or nested data structure that indicates the tags associated with the time entry.\n- userId: This column represents the identifier or unique identifier of the user who created the time entry. It likely contains alphanumeric values that uniquely identify the user.\n- billable: This column indicates whether the time entry is billable or not. It likely contains boolean values (True or False), with True indicating that the time entry is billable and False indicating that it is not.\n- taskId: This column stores the identifier or unique identifier of the task associated with the time entry. It likely contains alphanumeric values that uniquely identify the task.\n- projectId: This column represents the identifier or unique identifier of the project associated with the time entry. It likely contains alphanumeric values that uniquely identify the project.\n- timeInterval_start: This column stores the start timestamp of the time interval for the time entry. It likely contains timestamp values indicating when the time entry started.\n- timeInterval_end: This column stores the end timestamp of the time interval for the time entry. It likely contains timestamp values indicating when the time entry ended.\n- timeInterval_duration: This column stores the duration of the time entry. It likely contains a time duration format, such as \"PT37M16S\" (indicating a duration of 37 minutes and 16 seconds).\n- workspaceId: This column represents the identifier or unique identifier of the workspace associated with the time entry. It likely contains alphanumeric values that uniquely identify the workspace.\n- isLocked: This column indicates whether the time entry is locked or not. It likely contains boolean values (True or False), with True indicating that the time entry is locked and False indicating that it is not.\n- customFieldValues: This column stores custom field values associated with the time entry. It likely contains nested data structures or lists that hold custom field values specific to the time entry.\n- type: This column indicates the type or category of the time entry. It likely contains text values representing the type of activity or task associated with the time entry.\n- kioskId: This column stores the identifier or unique identifier of the kiosk associated with the time entry. It likely contains alphanumeric values that uniquely identify the kiosk.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Get_time_entries_for_a_user_on_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Get_time_entries_for_a_user_on_workspace.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "55ff26f7546527d35891d67642ff3558b55cbe046d7c2611c52da19231ce24bd", "tool": "Clockify", "notebook": "Remove user from workspace", "action": "", "tags": ["#clockify", "#workspace", "#remove", "#user", "#api", "#rest"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-05-16", "created_at": "2023-04-05", "description": "This notebook explains how to remove a user from a workspace using the Clockify API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Remove_user_from_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Remove_user_from_workspace.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "e9dd7f3721289c5cacbb673f835f8704f69b9c284464098a10e7a324a52b8a32", "tool": "Clockify", "notebook": "Send time entries database to a Google Sheets spreadsheet", "action": "", "tags": ["#clockify", "#timeentry", "#database", "#workspace", "#user", "#task", "#project", "#gsheet", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will send the time entries database from Clockify to a Google Sheets spreadsheet. This is usefull for organizations to keep track of their time entries and analyze them.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Send_time_entries_database_to_Google_Sheets_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Send_time_entries_database_to_Google_Sheets_spreadsheet.ipynb", "imports": ["requests", "naas", "pandas", "datetime.datetime", "naas_drivers.gsheet"], "image_url": ""}, {"objectID": "40a719b2a9fd405a4bac1dd9864c9832a49dcbab49584008dbede718c03e8ee7", "tool": "Clockify", "notebook": "Update client", "action": "", "tags": ["#clockify", "#client", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-16", "created_at": "2023-05-16", "description": "This notebook will show how to update a client using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Update_client.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Update_client.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "00cfb28fd1d25a93635ff29385838c7c9f14d989cbb35e6a77b60c5d156718ce", "tool": "Clockify", "notebook": "Update project", "action": "", "tags": ["#clockify", "#project", "#create", "#api", "#rest", "#documentation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-17", "created_at": "2023-05-17", "description": "This notebook will show how to update a project using Clockify API from a specific workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Clockify/Clockify_Update_project.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Clockify/Clockify_Update_project.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "c5fcb9a6ae84c92e74a8dd8b916b7741c133dc3e1efc59b1a730f711ae61f834", "tool": "Cloud Mercato", "notebook": "Compare VM pricing", "action": "", "tags": ["#cloud", "#infrastruture", "#pricing", "#vm", "#iaas", "#analytics", "#compute"], "author": "Anthony Monthe", "author_url": "https://www.linkedin.com/in/anthonymonthe/", "updated_at": "2023-04-12", "created_at": "2022-11-01", "description": "Cloud Mercato is an online platform that allows users to compare virtual machine pricing from different cloud providers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Cloud%20Mercato/Cloud_Mercato_Compare_VM_pricing.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Cloud%20Mercato/Cloud_Mercato_Compare_VM_pricing.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "a420b595b58b994e4a8054607be73c2945ba0b41c37a582aac12836ae0fb9cef", "tool": "Creditsafe", "notebook": "Get Company Credit Report", "action": "", "tags": ["#creditsafe", "#api", "#enterprise", "#integrations", "#company", "#creditreport"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-08", "description": "This notebook will demonstrate how to use the Creditsafe API to get a company credit report.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Creditsafe/Creditsafe_Get_Company_Credit_Report.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Creditsafe/Creditsafe_Get_Company_Credit_Report.ipynb", "imports": ["requests", "naas", "pprint.pprint", "json"], "image_url": ""}, {"objectID": "99dc0ea3413e44582f05edc31fb2079f4e0778981f68d58246b80aae2b23be24", "tool": "D-Tale", "notebook": "Visualize dataframe", "action": "", "tags": ["#csv", "#pandas", "#snippet", "#read", "#dataframe", "#visualize", "#dtale", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-04-11", "description": "D-Tale is a tool that allows users to quickly and easily visualize dataframes in an interactive and intuitive way.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/D-Tale/D-Tale_Visualize_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/D-Tale/D-Tale_Visualize_dataframe.ipynb", "imports": ["pandas", "dtale", "dtale.app"], "image_url": ""}, {"objectID": "27f443089a00055bee93b043b9b42d368258d639ffac4a99a34bcac72a8c6f06", "tool": "Dash", "notebook": "Add a customisable sidebar", "action": "", "tags": ["#dash", "#offcanvas", "#sidebar", "#customisable", "#component", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook demonstrates how to use the Offcanvas component to add a customisable sidebar to your apps. It is usefull for organisations that need to add a sidebar to their Dash apps.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Add_a_customisable_sidebar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Add_a_customisable_sidebar.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.Input, Output, State, html"], "image_url": ""}, {"objectID": "800cd47399958fce0bb44cc5202abf7b490ca015760efa4088ac69124bf4787e", "tool": "Dash", "notebook": "Create Datatable With Dropdown", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Ismail Chihab", "author_url": "https://www.linkedin.com/in/ismail-chihab-4b0a04202/", "updated_at": "2023-04-12", "created_at": "2022-08-26", "description": "Create a basic table that can be updated through a dcc.dropdown menu.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Datatable_With_Dropdown.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Datatable_With_Dropdown.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, Input, Output, dcc, dash_table", "pandas"], "image_url": ""}, {"objectID": "e9818d91a4e391da8889aa702a1be52ddf216175ed60dd4ce1b70b4b4b817cd7", "tool": "Dash", "notebook": "Create Dropdown Callback", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-18", "description": "Create a basic dropdown, provide options and a value to dcc.Dropdown in that order.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Dropdown_Callback.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Dropdown_Callback.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, Input, Output, State, dcc"], "image_url": ""}, {"objectID": "0c5da456dd8bf84ccd405188c1a60872fa082aae7a99567911a59be09a5b9fcd", "tool": "Dash", "notebook": "Create Dropdown with multiples output callbacks", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-18", "description": "Create a basic dropdown, provide options and a value to dcc.Dropdown in that order.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Dropdown_with_multiples_output_callbacks.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Dropdown_with_multiples_output_callbacks.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, Input, Output, State, dcc, dash_table", "plotly.graph_objs", "dash.exceptions.PreventUpdate"], "image_url": ""}, {"objectID": "68a887dfaaa80942ddb1a232171e004e74e6ef6db41fa8bbdb0454c220e10f3e", "tool": "Dash", "notebook": "Create Interactive Plot", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-05-29", "created_at": "2023-05-25", "description": "This notebook creates an interactive plot using Dash app infrastructure.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Interactive_Plot.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Interactive_Plot.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express", "io", "requests"], "image_url": ""}, {"objectID": "1774258ba69e802f126a725e1df40f6af2f051dcc113cb134a808e1bbfbc2236", "tool": "Dash", "notebook": "Create Navbar", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#asset", "#analytics", "#navbar", "#bootstrap"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-17", "description": "A simple app demonstrating how to manually construct a navbar with a customised layout using the Navbar component and the supporting Nav, NavItem, NavLink, NavbarBrand, and NavbarToggler components.\n\nRequires dash-bootstrap-components 0.3.0 or later", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Navbar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Navbar.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, Input, Output, State"], "image_url": ""}, {"objectID": "d4243fd641f0b712b1154b26fc159e3c1bb7df479750d063f11935eef3874ac6", "tool": "Dash", "notebook": "Create Navbar board", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#asset", "#analytics", "#navbar", "#bootstrap"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-18", "description": "This notebook allows users to create a customizable navigation bar for their website or application.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Navbar_Dashboard.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Navbar_Dashboard.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, Input, Output, State, dcc"], "image_url": ""}, {"objectID": "d195aeb80452c89e129ea46a655d09b2460d9fecc0f9770ce742bf3fc6cff0e9", "tool": "Dash", "notebook": "Create Navbar Search", "action": "", "tags": ["#dash", "#snippet", "#dashboard", "#plotly", "#dash", "#analytics"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-15", "description": "This notebook provides a tutorial on how to create a searchable navigation bar using the Dash library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_Navbar_Search.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_Navbar_Search.ipynb", "imports": ["dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc", "dash.dependencies.Input, Output", "os"], "image_url": ""}, {"objectID": "4b333f42522abb0ce297502127eba3288b9cd14336f94c563c7523156c545ceb", "tool": "Dash", "notebook": "Create button to refresh page", "action": "", "tags": ["#dash", "#python", "#button", "#refresh", "#page", "#stackoverflow"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-02", "created_at": "2023-06-02", "description": "This notebook explains how to create a button in Dash to refresh the page.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_button_to_refresh_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_button_to_refresh_page.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc, Output, Input, State"], "image_url": ""}, {"objectID": "5d0ec204e1adc070996a900d4212c1d45f5925dc25a522b3e3f45b857e1e6f54", "tool": "Dash", "notebook": "Create conditional formatting on HTML element", "action": "", "tags": ["#dash", "#html", "#conditional", "#formatting", "#element", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to create conditional formatting of an HTML element using Dash.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_conditional_formatting_on_HTML_element.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_conditional_formatting_on_HTML_element.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc, Output, Input, State"], "image_url": ""}, {"objectID": "e8bf48a389426d3ffba1975c7da90f59b8784773a0440500b8d64869357abfc7", "tool": "Dash", "notebook": "Create conditional formatting on number value", "action": "", "tags": ["#dash", "#html", "#conditional", "#formatting", "#element", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to create conditional formatting of an HTML element using Dash.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_conditional_formatting_on_number_value.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_conditional_formatting_on_number_value.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc, Output, Input, State"], "image_url": ""}, {"objectID": "0884edbacf735f45bc43e534555b0b0c3293fcfe22599d60ec7a9461e2e52e7e", "tool": "Dash", "notebook": "Create download button", "action": "", "tags": ["#dash", "#button", "#download", "#create", "#python", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook will show how to create a download button with Dash.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_download_button.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_download_button.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html"], "image_url": ""}, {"objectID": "8724d5174822ed9a031f96f8bb87140b72d60f7a27a664065d744aab70131681", "tool": "Dash", "notebook": "Create loading button", "action": "", "tags": ["#dash", "#plotly", "#loading", "#button", "#python", "#web"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-02", "created_at": "2023-06-02", "description": "This notebook explains how to create a loading button with Dash Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_loading_button.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_loading_button.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "dash.Dash, html, dcc, callback, Output, Input, State", "time"], "image_url": ""}, {"objectID": "dd2c5fe6315560fa638685fb739dc1b4a6d39089220f430d269c01b78c7dd953", "tool": "Dash", "notebook": "Create spinner button", "action": "", "tags": ["#dash", "#button", "#download", "#create", "#python", "#library", "#spinner"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook will show how to create a spinner button with Dash. The `Spinner` component can be used inside buttons to indicate that an action is currently processing or taking place.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Create_spinner_button.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Create_spinner_button.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html"], "image_url": ""}, {"objectID": "162e8064b2a3e2bb21972a90cb77673df932c178555c3a985b7218c3c2786444", "tool": "Dash", "notebook": "Deploy app in Naas", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#asset", "#automation", "#analytics"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-01", "description": "This notebook provides a step-by-step guide to deploying an app with Dash on Naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Deploy_app_in_Naas.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Deploy_app_in_Naas.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc", "plotly.express", "plotly.graph_objects"], "image_url": ""}, {"objectID": "477b2f627d6fc1d842945d36a8661d2f63c69d27ec2afe9612e5ccbf54aaba0a", "tool": "Dash", "notebook": "LinkedIn posts metrics dashboard", "action": "", "tags": ["#dash", "#linkedin", "#dashboard", "#plotly", "#naas", "#asset", "#automation", "#analytics"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-06", "description": "This notebook provides a dashboard to track and analyze metrics related to LinkedIn posts.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_LinkedIn_posts_metrics_dashboard.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_LinkedIn_posts_metrics_dashboard.ipynb", "imports": ["os", "os.environ", "pandas", "naas", "datetime.datetime", "naas_drivers.gsheet", "plotly.graph_objects", "plotly.express", "plotly.subplots.make_subplots", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc, Input, Output, State", "dash_bootstrap_components._components.Container.Container", "dash.exceptions.PreventUpdate"], "image_url": ""}, {"objectID": "950b5ed31417ee13e856d45afc141338d870a01592a83e9f71131ed42d8d2f02", "tool": "Dash", "notebook": "Plotly Dynamic Link", "action": "", "tags": ["#dash", "#plotly", "#naas", "#analytics"], "author": "Oguz Akif Tufekcioglu", "author_url": "https://www.linkedin.com/in/oguzakiftufekcioglu/", "updated_at": "2023-04-12", "created_at": "2022-10-18", "description": "This notebook provides an interactive way to explore data with Dash and Plotly, allowing users to create dynamic links between visualizations.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Plotly_Dynamic_Link.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Plotly_Dynamic_Link.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "webbrowser", "dash.dependencies.Input, Output", "dash.html, dcc", "dash.exceptions.PreventUpdate", "plotly.express", "plotly.graph_objects"], "image_url": ""}, {"objectID": "506d501ebff0f9b3a6ab229a88a2464ece6c09bfdd29e7b5ce5d43731c3a3c5d", "tool": "Dash", "notebook": "Upload mutiples CSV Excel", "action": "", "tags": ["#dashboard", "#plotly", "#dash", "#naas", "#upload", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-11-22", "description": "This notebook allows users to upload multiple CSV and Excel files to create interactive visualizations with Dash.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dash/Dash_Upload_mutiples_CSV_Excel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dash/Dash_Upload_mutiples_CSV_Excel.ipynb", "imports": ["os", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.Dash, dcc, html, Input, Output, State", "pandas", "base64", "datetime", "io", "dash.dcc, html, dash_table"], "image_url": ""}, {"objectID": "61bc9b898dcd8659c49a5ac5fe46a212b5f7217286b9bccdbfec9183f9cd9732", "tool": "Dask", "notebook": "Parallelize operations on multiple csvs", "action": "", "tags": ["#csv", "#pandas", "#snippet", "#read", "#dataframe", "#parallel", "#parallelize", "#dask", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-04-13", "description": "This notebook demonstrates how to use Dask to efficiently process and analyze multiple CSV files in parallel.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Dask/Dask_parallelize_operations_on_multiple_csvs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Dask/Dask_parallelize_operations_on_multiple_csvs.ipynb", "imports": ["os", "graphviz", "graphviz", "dask.dataframe", "dask.dataframe", "pandas", "glob"], "image_url": ""}, {"objectID": "6a8d408c93bbef46e9136bfea9c5e3416c18cccde9528f35a88f44c763960c08", "tool": "Data.gouv.fr", "notebook": "COVID19 - FR - Entr\u00e9es et sorties par r\u00e9gion pour 1 million d'hab.", "action": "", "tags": ["#data.gouv.fr", "#opendata", "#france", "#analytics"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook provides an analysis of the entry and exit of one million people in each region of France due to the COVID-19 pandemic.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Data.gouv.fr/COVID19%20-%20%20FR%20-%20Entr%C3%A9es%20et%20sorties%20par%20r%C3%A9gion%20pour%201%20million%20d%27hab..ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Data.gouv.fr/COVID19%20-%20%20FR%20-%20Entr%C3%A9es%20et%20sorties%20par%20r%C3%A9gion%20pour%201%20million%20d%27hab..ipynb", "imports": ["requests", "pandas", "datetime.datetime, timedelta", "plotly.graph_objects", "plotly.subplots.make_subplots", "numpy"], "image_url": ""}, {"objectID": "2725c6bbe45eba9e5d58de0a89d96d7ad467ef8dbe42a084dbfb28b3328a03aa", "tool": "Data.gouv.fr", "notebook": "R\u00e9cup\u00e9ration donn\u00e9es l\u00e9gales entreprise", "action": "", "tags": ["#data.gouv.fr", "#snippet", "#naas", "#societe", "#opendata"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-05-04", "description": "This notebook provides a guide to retrieving legal data from data.gouv.fr for businesses.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Data.gouv.fr/Data.gouv.fr_R%C3%A9cup%C3%A9ration_donn%C3%A9es_l%C3%A9gales_entreprise.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Data.gouv.fr/Data.gouv.fr_R%C3%A9cup%C3%A9ration_donn%C3%A9es_l%C3%A9gales_entreprise.ipynb", "imports": ["requests", "pprint.pprint"], "image_url": ""}, {"objectID": "14ddb09c734bc7d6e5f8c0adfd7ac2d7c8f2002d6e506149cf3e833c788c9ce9", "tool": "Datetime", "notebook": "Calculate relative time delta between two dates", "action": "", "tags": ["#datetime", "#datetime", "#relativedelta", "#calculate", "#date", "#time", "#dateutil"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-05-22", "description": "This notebook calculates the relative time delta between two dates.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Calculate_relative_time_delta_between_two_dates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Calculate_relative_time_delta_between_two_dates.ipynb", "imports": ["datetime.datetime", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "f7399e612e827014cbd261e6dfd655c72c29ebdcaa7f136699463a2cb8d5ae82", "tool": "Datetime", "notebook": "Calculate time delta between two dates", "action": "", "tags": ["#datetime", "#timedelta", "#calculate", "#date", "#time"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-05-22", "description": "This notebook calculates the time delta between two dates.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Calculate_time_delta_between_two_dates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Calculate_time_delta_between_two_dates.ipynb", "imports": ["datetime.datetime"], "image_url": ""}, {"objectID": "ee2454efaf6543bbecbe368327aa987b1cf2c65b67a0d60de28d59966ca7e3de", "tool": "Datetime", "notebook": "Convert datetime object to a formatted date string", "action": "", "tags": ["#datetime", "#snippet", "#operations", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-07-05", "description": "This notebook provides an introduction to using the Python datetime library to work with dates and times.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Convert_datetime_object_to_string_date.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Convert_datetime_object_to_string_date.ipynb", "imports": ["datetime.datetime"], "image_url": ""}, {"objectID": "527179e27a2e54e5090aa8ae94593c5883ba100a886199344c55e8a046e103de", "tool": "Datetime", "notebook": "Convert with Timezone to ISO 8601 date string", "action": "", "tags": ["#datetime", "#timezone", "#iso8601", "#string", "#conversion"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-02-15", "description": "This notebook will demonstrate how to convert a datetime with timezone to an ISO 8601 date string.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Convert_datetime_with_timezone_to_ISO_8601_date_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Convert_datetime_with_timezone_to_ISO_8601_date_string.ipynb", "imports": ["datetime.datetime", "pytz"], "image_url": ""}, {"objectID": "2e58cf9199f74e34fc1aae9761efc23814d7a0f9ce53e6d9464203e0b82e651a", "tool": "Datetime", "notebook": "Convert relative time delta to months", "action": "", "tags": ["#datetime", "#relativedelta", "#calculate", "#date", "#time", "#dateutil"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-05-22", "description": "This notebook is designed to convert the relative time delta between two dates into months. By utilizing the `relativedelta` function, the conversion becomes more accurate compared to using `timedelta`, as `relativedelta` considers the varying number of days in each month.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Convert_relative_time_delta_to_months.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Convert_relative_time_delta_to_months.ipynb", "imports": ["datetime.datetime", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "c2bafcf6bd3d8bd05a9b45ff7085dcc9a41d4300fdb65f762e0256546d40fd20", "tool": "Datetime", "notebook": "Convert a string date to a datetime object", "action": "", "tags": ["#datetime", "#snippet", "#operations", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-05", "created_at": "2023-07-05", "description": "This notebook converts a string date to a datetime object", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Convert_string_to_datetime_object.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Convert_string_to_datetime_object.ipynb", "imports": ["datetime.datetime"], "image_url": ""}, {"objectID": "deacb63cb8ea46333f7b10672b968a20991c44cc34048cecbd7af276488cdc36", "tool": "Datetime", "notebook": "Convert timestamp to a datetime object", "action": "", "tags": ["#datetime", "#python", "#timestamp", "#convert", "#datetimeobject", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-05", "created_at": "2023-07-05", "description": "This notebook will show how to convert a timestamp to a datetime object in Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Datetime/Datetime_Convert_timestamp_to_a_datetime_object.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Datetime/Datetime_Convert_timestamp_to_a_datetime_object.ipynb", "imports": ["datetime.datetime"], "image_url": ""}, {"objectID": "898c8b8d33cadf517a47046cf51115935b579a8a1797b5c0b098af29e2075b8f", "tool": "Deepl", "notebook": "Translated string to txt", "action": "", "tags": ["#deepl", "#translate", "#text", "#txt", "#api", "#string"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook show how to translate a string with Deepl API and save it in a txt file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Deepl/Deepl_Translated_string_to_txt.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Deepl/Deepl_Translated_string_to_txt.ipynb", "imports": ["naas", "deepl", "deepl"], "image_url": ""}, {"objectID": "8f82e653557ca28f058454ad86c1553add053a2e1d00829c8a1a7cc052d5df90", "tool": "Draft Kings", "notebook": "Get MLB Moneylines", "action": "", "tags": ["#draftkings", "#mlb", "#betting", "#python", "#analytics", "#automation", "#sports", "#sports_betting", "#opendata", "#notification", "#email"], "author": "JA Williams", "author_url": "https://www.linkedin.com/in/ja-williams-529517187/", "updated_at": "2023-04-12", "created_at": "2022-06-15", "description": "This notebook provides an analysis of Major League Baseball moneylines from DraftKings.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Draft%20Kings/Draft_Kings_Get_MLB_Moneylines.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Draft%20Kings/Draft_Kings_Get_MLB_Moneylines.ipynb", "imports": ["naas", "requests", "pandas", "bs4.BeautifulSoup", "naas_drivers.emailbuilder", "datetime.datetime", "pytz"], "image_url": ""}, {"objectID": "ceb5a587fbb4c9f40cba42de520895d00c40bba339419b224bf452d40c83e02c", "tool": "Draft Kings", "notebook": "Get NBA Moneylines", "action": "", "tags": ["#draftkings", "#nba", "#betting", "#python", "#analytics", "#automation", "#sports", "#sports_betting", "#opendata", "#notification", "#email"], "author": "JA Williams", "author_url": "https://www.linkedin.com/in/ja-williams-529517187/", "updated_at": "2023-04-12", "created_at": "2022-04-13", "description": "This notebook provides an analysis of NBA Moneylines from Draft Kings to help you make informed betting decisions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Draft%20Kings/Draft_Kings_Get_NBA_Moneylines.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Draft%20Kings/Draft_Kings_Get_NBA_Moneylines.ipynb", "imports": ["naas", "requests", "pandas", "bs4.BeautifulSoup", "naas_drivers.emailbuilder", "datetime.datetime", "pytz"], "image_url": ""}, {"objectID": "543ef2600b507345bc7b6cd2db8351aaed78fab51441bd3fb69d88cc5ec3f5e2", "tool": "EM-DAT", "notebook": "Natural disasters", "action": "", "tags": ["#em-dat", "#emdat", "#opendata", "#analytics", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-28", "description": "In 1988, the Centre for Research on the Epidemiology of Disasters (CRED) launched the Emergency Events Database (EM-DAT). [EM-DAT](https://www.emdat.be/) was created with the initial support of the World Health Organisation (WHO) and the Belgian Government.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/EM-DAT/EM-DAT_natural_disasters.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/EM-DAT/EM-DAT_natural_disasters.ipynb", "imports": ["pandas", "plotly.express"], "image_url": ""}, {"objectID": "30d15767a0d67fbb7c1aa3b0d8047bf5075074c348588a11dc34cfdf9bf52161", "tool": "Elasticsearch", "notebook": "Connect to server", "action": "", "tags": ["#elasticsearch", "#elastic", "#search", "#snippet", "#operations"], "author": "Ebin Paulose", "author_url": "https://www.linkedin.com/in/ebinpaulose/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "### 1. Prerequisites", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Elasticsearch/Elasticsearch_Connect_to_server.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Elasticsearch/Elasticsearch_Connect_to_server.ipynb", "imports": ["elasticsearchconnector.ElasticsearchConnector"], "image_url": ""}, {"objectID": "ba28d491fd759da0887e597f60ac8ca271d9e76837bd293f62d2557875a1d594", "tool": "Excel", "notebook": "Apply Custom Styles", "action": "", "tags": ["#excel", "#openpyxl", "#font", "#border", "#background", "#naas", "#finance", "#snippet"], "author": "S\u00e9bastien Grech", "author_url": "https://www.linkedin.com/in/s%C3%A9bastien-grech-4433a7150/", "updated_at": "2023-04-12", "created_at": "2023-02-07", "description": "This notebook provides instructions on how to apply custom styles to an Excel spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_Apply_Custom_Styles.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_Apply_Custom_Styles.ipynb", "imports": ["naas", "openpyxl.load_workbook", "openpyxl.cell.Cell", "openpyxl.styles.Color, PatternFill, Font, Border", "openpyxl.styles.borders.Border, Side"], "image_url": ""}, {"objectID": "d90301be264b3cf72aeee61ab98051d15815adda6f6e494fc0587923ba51118d", "tool": "Excel", "notebook": "Consolidate files", "action": "", "tags": ["#excel", "#pandas", "#read", "#save", "#naas", "#asset", "#finance", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook provides a comprehensive guide to consolidating multiple Excel files into one.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_Consolidate_files.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_Consolidate_files.ipynb", "imports": ["pandas", "naas"], "image_url": ""}, {"objectID": "217fff1a4dbbe5cdb391c88dd2e230eef12ddbf46fc6b2a4b7e05c49db3758fb", "tool": "Excel", "notebook": "Get dynamic active range", "action": "", "tags": ["#excel", "#openpyxl", "#active-range", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-24", "description": "This notebook provides a method for dynamically retrieving the active range of an Excel worksheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_Get_dynamic_active_range.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_Get_dynamic_active_range.ipynb", "imports": ["openpyxl.load_workbook", "openpyxl.utils.get_column_letter"], "image_url": ""}, {"objectID": "b92ea8d1185531f94864792601a94a86b90d79e8d8da49977d1ffdc87a6cce41", "tool": "Excel", "notebook": "List sheets in workbook", "action": "", "tags": ["#excel", "#list", "#sheets", "#workbook", "#data", "#analysis"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook will list the sheet's name in an Excel workbook.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_List_sheets_in_workbook.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_List_sheets_in_workbook.ipynb", "imports": ["openpyxl", "os"], "image_url": ""}, {"objectID": "32e6a2bbb504fb622cc153607a48c61677401ab357a4d2117b6b3820be4fbd69", "tool": "Excel", "notebook": "Read file", "action": "", "tags": ["#excel", "#pandas", "#read", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook reads an Excel file and allows users to manipulate the data within it.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_Read_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_Read_file.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "89dbd7dbd81efb97de7af6a3f612379e28d249f769af1c6aaec979867b4c796b", "tool": "Excel", "notebook": "Save file", "action": "", "tags": ["#excel", "#pandas", "#save", "#opendata", "#yahoofinance", "#naas_drivers", "#finance", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-22", "description": "This notebook allows users to save their Excel files quickly and easily.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Excel/Excel_Save_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Excel/Excel_Save_file.ipynb", "imports": ["pandas", "naas_drivers.yahoofinance"], "image_url": ""}, {"objectID": "82f6147c6bace8c4fe20f3c99ff957454a2ff4a331301a7201a9f3550feb508b", "tool": "FAO", "notebook": "Consumer price indice", "action": "", "tags": ["#fao", "#opendata", "#food", "#analytics", "#plotly"], "author": "Dereck DANIEL", "author_url": "https://github.com/DANIEL-Dereck", "updated_at": "2023-04-12", "created_at": "2021-06-10", "description": "This notebook provides an analysis of the changes in consumer prices over time as measured by the Food and Agriculture Organization's Consumer Price Index.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FAO/FAO_Consumer_price_indice.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FAO/FAO_Consumer_price_indice.ipynb", "imports": ["requests, zipfile, io", "matplotlib.pyplot", "naas_drivers", "pandas", "plotly.express", "csv", "codecs", "plotly.graph_objects"], "image_url": ""}, {"objectID": "097bbecb865851c847e60decdb392721feca4070a51c0ee2a95069f1b539e0a7", "tool": "FEC", "notebook": "Creer un dashboard PowerBI", "action": "", "tags": ["#fec", "#powerbi", "#dataviz", "#analytics", "#finance"], "author": "Alexandre STEVENS", "author_url": "https://www.linkedin.com/in/alexandrestevenspbix/", "updated_at": "2023-04-12", "created_at": "2021-08-17", "description": "This notebook provides instructions for creating a PowerBI dashboard to visualize Federal Election Commission (FEC) data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Creer_un_dashboard_PowerBI.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Creer_un_dashboard_PowerBI.ipynb", "imports": ["pandas", "datetime.datetime, timedelta", "os", "re", "naas", "json"], "image_url": ""}, {"objectID": "05f3e5c7ae59b593be99118e8041cef4b465f18e633b6f8afc3b889762a1bb58", "tool": "FEC", "notebook": "Lecture des fichiers", "action": "", "tags": ["#fec", "#lecture", "#fichiers", "#python", "#data", "#analyse"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to read files with Python and how it is usefull for organization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Lecture_des_fichiers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Lecture_des_fichiers.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "ae95a038ed1b23ff84eb40e19039601cba8278c3d969caa4124defd23ecdca63", "tool": "FEC", "notebook": "Visualiser Bilan Treemap", "action": "", "tags": ["#fec", "#plotly", "#treemap", "#snippet", "#dataviz"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-31", "description": "Ce notebook affiche les \u00e9l\u00e9ments du bilan sous forme de graphique treemap. Le graphique \"treemap\" est tr\u00e8s utile pour montrer la r\u00e9partition des actifs et des passifs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Visualiser_Bilan_Treemap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Visualiser_Bilan_Treemap.ipynb", "imports": ["plotly.graph_objects", "plotly.subplots.make_subplots", "pandas", "naas"], "image_url": ""}, {"objectID": "f7c01654a85e3e8cfadc6c93c2c38c27b13bf29df99a6094094bae4462f19abc", "tool": "FEC", "notebook": "Visualiser Charges Horizontal Barchart", "action": "", "tags": ["#fec", "#plotly", "#horizontalbarchart", "#visualisation", "#charges", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-23", "description": "Ce notebook vous permettra de visualiser les charges de votre entreprise \u00e0 l'aide d'un barchart horizontal.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Visualiser_Charges_Horizontal_Barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Visualiser_Charges_Horizontal_Barchart.ipynb", "imports": ["plotly.graph_objects", "pandas", "naas"], "image_url": ""}, {"objectID": "6741d446a829e89f2b656fe139e0319b2cd7c49feb3643bb10209e4dfdfe9d2d", "tool": "FEC", "notebook": "Visualiser Comparer Ventes Line Chart", "action": "", "tags": ["#fec", "#plotly", "#naas", "#snippet", "#operations", "#linechart"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-02-08", "description": "Ce notebook vous permettra de visualiser et comparer les ventes de votre entreprise pour les p\u00e9riodes N et N-1 \u00e0 l'aide de deux courbes de tendance. Vous pourrez facilement voir les tendances et les diff\u00e9rences entre les deux p\u00e9riodes pour prendre des d\u00e9cisions \u00e9clair\u00e9es pour am\u00e9liorer vos ventes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Visualiser_Comparer_Ventes_Line_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Visualiser_Comparer_Ventes_Line_Chart.ipynb", "imports": ["plotly.graph_objects", "plotly.subplots.make_subplots", "pandas", "naas", "random"], "image_url": ""}, {"objectID": "d73ae271b1557432c42c76c41c62f94628dd97120e11e41b0f1c0f0eee97a9c5", "tool": "FEC", "notebook": "Visualiser Tr\u00e9sorerie Barline Chart", "action": "", "tags": ["#fec", "#plotly", "#naas", "#snippet", "#operations", "#barline"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-02-08", "description": "Ce notebook vous permettra de visualiser la tr\u00e9sorerie de votre entreprise \u00e0 l'aide d'un diagramme de barres. Vous pourrez facilement suivre les entr\u00e9es et les sorties d'argent, ce qui vous aidera \u00e0 mieux comprendre la situation financi\u00e8re de votre entreprise.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FEC/FEC_Visualiser_Tr%C3%A9sorerie_Barline_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FEC/FEC_Visualiser_Tr%C3%A9sorerie_Barline_Chart.ipynb", "imports": ["plotly.graph_objects", "plotly.subplots.make_subplots", "pandas", "naas", "random"], "image_url": ""}, {"objectID": "3d5d98e21d25b8ffe3b8c6deb3b9d8beecba5a65754590a020591220885efdd0", "tool": "FED", "notebook": "Visualize Inflation Rate", "action": "", "tags": ["#fed", "#inflation_rate", "#vizualization", "#plotly"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-04-12", "created_at": "2023-04-06", "description": "This notebook vizualize the inflation rate of the US using plotly and fred api", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FED/FED_Visualize_Inflation_Rate.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FED/FED_Visualize_Inflation_Rate.ipynb", "imports": ["naas", "pandas", "plotly.express", "fredapi.Fred", "fredapi.Fred"], "image_url": ""}, {"objectID": "3bf073466b39d2c379ef627157f0279dece8ae6a7edb3238fc59b4282a76417a", "tool": "FTP", "notebook": "S Connect", "action": "", "tags": ["#ftp", "#ftps", "#file", "#naas_drivers", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook provides a guide to setting up an FTP connection to securely transfer files between two computers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FTP/FTPS_Connect.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FTP/FTPS_Connect.ipynb", "imports": ["naas_drivers.ftp"], "image_url": ""}, {"objectID": "69af686c106175459bb5ebbe8514346705fe801d27fdfd2f8ce9956d411fc755", "tool": "FTP", "notebook": "Connect", "action": "", "tags": ["#ftp", "#file", "#naas_drivers", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook provides instructions on how to connect to an FTP server.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FTP/FTP_Connect.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FTP/FTP_Connect.ipynb", "imports": ["naas_drivers.ftp"], "image_url": ""}, {"objectID": "b17b56d2b058f53c97a81c8cd360ad2fcc3a6f08d49c9a493fa8a6fd92127173", "tool": "FTP", "notebook": "Get file", "action": "", "tags": ["#ftp", "#file", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook retrieves a file from an FTP server.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FTP/FTP_Get_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FTP/FTP_Get_file.ipynb", "imports": ["naas_drivers.ftp"], "image_url": ""}, {"objectID": "a228c9862a9e8eb6ff9cad6f815931ec3d02927ee30a1123dfe647d9836b2b05", "tool": "FTP", "notebook": "Send file", "action": "", "tags": ["#ftp", "#file", "#naas_drivers", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook allows users to securely transfer files to a remote server using the File Transfer Protocol (FTP).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/FTP/FTP_Send_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/FTP/FTP_Send_file.ipynb", "imports": ["naas_drivers.ftp"], "image_url": ""}, {"objectID": "d81834f3139bb9d206b4f2e2248280d5de152a4eff80dd9c2012832b7080367f", "tool": "Faker", "notebook": "Anonymize Address from dataframe", "action": "", "tags": ["#faker", "#operations", "#snippet", "#database", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-09", "description": "This notebook provides a way to anonymize address data from a dataframe using the Faker library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Faker/Faker_Anonymize_Address_from_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Faker/Faker_Anonymize_Address_from_dataframe.ipynb", "imports": ["faker.Faker", "faker.Faker", "pandas"], "image_url": ""}, {"objectID": "58a9c428e21814107d47582ef149ba3f79b5f26652ec3e6540d894662f3dd956", "tool": "Faker", "notebook": "Anonymize Personal Names from dataframe", "action": "", "tags": ["#faker", "#operations", "#snippet", "#database", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-09", "description": "This notebook provides a way to anonymize personal names from a dataframe using the Faker library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Faker/Faker_Anonymize_Personal_Names_from_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Faker/Faker_Anonymize_Personal_Names_from_dataframe.ipynb", "imports": ["faker.Faker", "faker.Faker", "pandas"], "image_url": ""}, {"objectID": "4580c539c8dc22fe627c347782220eb1211d51d3ac534c0074061911c83afbab", "tool": "Folium", "notebook": "Add markers on map", "action": "", "tags": ["#folium", "#map", "#markers", "#snippet"], "author": "Florent Ravenel", "author_url": "www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook demonstrates how to add markers on a map using `folium`.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Folium/Folium_Add_markers_on_map.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Folium/Folium_Add_markers_on_map.ipynb", "imports": ["folium", "folium"], "image_url": ""}, {"objectID": "cccf6467c3889278ee01c94fc28e2e0c58a81c12959ef887209eb2206a85971c", "tool": "Folium", "notebook": "Build route maps", "action": "", "tags": ["#folium", "#maps", "#routes", "#python", "#visualization", "#data"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will show how to use Folium to build route maps.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Folium/Folium_Build_route_maps.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Folium/Folium_Build_route_maps.ipynb", "imports": ["folium", "folium"], "image_url": ""}, {"objectID": "0b4cee6175ae01bdba70e486dae08388db62860db483724d3feb06a0fbe59a94", "tool": "Folium", "notebook": "Create map", "action": "", "tags": ["#folium", "#map", "#leaflet", "#snippet"], "author": "Florent Ravenel", "author_url": "www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook creates a map with Folium and Leaflet.js.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Folium/Folium_Create_map.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Folium/Folium_Create_map.ipynb", "imports": ["folium", "folium"], "image_url": ""}, {"objectID": "92843af029dccefb840512cc32f2146422288d20bf883643c3012da6da46c604", "tool": "Forecast", "notebook": "List all assignments", "action": "", "tags": ["#forecast", "#assignments", "#api", "#list", "#python", "#get"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-08", "created_at": "2023-08-08", "description": "This notebook will list all assignments from the forecast API. Forecast is a service that connects to harvest and allows you to plan for allocations to harvest projects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Forecast/Forecast_List_all_assignments.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Forecast/Forecast_List_all_assignments.ipynb", "imports": ["requests", "pandas", "naas", "datetime"], "image_url": ""}, {"objectID": "ec42b7671812e53369957d3aed72789a828f597c008d8b93070df4e423e92c8c", "tool": "Forecast", "notebook": "List all clients", "action": "", "tags": ["#forecast", "#clients", "#api", "#list", "#python", "#get"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-08", "created_at": "2023-08-08", "description": "This notebook will list all clients from the forecast API. Forecast is a service that connects to harvest and allows you to plan for allocations to harvest projects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Forecast/Forecast_List_all_clients.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Forecast/Forecast_List_all_clients.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "1e3981cbb25a39575b8a02a7f99ced455da1778da4ea90bffc9e80a5fc67ae76", "tool": "Forecast", "notebook": "List all people", "action": "", "tags": ["#forecast", "#people", "#api", "#list", "#python", "#get"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-07", "created_at": "2023-08-07", "description": "This notebook will list all people from the forecast API. Forecast is a service that connects to harvest and allows you to plan for allocations to harvest projects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Forecast/Forecast_List_all_people.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Forecast/Forecast_List_all_people.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "f0fba9e2e8ab797314e1454cd85c86759be2856b0c0fffa55a916148ae49d9b3", "tool": "Forecast", "notebook": "List all projects", "action": "", "tags": ["#forecast", "#projects", "#api", "#list", "#python", "#get"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-08", "created_at": "2023-08-08", "description": "This notebook will list all projects from the forecast API. Forecast is a service that connects to harvest and allows you to plan for allocations to harvest projects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Forecast/Forecast_List_all_projects.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Forecast/Forecast_List_all_projects.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "25c79c072793ed9689fec890977052fa9dd7977df1e8fb6e9832aa77df17f10f", "tool": "Formant", "notebook": "Query Device Network", "action": "", "tags": ["#formant", "#matplotlib", "#notification", "#email", "#image"], "author": "Nicolas Binford", "author_url": "https://www.linkedin.com/in/nicolasbinford", "updated_at": "2023-05-25", "created_at": "2023-05-25", "description": "This notebook queries network data over a period of time from a Formant device, graphs it, and emails the images.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Formant/Formant_Query_Device_Network.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Formant/Formant_Query_Device_Network.ipynb", "imports": ["datetime.datetime, timedelta", "dateutil.parser", "numpy", "matplotlib.pyplot", "os", "naas", "formant.sdk.cloud.v2.Client", "formant.sdk.cloud.v2.formant_admin_api_client.models.device_query.(", "formant.sdk.cloud.v2.formant_admin_api_client.models.event_query.(", "formant.sdk.cloud.v2.formant_admin_api_client.models.event_list_response.(", "formant.sdk.cloud.v2.formant_query_api_client.models.query.Query"], "image_url": ""}, {"objectID": "afb1d171e3d6d01f64e538e5218cb05bcb151bbf7b3bdc4aede393413b6795d8", "tool": "Geopy", "notebook": "Calculate distance between two locations in kilometers", "action": "", "tags": ["#geopy", "#distance", "#navigation", "#snippet"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to calculate distance between two locations in kilometers using `geopy`.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Calculate_distance_between_two_locations_in_km.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Calculate_distance_between_two_locations_in_km.ipynb", "imports": ["geopy.geocoders.Nominatim", "geopy.distance.geodesic"], "image_url": ""}, {"objectID": "63101b2ad458f9d789b07b0da6879d15330e9333534fcf1bfa68256633388959", "tool": "Geopy", "notebook": "Calculate distance between two locations in miles", "action": "", "tags": ["#geopy", "#distance", "#navigation", "#snippet"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to calculate distance between two locations in miles using `geopy`.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Calculate_distance_between_two_locations_in_miles.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Calculate_distance_between_two_locations_in_miles.ipynb", "imports": ["geopy.geocoders.Nominatim", "geopy.distance.geodesic"], "image_url": ""}, {"objectID": "993ce0d908ba89f3ea2afcdec012b379878997c9398eb0fd49ef9cfb39647805", "tool": "Geopy", "notebook": "Display markers on map from addresses", "action": "", "tags": ["#geopy", "#folium", "#operations", "#navigation"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to display markers on a map from addresses using `geopy` and `folium`.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Display_markers_on_map.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Display_markers_on_map.ipynb", "imports": ["geopy.geocoders.Nominatim", "folium", "folium"], "image_url": ""}, {"objectID": "1c652e1306432bebf00b0ff980057b2b61e37ea66a9f78d36593e441fadda873", "tool": "Geopy", "notebook": "Display route itinerary between two locations", "action": "", "tags": ["#geopy", "#folium", "#polyline", "#googlemaps", "#itinerary", "#navigation"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to display a route initnerary between two locations using `geopy`, `folium`, `polyline` and Google Maps API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Display_route_itinerary_between_two_locations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Display_route_itinerary_between_two_locations.ipynb", "imports": ["geopy.geocoders.Nominatim", "polyline", "folium", "naas", "requests"], "image_url": ""}, {"objectID": "63fd46f3d47b86684983e648b8ce1b52533ad5e25df8521927f614d42973c09e", "tool": "Geopy", "notebook": "Get address from coordinates", "action": "", "tags": ["#geopy", "#coordinates", "#address", "#navigation", "#snippet"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to utilize Geopy to convert a location(latitude and longitude) to its corresponding address.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Get_address_from_coordinates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Get_address_from_coordinates.ipynb", "imports": ["geopy.geocoders.Nominatim"], "image_url": ""}, {"objectID": "e58363280d4ff558e10c90bb9294d8ad7f0467db115d5dca1be059dc911939f5", "tool": "Geopy", "notebook": "Get coordinates from address", "action": "", "tags": ["#geopy", "#coordinates", "#address", "#navigation", "#snippet"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook demonstrates how to utilize Geopy to the coordinates(longitude and latitude) of a given address.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Geopy/Geopy_Get_coordinates_from_address.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Geopy/Geopy_Get_coordinates_from_address.ipynb", "imports": ["geopy.geocoders.Nominatim"], "image_url": ""}, {"objectID": "b8a92a0e4b6e40db304564f999566443fb35e93df716ab4be5021aabba8230ee", "tool": "GitHub", "notebook": "Add new issues as page in Notion database", "action": "", "tags": ["#github", "#notion", "#operations", "#automation"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-05-12", "description": "This notebook allows users to add new GitHub issues as pages in a Notion database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Add_new_issues_as_page_in_Notion_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Add_new_issues_as_page_in_Notion_database.ipynb", "imports": ["naas", "naas_drivers.notion, github"], "image_url": ""}, {"objectID": "bcda82e2ccc375448f59bfea7ab1cc6a9c5e3388650e69034914e132319a5924", "tool": "GitHub", "notebook": "Add new member to team", "action": "", "tags": ["#github", "#teams", "#snippet", "#operations", "#invitations"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-05-07", "description": "This notebook provides instructions on how to add a new member to a GitHub team.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Add_new_member_to_team.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Add_new_member_to_team.ipynb", "imports": ["requests", "naas_drivers.github", "pandas", "naas"], "image_url": ""}, {"objectID": "10bd58b431807c01460f0309cd7ee2b2a7e2a61e38cbabc60c0fc2b439b9d309", "tool": "GitHub", "notebook": "Add or update team membership for a user", "action": "", "tags": ["#github", "#teams", "#members", "#api", "#rest", "#python"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-26", "created_at": "2023-04-18", "description": "This notebook add or update team membership for a user.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Add_or_update_team_membership_for_a_user.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Add_or_update_team_membership_for_a_user.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "b8cc352b30977a358e1bb8128a3462f0e6385185fe45c76b5b5a83a702223d3f", "tool": "GitHub", "notebook": "Clone open branches from repository on my local", "action": "", "tags": ["#github", "#snippet", "#operations", "#repository", "#efficiency"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook streamlines your workflow by cloning open branches from a GitHub repository to your local machine, renaming the repository to match the branch name, and switching to the respective branch. This approach enhances efficiency by enabling you to work on multiple branches simultaneously without the need to constantly switch, thus avoiding conflicts. Before using this on Naas, ensure your SSH is properly configured (you can use the Naas_Configure_SSH.ipynb template for this).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Clone_open_branches_from_repository_on_my_local.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Clone_open_branches_from_repository_on_my_local.ipynb", "imports": ["os", "naas", "pandas", "requests"], "image_url": ""}, {"objectID": "9a285091900a306e1d94106e8130989f033c65589f2bc28dc7515436d73a5af4", "tool": "GitHub", "notebook": "Clone repository", "action": "", "tags": ["#github", "#snippet", "#operations", "#repository"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-09", "created_at": "2022-12-07", "description": "**References:**\n- [GitHub Documentation - Cloning a repository](https://docs.github.com/en/github/creating-cloning-and-archiving-repositories/cloning-a-repository)", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Clone_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Clone_repository.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "ff694fb2b2ebce38feccd3e1bef21019cdb9994ae3cf4f6fdc0ab7e317c15f22", "tool": "GitHub", "notebook": "Clone repository and switch branch", "action": "", "tags": ["#github", "#clone", "#repository", "#branch", "#switch", "#git"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-09", "created_at": "2023-05-09", "description": "This notebook clones a branche from a GitHub repository to your local machine, rename the repository with the branch name, and switch to it to the designated branch. This approach enhances efficiency by enabling you to work on multiple branches simultaneously without the need to constantly switch, thus avoiding conflicts. Before using this on Naas, ensure your SSH is properly configured (you can use the Naas_Configure_SSH.ipynb template for this).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Clone_repository_and_switch_branch.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Clone_repository_and_switch_branch.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "6bba57317ecb03136235cc932153d2657c0ddffeb2ea0290584824b427ae4d76", "tool": "GitHub", "notebook": "Close issue", "action": "", "tags": ["#github", "#issues", "#update", "#rest", "#api", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2022-03-18", "description": "This notebook explains how to close an issue on GitHub using the REST API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Close_issue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Close_issue.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "243aca01f02c1bd1deb2c0157c3fce1ea04ac03c9e2f8df73d9cd04128dafc90", "tool": "GitHub", "notebook": "Create Repo", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet"], "author": "Kanishk Pareek", "author_url": "https://in.linkedin.com/in/kanishkpareek/", "updated_at": "2023-04-12", "created_at": "2023-02-28", "description": "This notebook provides instructions on how to create a repository on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_Repo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_Repo.ipynb", "imports": ["requests", "json"], "image_url": ""}, {"objectID": "cffce74b26b67e98eceee05e167b0db356b2dd610bd6e82d7a8e28e2c50398a9", "tool": "GitHub", "notebook": "Create an issue comment", "action": "", "tags": ["#github", "#issue", "#comment", "#api", "#python", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2023-05-26", "description": "This notebook shows how to add a comment to an issue on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_an_issue_comment.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_an_issue_comment.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "d735705c15fc17370b8e6a4cb688184c65210cbb249e2466dfa2b754b47b07b9", "tool": "GitHub", "notebook": "Create issue", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides instructions on how to create an issue on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_issue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_issue.ipynb", "imports": ["github.Github"], "image_url": ""}, {"objectID": "58d4c2b5a700d444c161aa052156ca47ffb7642a2e44c771125cac9a6fe04edc", "tool": "GitHub", "notebook": "Create leaderboard of contributors", "action": "", "tags": ["#github", "#repos", "#commits", "#stats", "#naas_drivers", "#leaderboard", "#commitsPoints"], "author": "Suhas B", "author_url": "https://www.linkedin.com/in/suhasbrao/", "updated_at": "2023-04-12", "created_at": "2023-02-01", "description": "## Input", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_leaderboard_of_contributors.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_leaderboard_of_contributors.ipynb", "imports": ["pandas", "plotly.express", "naas_drivers.github", "naas", "requests", "urllib.parse.urlencode"], "image_url": ""}, {"objectID": "8ae2c7c1e9a984b87050a86432e0e8d09f71f62e51e2bb84533b97ad4494e04d", "tool": "GitHub", "notebook": "Create newsletter based on repository activity", "action": "", "tags": ["#tool", "#naas_drivers", "#naas", "#scheduler", "#asset", "#snippet", "#automation", "#ai", "#newsletter"], "author": "Suhas B", "author_url": "https://www.linkedin.com/in/suhasbrao/", "updated_at": "2023-04-12", "created_at": "2023-02-28", "description": "This notebook allows users to create newsletters based on their repository activity on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_newsletter_based_on_repository_activity.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_newsletter_based_on_repository_activity.ipynb", "imports": ["naas_drivers.github", "naas", "markdown2", "IPython.core.display.display, HTML", "datetime", "pandas", "requests", "urllib.parse.urlencode"], "image_url": ""}, {"objectID": "13d50e7c0ca00c6a1963a5a2180ad159bd9cd0db2fd8143fbe18ca655d99dc4a", "tool": "GitHub", "notebook": "Create pull request", "action": "", "tags": ["#github", "#pygithub", "#pullrequest", "#create", "#assign", "#issue"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook creates a pull request using pygithub library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_pull_request.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_pull_request.ipynb", "imports": ["github", "github", "naas"], "image_url": ""}, {"objectID": "45e3c14a696be711aaa32ba00141daa87f830e1d23755fa0a4974ebf66cc81ef", "tool": "GitHub", "notebook": "Create repository on personal account", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet"], "author": "Kanishk Pareek", "author_url": "https://in.linkedin.com/in/kanishkpareek/", "updated_at": "2023-04-12", "created_at": "2022-10-04", "description": "This notebook provides instructions on how to create a repository on a personal GitHub account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Create_repository_on_personal_account.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Create_repository_on_personal_account.ipynb", "imports": ["requests", "json"], "image_url": ""}, {"objectID": "7c337804978be615c8e4cf519d6575a8e16fe0b28e5c250c52393e3a5588e4d5", "tool": "GitHub", "notebook": "Delete an issue comment", "action": "", "tags": ["#github", "#issue", "#comment", "#api", "#python", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2023-05-26", "description": "This notebook shows how to delete a comment to an issue on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Delete_an_issue_comment.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Delete_an_issue_comment.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "dbff6f5f2fa8547e5d0a19beb2643be87b924ee91e01121e3d37985bac070cd8", "tool": "GitHub", "notebook": "Download Excel file from URL", "action": "", "tags": ["#github", "#excel", "#download", "#url", "#file", "#python"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook explains how to download an Excel file stored on a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Download_Excel_file_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Download_Excel_file_from_URL.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "328cf85beb39894413fcc4034f6c1a7deb5729e38b294307534bf49013c42ba5", "tool": "GitHub", "notebook": "Download file from url", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-24", "created_at": "2022-03-18", "description": "This notebook provides instructions on how to download a file from a URL using GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Download_file_from_url.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Download_file_from_url.ipynb", "imports": ["requests", "naas", "uuid", "urllib.parse"], "image_url": ""}, {"objectID": "1002d8195ec68aad7c2c4d45777ae51f859a5f5aaac8f2e7596fbf46203b65ff", "tool": "GitHub", "notebook": "Download repository from URL", "action": "", "tags": ["#github", "#download", "#repository", "#url", "#api", "#zip"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-10", "description": "This notebook explains how to download a repository from a URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Download_repository_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Download_repository_from_URL.ipynb", "imports": ["requests", "urllib", "os", "zipfile"], "image_url": ""}, {"objectID": "ac33d518bc759838d5a1b8a6392baae861e48fdde87d5d10539c3e8768ea2346", "tool": "GitHub", "notebook": "Follow stargazers trend", "action": "", "tags": ["#github", "#stars", "#stargazers", "#naas_drivers", "#operations", "#analytics", "#html", "#plotly", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook creates a linechart to follow the trend of stars received on a specific repository. A csv, html and png files will be created as output with the possibility to be shared with a naas asset link.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Follow_stargazers_trend.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Follow_stargazers_trend.ipynb", "imports": ["pandas", "datetime.datetime", "plotly.graph_objects", "naas_drivers.github", "naas"], "image_url": ""}, {"objectID": "320908ffbe4931be40be2e749cd53cef0ae7448e70673b5b014314e7535adf59", "tool": "GitHub", "notebook": "Get DataFrame with issue estimate from project view", "action": "", "tags": ["#github", "#dataframe", "#beautifulsoup", "#projectview", "#scraping", "#python"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook demonstrates how to retrieve a dataframe containing issue estimates from the project view using BeautifulSoup. Since GitHub's API doesn't offer a way to fetch issue estimates directly, this method allows us to obtain these estimates and generate statistics by assignee and iteration. To use this template, you must create a view with columns in the following order:\n- Issue Title\n- Assginees\n- Estimate\n- LinkedIn pull request", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_DataFrame_with_issue_estimate_from_project_view.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_DataFrame_with_issue_estimate_from_project_view.ipynb", "imports": ["requests", "bs4.BeautifulSoup", "pandas", "IPython.display.display"], "image_url": ""}, {"objectID": "2d6e1a35712e37dcf78b873d165069cce01361f5c3800ddca0f1455a215c6bfd", "tool": "GitHub", "notebook": "Get Traffic Clones on repository", "action": "", "tags": ["#github", "#api", "#traffic", "#clones", "#plotly", "#linechart"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-08", "description": "This notebook will show how to get traffic clones on a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_Traffic_Clones_on_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_Traffic_Clones_on_repository.ipynb", "imports": ["requests", "naas", "pprint.pprint", "pandas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "f9bebb30e5a9beff438ea68ecfd4766b58d80a7990a9a745ed628ab82c295b14", "tool": "GitHub", "notebook": "Get Traffic Views on repository", "action": "", "tags": ["#github", "#api", "#traffic", "#views", "#plotly", "#linechart", "#analytics"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-16", "description": "This notebook will show how to get traffic views on a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_Traffic_Views_on_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_Traffic_Views_on_repository.ipynb", "imports": ["requests", "naas", "pprint.pprint", "pandas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "c8a8977c13770d7cc1a9709d463a6c9b394b327ba768a497ede1e05dda40b7d7", "tool": "GitHub", "notebook": "Get a repository", "action": "", "tags": ["#github", "#pygithub", "#repository", "#get", "#rest", "#api"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-05", "description": "This notebook will show how to get a repository using pygithub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_a_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_a_repository.ipynb", "imports": ["naas", "github"], "image_url": ""}, {"objectID": "1626bc2443cb5ef3c6ac18d27f82fe1dfcdbc8845c38d45ca30b4f7eeaf7dbf2", "tool": "GitHub", "notebook": "Get active projects", "action": "", "tags": ["#github", "#projects", "#operations", "#snippet", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides an overview of active projects on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_active_projects.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_active_projects.ipynb", "imports": ["naas_drivers.github"], "image_url": ""}, {"objectID": "f89b6e0c45286c0029ace95a4357a4d498a9b31f5c1625082e26eb2ff82e1bf7", "tool": "GitHub", "notebook": "Get commits from repository", "action": "", "tags": ["#github", "#repos", "#commits", "#stats", "#naas_drivers", "#plotly", "#linechart", "#operations", "#analytics", "#dataframe", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-09", "description": "This notebook provides a tutorial on how to retrieve a list of commits for a specific repository on GitHub using the GitHub API. It covers how to set up a personal access token for accessing the API, how to get commits using naas_drivers.github. The output returned is a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_commits_from_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_commits_from_repository.ipynb", "imports": ["naas_drivers.github", "datetime.datetime", "naas"], "image_url": ""}, {"objectID": "4f2312393c84b6863a931e5e5af8c99bd0ea48b34dfeda84093855cca17b510e", "tool": "GitHub", "notebook": "List commits history from file path", "action": "", "tags": ["#github", "#commits", "#history", "#snippet", "#operations", "#tracking"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-03", "created_at": "2023-07-03", "description": "This notebook demonstrateshow to retrieve a list of commits containing a file path that exists in master branch.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_commits_history_from_file_path.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_commits_history_from_file_path.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "19d43ffdcf1cb2f75a558259f7cfc3eed25577effd5690eb7a64e81cfacc9da9", "tool": "GitHub", "notebook": "Get commits ranking from repository", "action": "", "tags": ["#github", "#repos", "#commits", "#stats", "#naas_drivers", "#plotly", "#linechart", "#operations", "#analytics", "#dataframe", "#html"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a way to view the commit rankings of a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_commits_ranking_from_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_commits_ranking_from_repository.ipynb", "imports": ["pandas", "plotly.express", "naas_drivers.github", "naas"], "image_url": ""}, {"objectID": "1128f006266221999d8fbaa49d9e373c698e9b5c08a0ecefbe8eaa41795d69ee", "tool": "GitHub", "notebook": "Get files added on pull request", "action": "", "tags": ["#github", "#pullrequest", "#files", "#merge", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-13", "description": "This notebook get the files added on a pull request using the GitHub API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_files_added_on_pull_request.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_files_added_on_pull_request.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "c8b1218b10d5fedf3def66d9c7037ad6ee1b3b7f9bdb949ea73cce5d41dcf544", "tool": "GitHub", "notebook": "Get files changed on pull request", "action": "", "tags": ["#github", "#pullrequest", "#files", "#api", "#python", "#git"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook get the list of files changed on a pull request using the GitHub API. Files changed could be 'added', 'renamed' or 'removed'.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_files_changed_on_pull_request.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_files_changed_on_pull_request.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "bb644c3ac7177413c1f9b04a3a8d8d2f6d337072807baf2ec8dbe0af0192458c", "tool": "GitHub", "notebook": "Get issues from repo", "action": "", "tags": ["#github", "#repos", "#issues", "#operations", "#analytics", "#dataframe", "#html", "#plotly"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows users to retrieve issues from a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_issues_from_repo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_issues_from_repo.ipynb", "imports": ["naas_drivers.github"], "image_url": ""}, {"objectID": "f8b2a5b06ad0b1bc4d25de7e3aa1130a926d75e334885b7f4ad7abe3b774087d", "tool": "GitHub", "notebook": "Get most starred repos", "action": "", "tags": ["#github", "#repos", "#stars", "#snippet"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190", "updated_at": "2023-04-12", "created_at": "2022-06-06", "description": "This notebook provides a list of the most popular GitHub repositories based on the number of stars they have received.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_most_starred_repos.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_most_starred_repos.ipynb", "imports": ["requests", "pandas", "plotly.express", "naas"], "image_url": ""}, {"objectID": "bd51601dc7146cccf78e53232a470ddde08272706420c31e7494698e0fe8b38e", "tool": "GitHub", "notebook": "Get open pull requests", "action": "", "tags": ["#github", "#repos", "#pulls", "#PR", "#operations", "#analytics", "#plotly", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook retrieves pull requests from a repository URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_open_pull_requests.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_open_pull_requests.ipynb", "imports": ["naas_drivers.github", "naas"], "image_url": ""}, {"objectID": "567fd994f272de8dda30cabbcd7b893fea10b7cd949e94decd11cfa77224af3e", "tool": "GitHub", "notebook": "Get profile from user", "action": "", "tags": ["#github", "#user", "#profile", "#operations", "#snippet", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a way to retrieve a user's profile information from GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_profile_from_user.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_profile_from_user.ipynb", "imports": ["naas_drivers.github"], "image_url": ""}, {"objectID": "131faef4977e217b5cc7c313edb1d08a280bd20881389b14ed6a925bc25a3bab", "tool": "GitHub", "notebook": "Get profiles from teams", "action": "", "tags": ["#github", "#team", "#operations", "#snippet", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows users to retrieve profiles from teams on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_profiles_from_teams.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_profiles_from_teams.ipynb", "imports": ["naas_drivers.github"], "image_url": ""}, {"objectID": "cff3ad5e2da30b6e823aef6421cf3d08a71a70e60c8fde077ba9952f06c9624e", "tool": "GitHub", "notebook": "Get team membership for a user", "action": "", "tags": ["#github", "#teams", "#members", "#rest", "#api", "#python", "#snippet"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-26", "created_at": "2023-04-18", "description": "This notebook get team membership for a user. It will return a dictionary with the state, role and url of the membership.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_team_membership_for_a_user.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_team_membership_for_a_user.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "8a639940269e34df28bbdefbea42c889370febabbb161f8d5d31cc5772689c93", "tool": "GitHub", "notebook": "Get weekly commits from repository", "action": "", "tags": ["#github", "#repos", "#commits", "#stats", "#naas_drivers", "#plotly", "#linechart", "#operations", "#analytics", "#dataframe", "#html"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a weekly summary of commits made to a GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Get_weekly_commits_from_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Get_weekly_commits_from_repository.ipynb", "imports": ["pandas", "plotly.express", "naas_drivers.github", "naas"], "image_url": ""}, {"objectID": "5494d12097ff82773cb0889f21a3f00dc84f32169f334038fc77493d818710ef", "tool": "GitHub", "notebook": "List all pull requests", "action": "", "tags": ["#github", "#pygithub", "#repo", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook list all pull requests from a repository name using pygithub library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_all_pull_requests.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_all_pull_requests.ipynb", "imports": ["os", "json", "github.Github", "naas"], "image_url": ""}, {"objectID": "9c502c94394240a77a6261022e61b720843f587f1694bc5067f24e85ca04b1cf", "tool": "GitHub", "notebook": "List branches", "action": "", "tags": ["#github", "#branches", "#list", "#api", "#rest", "#python"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-26", "created_at": "2023-06-20", "description": "This notebook will list all branches from a given GitHub repository;", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_branches.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_branches.ipynb", "imports": ["naas", "pandas", "github.Github", "github.Github", "pprint.pprint"], "image_url": ""}, {"objectID": "8f69f5fa373908c7173719e4b762a4944449492ad6b68e4fff8be0a5650d9fe2", "tool": "GitHub", "notebook": "List branches with open PR", "action": "", "tags": ["#github", "#branches", "#list", "#api", "#rest", "#python", "#active"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-26", "created_at": "2023-06-26", "description": "This notebook will list branches with open PR from a given GitHub repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_branches_with_open_PR.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_branches_with_open_PR.ipynb", "imports": ["naas", "pandas", "requests", "pprint.pprint"], "image_url": ""}, {"objectID": "087ed8be214fa3812d0506587434b69b44b3c162378979f98d3ac937c1609f9d", "tool": "GitHub", "notebook": "List closed pull requests", "action": "", "tags": ["#github", "#pygithub", "#closedpr", "#repo", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook list closed pull requests from a repository name using pygithub library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_closed_pull_requests.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_closed_pull_requests.ipynb", "imports": ["os", "json", "github.Github", "naas"], "image_url": ""}, {"objectID": "0acd7acb64f20d87ed237d4c909f9743978f067f9d98836c6ff364c577fa8d3b", "tool": "GitHub", "notebook": "List issue comments", "action": "", "tags": ["#github", "#issue", "#comment", "#api", "#python", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2023-05-26", "description": "This notebook shows how to list comments from an issue on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_issue_comments.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_issue_comments.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "09d2ca4100cec4201ff843f1c383df5e6e7f88a4dc162fc65c8bf0d33675bd6e", "tool": "GitHub", "notebook": "List open pull requests", "action": "", "tags": ["#github", "#pygithub", "#repo", "#api", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-09", "description": "This notebook list open pull requests from a repository name using pygithub library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_open_pull_requests.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_open_pull_requests.ipynb", "imports": ["os", "json", "github.Github", "naas"], "image_url": ""}, {"objectID": "91d4843ef8544aef83848c962ab6e38be11682c7ef728a1a9e2f10abd65cae9e", "tool": "GitHub", "notebook": "List organization repositories", "action": "", "tags": ["#github", "#pygithub", "#list", "#organization", "#repositories"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-05", "description": "This notebook will show how to list organization repositories using pygithub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_organization_repositories.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_organization_repositories.ipynb", "imports": ["naas", "github"], "image_url": ""}, {"objectID": "9402c5818d40c9a1056603298a6ece7b054a8313e93aa96e3a08670d775334b7", "tool": "GitHub", "notebook": "List pending team invitations", "action": "", "tags": ["#github", "#teams", "#invitations", "#rest", "#api", "#list", "#snippet"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-19", "created_at": "2023-04-18", "description": "This notebook will show how to list pending team invitations using the GitHub REST API and will create a DataFrame as output. It can be used by organizations with multiple teams on GitHub to keep track of pending team invitations, ensuring that all team members are added to the appropriate teams and can collaborate effectively. It helps in managing team membership and permissions for efficient collaboration within the organization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_pending_team_invitations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_pending_team_invitations.ipynb", "imports": ["requests", "naas", "pandas", "pprint.pprint"], "image_url": ""}, {"objectID": "2afff9452829305d478206c7df493312ed90cc027380628a2fa35705dc1246a0", "tool": "GitHub", "notebook": "List stargazers from repository", "action": "", "tags": ["#github", "#stars", "#stargazers", "#naas_drivers", "#operations", "#analytics", "#html", "#plotly", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook provides a way to retrieve the list of users who have starred a given GitHub repository and save it into a csv file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_stargazers_from_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_stargazers_from_repository.ipynb", "imports": ["naas_drivers.github", "naas"], "image_url": ""}, {"objectID": "cbb03445c11c8235ed502fd4031d9c94f68d15a70486cc4eae08329f546df285", "tool": "GitHub", "notebook": "List team members", "action": "", "tags": ["#github", "#teams", "#members", "#rest", "#api", "#list", "#snippet"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-19", "created_at": "2023-04-18", "description": "This notebook will demonstrate how to list team members using the GitHub REST API and will create a DataFrame as output. It can be used by organizations or repository owners to manage their teams on GitHub by listing the current team members. It helps in keeping track of team members, their roles, and permissions, enabling organizations to efficiently manage their teams and ensure that the right users have the appropriate access.\n\nDataFrame returned:\n- login': Represents the username or login name of the GitHub user.\n- 'id': Represents the unique identifier assigned to the GitHub user.\n- 'node_id': Represents the unique identifier for the GitHub user's profile as a node in the GitHub GraphQL API.\n- 'avatar_url': Represents the URL of the avatar (profile picture) of the GitHub user.\n- 'gravatar_id': Represents the unique identifier associated with the GitHub user's Gravatar profile.\n- 'url': Represents the URL of the GitHub user's profile.\n- 'html_url': Represents the HTML URL of the GitHub user's profile.\n- 'followers_url': Represents the URL for retrieving the list of followers of the GitHub user.\n- 'following_url': Represents the URL for retrieving the list of users that the GitHub user is following.\n- 'gists_url': Represents the URL for retrieving the list of gists created by the GitHub user.\n- 'starred_url': Represents the URL for retrieving the list of repositories starred by the GitHub user.\n- 'subscriptions_url': Represents the URL for retrieving the list of repositories subscribed to by the GitHub user.\n- 'organizations_url': Represents the URL for retrieving the list of organizations the GitHub user is a member of.\n- 'repos_url': Represents the URL for retrieving the list of repositories owned by the GitHub user.\n- 'events_url': Represents the URL for retrieving the list of events related to the GitHub user's activity.\n- 'received_events_url': Represents the URL for retrieving the list of events received by the GitHub user.\n- 'type': Represents the type of GitHub user, which can be 'User' or 'Organization'.\n- 'site_admin': Represents a boolean value indicating if the GitHub user has administrative privileges (true) or not (false) in the associated organization or repository.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_List_team_members.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_List_team_members.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "8591114911bf4f214706b00f87ba2c2ac8b8ac4af35a244bee65923f75841c03", "tool": "GitHub", "notebook": "Peform basic actions", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides instructions on how to use GitHub to perform basic tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Peform_basic_actions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Peform_basic_actions.ipynb", "imports": ["git_lib.Git"], "image_url": ""}, {"objectID": "cd80d6b09a931a9e136faa98ec7db9b739b3d2f198222dc8b96f947b56d9cadc", "tool": "GitHub", "notebook": "Read issue", "action": "", "tags": ["#github", "#productivity", "#code", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides instructions on how to read and understand issues on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Read_issue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Read_issue.ipynb", "imports": ["github.Github", "pandas"], "image_url": ""}, {"objectID": "1d105e6fd6ce6afd43b108739842b18b3af440c768cd23db3fa62d9ddf6521e3", "tool": "GitHub", "notebook": "Remove directories with branches closed on my local", "action": "", "tags": ["#github", "#branches", "#list", "#api", "#rest", "#python", "#active"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook facilitates the removal of directories associated with branches on your local machine. If you need to clone and create directories based on active branches, you can use either of the following notebooks: GitHub_Clone_open_branches_from_repository_on_my_local or GitHub_Clone_repository_and_switch_branch.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Remove_directories_with_branches_closed_on_my_local.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Remove_directories_with_branches_closed_on_my_local.ipynb", "imports": ["naas", "pandas", "requests", "shutil", "os", "datetime.datetime, timedelta"], "image_url": ""}, {"objectID": "332448e5948d4198f461223f9937a1ce1cd7912fa7df229fa71a2f3121d80949", "tool": "GitHub", "notebook": "Remove member from team", "action": "", "tags": ["#github", "#teams", "#snippet", "#operations"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-05-07", "description": "This notebook provides instructions on how to remove a member from a GitHub team.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Remove_member_from_team.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Remove_member_from_team.ipynb", "imports": ["requests", "naas_drivers.github"], "image_url": ""}, {"objectID": "fdcbabe75aaf3e5fb4fdd20389fa8f467d45d1bdb07f1bdd792b851b3747da63", "tool": "GitHub", "notebook": "Remove team membership for a user", "action": "", "tags": ["#github", "#teams", "#members", "#remove", "#api", "#rest"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-26", "created_at": "2023-04-19", "description": "This notebook explains how to remove team membership for a user. It is usefull for organizations that need to manage their team memberships.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Remove_team_membership_for_a_user.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Remove_team_membership_for_a_user.ipynb", "imports": ["requests", "json"], "image_url": ""}, {"objectID": "34d8e5474a94719c1703516d66d3e99cbaaada2b84c29f116ea81516710e5783", "tool": "GitHub", "notebook": "Reopen issue", "action": "", "tags": ["#github", "#issues", "#update", "#rest", "#api", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2023-05-26", "description": "This notebook explains how to reopened an issue on GitHub using the REST API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Reopen_issue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Reopen_issue.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "3d075044a53de36f530c33cdb1aec8ba83ab4108b44d2584062e37c5344cb45e", "tool": "GitHub", "notebook": "Send contributor activity on slack", "action": "", "tags": ["#github", "#activity", "#update", "#api", "#snippet", "#operations", "#slack"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-28", "created_at": "2023-06-16", "description": "This notebook demonstrates how to send GitHub activity of a contributor of awesome notebook templates to Slack. It includes the sections below:\n- \u2705 **Templates created:** the total number of templates created (overall, by month, by week).\n- \ud83d\udc40 **In review:** the number of PRs ready reviewed. Make sure you made a comment with **\"Ready to review\"** inside the PR.\n- \ud83c\udfd7 **In progress:** the current PRs you are working on.\n- \ud83d\udccb **Backlog:** the issues you are assigned to with no PRs opened.\n\n*NB: Execution time may takes between 2 to 5 min.*", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Send_contributor_activity_on_slack.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Send_contributor_activity_on_slack.ipynb", "imports": ["os", "json", "datetime.datetime", "github.Github", "naas", "pandas", "requests", "naas_drivers.slack", "warnings"], "image_url": ""}, {"objectID": "9c57f872a50f25acbb10c6400142ac1e874a1c4b7d26c38e6efc0c4b819bb16f", "tool": "GitHub", "notebook": "Send stargazers to Google Sheets", "action": "", "tags": ["#github", "#stars", "#stargazers", "#googlesheets", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-23", "description": "This notebook will show how to send GitHub stargazers from a given repository to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Send_stargazers_to_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Send_stargazers_to_Google_Sheets.ipynb", "imports": ["naas_drivers.github, gsheet", "naas"], "image_url": ""}, {"objectID": "c10a991b52bbeb12828cfcc922d3d1126bc807071ecf6038d593adbe94fbc6e8", "tool": "GitHub", "notebook": "Send template maintainer monthly report", "action": "", "tags": ["#github", "#issues", "#merged", "#rest", "#api", "#snippet", "#operations", "#email", "#awesomenotebooks", "#maintainer"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook retrieves data to ascertain the sponsorships provided by Naas for template maintainers and dispatches a notification on every 7th day of the month, as well as the last three days. It incorporates the monthly count of issue closed with estimates, and the number of Pull Requests reviewed within the month.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Send_template_maintainer_monthly_report.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Send_template_maintainer_monthly_report.ipynb", "imports": ["pandas", "github.Github", "datetime.datetime, timezone", "requests", "bs4.BeautifulSoup", "IPython.display.display, HTML", "numpy", "datetime.datetime", "naas", "naas_drivers.naasauth, emailbuilder", "warnings"], "image_url": ""}, {"objectID": "7b2207634faad3e18e2a4179115d4b835a53bed640a16cccc0c7e8d740a7970f", "tool": "GitHub", "notebook": "Send templates created on a notebooks to Slack channel", "action": "", "tags": ["#github", "#templates", "#created", "#rest", "#api", "#snippet", "#operations", "#slack"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-11", "created_at": "2023-07-11", "description": "This notebook demonstrates how to send the templates created on GitHub to a specific Slack channel. It includes the sections below:\n\n- \u2705 **Templates created:** the total number of templates created (overall, by month, by week).\n- \ud83d\udcca **Bar chart:** a barchart of the templates created the last 8 weeks\n\n*NB: Execution time may takes between 1 to 4 min.*", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Send_templates_created_on_a_notebooks_to_Slack_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Send_templates_created_on_a_notebooks_to_Slack_channel.ipynb", "imports": ["github.Github", "naas", "pandas", "naas_drivers.slack", "plotly.graph_objects", "datetime.datetime, timedelta, date", "warnings"], "image_url": ""}, {"objectID": "7afaaedd1fb202006ad3861d87fc8671e703e8ab3af059d97fd4c95fc4e61601", "tool": "GitHub", "notebook": "Track issues on projects", "action": "", "tags": ["#github", "#repos", "#issues", "#operations", "#analytics", "#csv", "#plotly"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-04-12", "description": "This notebook allows users to track and manage issues related to their projects on GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Track_issues_on_projects.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Track_issues_on_projects.ipynb", "imports": ["plotly.express", "naas_drivers.github"], "image_url": ""}, {"objectID": "e6462e6eaca51db7dbf96bbd6be22be706fa160145a35d73671984ccb506f093", "tool": "GitHub", "notebook": "Track notebooks created over time", "action": "", "tags": ["#github", "#repos", "#commits", "#notebooks", "#operations", "#analytics", "#html", "#plotly", "#csv", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows users to track changes to their notebooks over time using GitHub.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Track_notebooks_created_over_time.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Track_notebooks_created_over_time.ipynb", "imports": ["pandas", "requests", "os", "naas_drivers.github", "plotly.graph_objects", "pydash", "urllib.parse.urlencode", "datetime.datetime, timedelta", "naas"], "image_url": ""}, {"objectID": "e188766003d17aa7cd99e2ba165f5eee5b6fabb6336e759d7a1271f0f99dbefd", "tool": "GitHub", "notebook": "Update issue", "action": "", "tags": ["#github", "#issues", "#update", "#rest", "#api", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-26", "created_at": "2023-05-26", "description": "This notebook explains how to update an issue on GitHub using the REST API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/GitHub/GitHub_Update_issue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/GitHub/GitHub_Update_issue.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "fa79dae352658caaec4422cf9d3df4cb3f10675a6b3d3f8323ec98354f5504af", "tool": "Gmail", "notebook": "Automate response from keywords in mailbox", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Sanjay Sabu", "author_url": "https://www.linkedin.com/in/sanjay-sabu-4205/", "updated_at": "2023-05-18", "created_at": "2021-04-20", "description": "This notebook automates the process of responding to emails in Gmail based on keywords found in the mailbox.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Automate_response_from_keywords_in_mailbox.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Automate_response_from_keywords_in_mailbox.ipynb", "imports": ["naas", "naas_drivers.email", "re.search"], "image_url": ""}, {"objectID": "2b5e18eec609ef0127f4d6d9be1802a2283fec60a598d654b98535b6bcd321ce", "tool": "Gmail", "notebook": "Clean mailbox", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#automation", "#scheduler"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-12", "created_at": "2021-04-14", "description": "This notebook helps you quickly and easily organize your Gmail inbox by removing unwanted emails.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Clean_mailbox.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Clean_mailbox.ipynb", "imports": ["naas", "naas_drivers.email", "pandas", "numpy", "plotly.express"], "image_url": ""}, {"objectID": "78ce50f9ba2a77f6308dbeb62b15c57fd5db2e92ecb652d13658246a50ead748", "tool": "Gmail", "notebook": "Create GitHub issue on specific email", "action": "", "tags": ["#gmail", "#github", "#email", "#issue", "#create", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-18", "created_at": "2023-05-17", "description": "This notebook will show how to create a GitHub issue from a specific email using Gmail and Python. It is usefull for organizations that need to track emails and create issues from them.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Create_GitHub_issue_on_specific_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Create_GitHub_issue_on_specific_email.ipynb", "imports": ["naas", "naas_drivers.email", "re.search", "pandas", "requests"], "image_url": ""}, {"objectID": "4eeb57ee19493997c46d04f94059ef5c2bd3f809491461cfe8c8c065d7d75921", "tool": "Gmail", "notebook": "Create draft email", "action": "", "tags": ["#gmail", "#email", "#draft", "#create", "#python", "#library"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-05-19", "created_at": "2023-05-16", "description": "This notebook will show how to create a draft email using the Gmail API. It is usefull for organizations that need to automate the creation of emails.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Create_draft_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Create_draft_email.ipynb", "imports": ["naas", "googleapiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "google.auth.transport.requests.Request", "pickle", "datetime", "os.path", "base64", "email.mime.text.MIMEText", "email.mime.multipart.MIMEMultipart"], "image_url": ""}, {"objectID": "cf0d71ca4f2f41fa0272cbf9fbe3b1e890e7c4968b3a9f57478f8d65e40f60e8", "tool": "Gmail", "notebook": "Delete email from mailbox", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows you to update an email status in your Gmail inbox.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Delete_email_from_mailbox.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Delete_email_from_mailbox.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "c2c64b6f6dd2e5281a3730230214ff3d877fea2309eb0b74ddeae27e331cac8a", "tool": "Gmail", "notebook": "Get emails by date", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#automation", "#analytics", "#plotly"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-07", "created_at": "2023-07-07", "description": "This notebook provides an example of how to retrieve emails based on a specified date or filter them by 'before' or 'after' a given date. It demonstrates the process of fetching emails using date-based criteria for more targeted email retrieval.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_emails_by_date.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_emails_by_date.ipynb", "imports": ["naas", "naas_drivers.email", "pandas", "numpy", "plotly.express", "datetime.date"], "image_url": ""}, {"objectID": "9d0515a1c77f00567dfb9833c75af19c3c9b24efd7b7a6e0a6d53ef0de00fcd0", "tool": "Gmail", "notebook": "Get emails stats by sender", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#automation", "#analytics", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows users to get stats from their emailbox by sender.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_emails_stats_by_sender.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_emails_stats_by_sender.ipynb", "imports": ["naas", "naas_drivers.email", "pandas", "numpy", "plotly.express"], "image_url": ""}, {"objectID": "3cc6c378e11b85f9191dac73c7c0f5f5118c8f9f96af0926e9d688849b470db8", "tool": "Gmail", "notebook": "Get most common senders", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#automation", "#analytics", "#plotly"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-19", "created_at": "2023-07-19", "description": "This notebook analyses users' inbox, identifies a list of the most common senders depending on the emails for the set period of time, and outputs the list of most common senders.\nThis notebook aims to identify unwanted subscriptions or emails that Gmail didn't successfully filter as \"Spam.\"", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_most_common_senders.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_most_common_senders.ipynb", "imports": ["datetime", "os", "imapclient.IMAPClient", "naas", "collections.Counter", "quopri", "email.header"], "image_url": ""}, {"objectID": "714810e2c13b0614a2e4dcca2ea5dade6fb7472a230e20e2bada4b75a1882fee", "tool": "Gmail", "notebook": "Get most important unseen emails", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#automation", "#analytics", "#plotly"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-19", "created_at": "2023-07-19", "description": "This notebook retrieves all emails for a set period of time and calculates the user's reply rate to each sender. By identifying the important senders with a higher reply rate, the code helps prioritize the user's responses and ensures timely communication. The code then outputs the list of unseen emails from these important senders, providing a focused view of the most relevant and pending email conversations.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_most_important_unseen_emails.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_most_important_unseen_emails.ipynb", "imports": ["datetime", "os", "imapclient.IMAPClient", "imapclient.IMAPClient", "naas", "collections.Counter", "quopri", "email.header"], "image_url": ""}, {"objectID": "e8855875aba10e1d9817664191d5f2ae82c89b8addef409700da4edb5c174f1c", "tool": "Gmail", "notebook": "Get seen emails", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows you to read your Gmail inbox and get the seen emails. It returns a dataframe as follow:\n- uid: This column represents the unique identifier associated with each row or email in the dataframe.\n- subject: The subject column contains the subject line or title of the email.\n- from: The \"from\" column contains information about the sender of the email. It includes the email address and name of the sender.\n- to: The \"to\" column contains information about the primary recipients of the email. It includes the email addresses and names of the recipients.\n- cc: The \"cc\" column represents the carbon copy recipients of the email. It contains a list of email addresses and names of the cc'd recipients.\n- bcc: The \"bcc\" column contains the blind carbon copy recipients of the email. Similar to the \"cc\" column, it includes a list of email addresses and names.\n- reply_to: This column contains the email addresses and names that should be used when replying to the email.\n- date: The \"date\" column indicates the date and time when the email was sent.\n- text: The \"text\" column contains the plain text content of the email.\n- html: The \"html\" column includes the HTML-formatted content of the email.\n- flags: The \"flags\" column represents any flags or indicators associated with the email, such as important, starred, etc.\n- headers: This column contains additional headers of the email, such as the \"delivered-to,\" \"received,\" and \"X-Google-Smtp-Source\" headers.\n- size_rfc822: The \"size_rfc822\" column indicates the size of the email in RFC822 format.\n- size: The \"size\" column represents the size of the email in bytes.\n- obj: The \"obj\" column contains the object representation of the email.\n- attachments: This column includes any attachments associated with the email, such as files, images, etc.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_seen_emails.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_seen_emails.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "c05ec3727f7f634fa76664cc32f3de7e7cae8ef27a4b8abf2f2eb444406359dc", "tool": "Gmail", "notebook": "Get unseen emails", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows you to read your Gmail inbox and get the unseen emails. It returns a dataframe as follow:\n- uid: This column represents the unique identifier associated with each row or email in the dataframe.\n- subject: The subject column contains the subject line or title of the email.\n- from: The \"from\" column contains information about the sender of the email. It includes the email address and name of the sender.\n- to: The \"to\" column contains information about the primary recipients of the email. It includes the email addresses and names of the recipients.\n- cc: The \"cc\" column represents the carbon copy recipients of the email. It contains a list of email addresses and names of the cc'd recipients.\n- bcc: The \"bcc\" column contains the blind carbon copy recipients of the email. Similar to the \"cc\" column, it includes a list of email addresses and names.\n- reply_to: This column contains the email addresses and names that should be used when replying to the email.\n- date: The \"date\" column indicates the date and time when the email was sent.\n- text: The \"text\" column contains the plain text content of the email.\n- html: The \"html\" column includes the HTML-formatted content of the email.\n- flags: The \"flags\" column represents any flags or indicators associated with the email, such as important, starred, etc.\n- headers: This column contains additional headers of the email, such as the \"delivered-to,\" \"received,\" and \"X-Google-Smtp-Source\" headers.\n- size_rfc822: The \"size_rfc822\" column indicates the size of the email in RFC822 format.\n- size: The \"size\" column represents the size of the email in bytes.\n- obj: The \"obj\" column contains the object representation of the email.\n- attachments: This column includes any attachments associated with the email, such as files, images, etc.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Get_unseen_emails.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Get_unseen_emails.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "a2209f3b3f09d821c3270ef170323d3ab2583d4a1c9eb628e3862e887382d6c0", "tool": "Gmail", "notebook": "Mark emails as seen by dates", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook goes through the emails within the date range set by the user and marks them all as seen.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Mark_emails_as_seen_by_dates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Mark_emails_as_seen_by_dates.ipynb", "imports": ["naas", "imaplib", "email", "datetime.date", "imapclient.IMAPClient", "imapclient.IMAPClient"], "image_url": ""}, {"objectID": "271cd524edb23b21e977fab95d1defea1649ae0caa2dc08f666f1c6e25d6b020", "tool": "Gmail", "notebook": "Read mailbox", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu", "updated_at": "2023-05-12", "created_at": "2021-04-15", "description": "This notebook allows you to read your Gmail inbox and returns a dataframe:\n- uid: This column represents the unique identifier associated with each row or email in the dataframe.\n- subject: The subject column contains the subject line or title of the email.\n- from: The \"from\" column contains information about the sender of the email. It includes the email address and name of the sender.\n- to: The \"to\" column contains information about the primary recipients of the email. It includes the email addresses and names of the recipients.\n- cc: The \"cc\" column represents the carbon copy recipients of the email. It contains a list of email addresses and names of the cc'd recipients.\n- bcc: The \"bcc\" column contains the blind carbon copy recipients of the email. Similar to the \"cc\" column, it includes a list of email addresses and names.\n- reply_to: This column contains the email addresses and names that should be used when replying to the email.\n- date: The \"date\" column indicates the date and time when the email was sent.\n- text: The \"text\" column contains the plain text content of the email.\n- html: The \"html\" column includes the HTML-formatted content of the email.\n- flags: The \"flags\" column represents any flags or indicators associated with the email, such as important, starred, etc. Possible value for flag: 'SEEN', 'ANSWERED', 'FLAGGED', 'DELETED', 'DRAFT', 'RECENT'\n- headers: This column contains additional headers of the email, such as the \"delivered-to,\" \"received,\" and \"X-Google-Smtp-Source\" headers.\n- size_rfc822: The \"size_rfc822\" column indicates the size of the email in RFC822 format.\n- size: The \"size\" column represents the size of the email in bytes.\n- obj: The \"obj\" column contains the object representation of the email.\n- attachments: This column includes any attachments associated with the email, such as files, images, etc.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Read_mailbox.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Read_mailbox.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "8f12ba6e2beed9a59f7b18f42a101ad2d7336041f95eb7e5bd50bb09f6052184", "tool": "Gmail", "notebook": "Send email", "action": "", "tags": ["#gmail", "#email", "#send", "#python", "#library", "#smtplib"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook will show how to send an email using naas_drivers. It is usefull for organizations that need to send emails from their Gmail account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Send_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Send_email.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "d292b17e6643b9537f5b4f295149979d2c5b081a8e0ab0f0d3ab78bb5c1bfddd", "tool": "Gmail", "notebook": "Update email flag", "action": "", "tags": ["#gmail", "#productivity", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows you to update an email flag in your Gmail inbox.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Gmail/Gmail_Update_email_flag.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Gmail/Gmail_Update_email_flag.ipynb", "imports": ["naas", "naas_drivers.email"], "image_url": ""}, {"objectID": "104108f1cfc4292347929774d2c5e72f8691076a4e1576cd5d3e52a752c9520c", "tool": "Google Analytics", "notebook": "Follow average session duration daily", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-04-22", "description": "This notebook provides a daily overview of the average session duration for a website tracked with Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_average_session_duration_daily.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_average_session_duration_daily.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "9c612681622da896898b8d2e1234a00856e1515c326db064afae2d84fa7eb702", "tool": "Google Analytics", "notebook": "Follow number of new visitors daily", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-04-22", "description": "This notebook tracks the daily number of new visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_daily.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_daily.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "3fe7b4b211e6b581b521cf3dc9a9ed7c4a9a81e4c89f957444b5d04ec985ca33", "tool": "Google Analytics", "notebook": "Follow number of new visitors hourly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the hourly number of new visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_hourly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_hourly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "b8a4989937c8ebbec020312fc8d1e7bd427af1ca3f45a9afb9b5c83c55abc1c3", "tool": "Google Analytics", "notebook": "Follow number of new visitors monthly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the monthly number of new visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_monthly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "5b7788ab05dab3b644afdcb2d321dbf68370269934b6d4d53e02331b0d6b8bd1", "tool": "Google Analytics", "notebook": "Follow number of new visitors weekly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the weekly number of new visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_new_visitors_weekly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "c936eb78a90ad7c2a2baf26fe6ccd941e1ae7d29b5853b89fbbd4d0bb3235ee0", "tool": "Google Analytics", "notebook": "Follow number of sessions daily", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-04-22", "description": "This notebook provides a daily overview of the number of sessions tracked by Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_daily.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_daily.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "32df9d633cd4afefc4274cc22048edf92136f7e26c238ec4aa6d593868d90017", "tool": "Google Analytics", "notebook": "Follow number of sessions hourly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the number of sessions on Google Analytics over the course of an hour.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_hourly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_hourly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "3bdd912e77792584482b7d2b4f975959046378c261b29f97a4b2b65255b1475c", "tool": "Google Analytics", "notebook": "Follow number of sessions monthly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the monthly number of sessions on Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_monthly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "da843f31021b75f4fec31cc2deb7f06f955056d68c2045cf540597f6dd769591", "tool": "Google Analytics", "notebook": "Follow number of sessions weekly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the number of sessions on Google Analytics on a weekly basis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_sessions_weekly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "47b2f1e75d1576ff8090e484fd541f2fe88c07fd94a3ff71e1ab30bb29a426eb", "tool": "Google Analytics", "notebook": "Follow number of visitors daily", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-04-22", "description": "This notebook tracks the daily number of visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_daily.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_daily.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "56bd24cb31d186f8cef0bddcfae15554b4f2212fabaf28ef9f232c37acaf5d9f", "tool": "Google Analytics", "notebook": "Follow number of visitors hourly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the hourly number of visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_hourly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_hourly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "99e8d32201a65a79018137233c5e2b545ad46814a6de7617ea91a2c53cf918ff", "tool": "Google Analytics", "notebook": "Follow number of visitors monthly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the monthly number of visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_monthly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "05f3277c0413c03585c01a7b0f7a97cff58554756a85a014fa6ecd61fe5f0d6e", "tool": "Google Analytics", "notebook": "Follow number of visitors weekly", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#csv", "#html", "#plotly", "#image", "#png"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-31", "description": "This notebook tracks the weekly number of visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Follow_number_of_visitors_weekly.ipynb", "imports": ["plotly.graph_objects", "naas", "datetime", "pandas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "9efbf241b3610e5a74d4d6c0a06e1364d12516ab32d4dd06960d4af38f317dbb", "tool": "Google Analytics", "notebook": "Get bounce rate", "action": "", "tags": ["#googleanalytics", "#bouncerate", "#plotly", "#linechart", "#naas_drivers", "#scheduler", "#asset", "#naas", "#marketing", "#analytics", "#automation", "#image", "#csv", "#html"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides an analysis of the bounce rate of a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_bounce_rate.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_bounce_rate.ipynb", "imports": ["pandas", "plotly.graph_objects", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "fd0747c320e63718180faefdcd4021fd259514b20ba255a20a00aae4fc81a00c", "tool": "Google Analytics", "notebook": "Get pageview ranking", "action": "", "tags": ["#googleanalytics", "#pageviews", "#plotly", "#horizontalbarchart", "#naas_drivers", "#scheduler", "#asset", "#naas", "#marketing", "#analytics", "#automation", "#image", "#csv", "#html"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides a ranking of pageviews for a website using Google Analytics data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_pageview_ranking.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_pageview_ranking.ipynb", "imports": ["pandas", "plotly.graph_objects", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "eb4c394db4b8712ba495abae2c5eef6becfd0cfc413bf2463e82ab76f8c9b973", "tool": "Google Analytics", "notebook": "Get stats per country", "action": "", "tags": ["#googleanalytics", "#statspercountry", "#marketing", "#analytics", "#automation", "#image", "#csv", "#html", "#plotly"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides a comprehensive analysis of website traffic by country using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_stats_per_country.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_stats_per_country.ipynb", "imports": ["pycountry", "pycountry", "plotly.graph_objects", "plotly.express", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "b432939ab2679ed5875c113d75531e92776d116566343b19908714fa461a20c5", "tool": "Google Analytics", "notebook": "Get time on landing page", "action": "", "tags": ["#googleanalytics", "#timeonlanding", "#marketing", "#analytics", "#automation", "#image", "#csv", "#html", "#plotly"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides an analysis of the amount of time visitors spend on a landing page using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_time_on_landing_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_time_on_landing_page.ipynb", "imports": ["datetime.timedelta", "pandas", "plotly.graph_objects", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "d07d75e8dd6ee9ce1a85c6a5909028184fd0a04a3030164ac5c6430a5f7e7b56", "tool": "Google Analytics", "notebook": "Get unique visitors", "action": "", "tags": ["#googleanalytics", "#getuniquevisitors", "#plotly", "#barchart", "#naas_drivers", "#scheduler", "#asset", "#naas", "#marketing", "#analytics", "#automation", "#image", "#csv", "#html"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides an analysis of unique visitors to a website using Google Analytics.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_unique_visitors.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_unique_visitors.ipynb", "imports": ["pandas", "plotly.graph_objects", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "afb36fe72b75ccd000b3c821eabec5037797e3ea1064bce8e088ba44b82ed1d8", "tool": "Google Analytics", "notebook": "Get unique visitors by country", "action": "", "tags": ["#googleanalytics", "#statspercountry", "#analytics", "#marketing", "#dataframe"], "author": "Charles Demontigny", "author_url": "https://www.linkedin.com/in/charles-demontigny/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook provides a breakdown of unique visitors to a website by country using Google Analytics data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Get_unique_visitors_by_country.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Get_unique_visitors_by_country.ipynb", "imports": ["plotly.graph_objects", "plotly.express", "naas", "naas_drivers.googleanalytics"], "image_url": ""}, {"objectID": "bf81d9bdc059f8647005c3dc6132525ff6c4e7be3881311851324030a9be3eb2", "tool": "Google Analytics", "notebook": "Send visitors traffic graph and trends prediction to Slack channel", "action": "", "tags": ["#googleanalytics", "#analytics", "#marketing", "#dataframe"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maxime-jublou", "updated_at": "2023-04-12", "created_at": "2022-05-16", "description": "This notebook allows users to send Google Analytics visitor traffic graphs and trends predictions to a Slack channel.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Analytics/Google_Analytics_Send_visitors_traffic_graph_and_trends_prediction_to_Slack_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Analytics/Google_Analytics_Send_visitors_traffic_graph_and_trends_prediction_to_Slack_channel.ipynb", "imports": ["naas", "naas_drivers.googleanalytics", "naas_drivers.prediction", "naas_drivers.plotly", "naas_drivers.slack", "plotly.graph_objects", "pandas", "datetime.datetime", "json"], "image_url": ""}, {"objectID": "f28cb2cc683e6496c50f1a68829a0c527ee8e5af9091132ec5c0b87769aba753", "tool": "Google Calendar", "notebook": "Get calendar", "action": "", "tags": ["#googlecalendar", "#calendar", "#get", "#api", "#reference", "#v3"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will demonstrate how to use the Google Calendar API to get metadata for a calendar.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Calendar/Google_Calendar_Get_calendar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Calendar/Google_Calendar_Get_calendar.ipynb", "imports": ["pprint.pprint", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow"], "image_url": ""}, {"objectID": "7513483959a8c033cb93018a8f4a9eb29cbfbfcbef8eacd5d2f2b9f5dd48ef1c", "tool": "Google Calendar", "notebook": "List calendars", "action": "", "tags": ["#googlecalendar", "#calendarlist", "#list", "#api", "#python", "#reference"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will demonstrate how to use the Google Calendar API to list the calendars on the user's calendar list.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Calendar/Google_Calendar_List_calendars.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Calendar/Google_Calendar_List_calendars.ipynb", "imports": ["pprint.pprint", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow"], "image_url": ""}, {"objectID": "a2db899b2d3b4a8407d9734bb11c66eb169b4a0a55b53fe65902049471de9fc7", "tool": "Google Calendar", "notebook": "List events from calendar", "action": "", "tags": ["#googlecalendar", "#calendar", "#events", "#list", "#api", "#python"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will demonstrate how to use the Google Calendar API to list events from a calendar.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Calendar/Google_Calendar_List_events_from_calendar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Calendar/Google_Calendar_List_events_from_calendar.ipynb", "imports": ["pprint.pprint", "datetime.datetime", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow"], "image_url": ""}, {"objectID": "4d62505c0b27fe497af44172fffb4bd8ca5ed2bcfcd1945d9434f00347ac442d", "tool": "Google Drive", "notebook": "Download file", "action": "", "tags": ["#googledrive", "#snippet", "#operations", "#naas"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows users to download files from their Google Drive account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Drive/Google_Drive_Download_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Drive/Google_Drive_Download_file.ipynb", "imports": ["gdown", "gdown"], "image_url": ""}, {"objectID": "7e5630a4f5744470a9195a186592bb24d9e9900acefba7d9a6ea179bedf905c7", "tool": "Google Maps", "notebook": "Calculate travel costs between two addresses", "action": "", "tags": ["#googlemaps", "#productivity", "#operations", "#automation", "#jupyternotebooks"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-26", "created_at": "2023-07-25", "description": "This notebook calculates the travel costs between two addresses using Google Maps API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Maps/Google_Maps_Calculate_travel_costs_between_two_addresses.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Maps/Google_Maps_Calculate_travel_costs_between_two_addresses.ipynb", "imports": ["os", "requests", "naas"], "image_url": ""}, {"objectID": "54859e1650428404cec4471aa488e37169ff7612eafb140d2ec610458085d181", "tool": "Google Maps", "notebook": "Connect to Routes API", "action": "", "tags": ["#googlemaps", "#productivity", "#operations", "#automation", "#jupyternotebooks"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook is designed to perform several functions. Firstly, it acquires the necessary credentials that are required for API access. Then, it proceeds to configure the API endpoint URL. After setting up the URL, it establishes a secure connection between the client and the API. Finally, it validates the user's identity and permissions for interactions with the API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Maps/Google_Maps_Connect_to_Routes_API.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Maps/Google_Maps_Connect_to_Routes_API.ipynb", "imports": ["os", "requests", "naas"], "image_url": ""}, {"objectID": "d41f3d68b8aab7d650b71042b444c5e5ebb1d8b4d3ca1487383f3c3aab62dc85", "tool": "Google Maps", "notebook": "Create and display distance matrix", "action": "", "tags": ["#googlemaps", "#productivity", "#operations", "#automation", "#jupyternotebooks"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-08-08", "created_at": "2023-08-08", "description": "This notebook shows how to use the Google Maps Distance Matrix API to determine distances and trip durations between a number of different origins and destinations, giving accurate and efficient geospatial data. Furthermore, it provides a visual representation of the created matrix.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Maps/Google_Maps_Create_and_display_distance_matrix.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Maps/Google_Maps_Create_and_display_distance_matrix.ipynb", "imports": ["os", "requests", "naas", "folium", "googlemaps", "polyline", "geopy.geocoders.Nominatim"], "image_url": ""}, {"objectID": "cad8fb307d05f4ec0dcf9a7567bc7e5c2fc50a8ec0f9537ac26299130df2987a", "tool": "Google Maps", "notebook": "Create itinerary optimisation on differents waypoints", "action": "", "tags": ["#googlemaps", "#optimization", "#data", "#naas_drivers", "#operations", "#snippet", "#dataframe", "#google_maps_api", "#directions_api"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-08-08", "created_at": "2023-08-08", "description": "This template analyses a given set of waypoints, optimizes the order of visiting them, and outputs a list with the correct order. Thus, making it useful for travelers, who want to visit multiple locations most efficiently.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Maps/Google_Maps_Create_itinerary_optimisation_on_differents_waypoints.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Maps/Google_Maps_Create_itinerary_optimisation_on_differents_waypoints.ipynb", "imports": ["naas", "folium", "polyline", "polyline", "geopy.geocoders.Nominatim", "itertools.permutations", "googlemaps", "googlemaps"], "image_url": ""}, {"objectID": "863199793a97917978b0681eac7e59c3615a9e454525435b9a1eb6845f701d40", "tool": "Google Maps", "notebook": "Get coordinates from address", "action": "", "tags": ["#googlemaps", "#productivity", "#operations", "#automation", "#jupyternotebooks"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-26", "created_at": "2023-07-25", "description": "This notebook get coordinates from a given address using Google Maps API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Maps/Google_Maps_Get_coordinates_from_address.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Maps/Google_Maps_Get_coordinates_from_address.ipynb", "imports": ["os", "requests", "naas"], "image_url": ""}, {"objectID": "4524ee41a55c75df72f6dc0d75ada96d8305d81e20b3626f7a785d6be7431b9d", "tool": "Google Search", "notebook": "Get LinkedIn company url from name", "action": "", "tags": ["#googlesearch", "#snippet", "#operations", "#url"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "This notebook provides a method to quickly obtain the LinkedIn URL of a company from its name using Google Search.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Search/Google_Search_Get_LinkedIn_company_url_from_name.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Search/Google_Search_Get_LinkedIn_company_url_from_name.ipynb", "imports": ["googlesearch.search", "googlesearch.search", "re"], "image_url": ""}, {"objectID": "d1c949fe9e214226b7df5584548da212d42692f254b3325a5b9a03b14993b5be", "tool": "Google Search", "notebook": "Get LinkedIn profile url from name", "action": "", "tags": ["#googlesearch", "#snippet", "#operations", "#url"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "This notebook provides a method to quickly and easily obtain a LinkedIn profile URL from a given name using Google Search.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Search/Google_Search_Get_LinkedIn_profile_url_from_name.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Search/Google_Search_Get_LinkedIn_profile_url_from_name.ipynb", "imports": ["googlesearch.search", "googlesearch.search", "re"], "image_url": ""}, {"objectID": "2064667ee2f72eea060b675451e0aa7ce39cae50c52fce3ddd817440bfba9e21", "tool": "Google Search", "notebook": "Perform search", "action": "", "tags": ["#googlesearch", "#snippet", "#operations", "#url"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows users to perform Google searches quickly and easily.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Search/Google_Search_Perform_search.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Search/Google_Search_Perform_search.ipynb", "imports": ["googlesearch.search", "googlesearch.search"], "image_url": ""}, {"objectID": "a3806d0e8beb6df74a694e543ef83a8bf1058b7cc2dd05636cdeb22dde4ed654", "tool": "Google Sheets", "notebook": "Add items to Notion databases from new rows in", "action": "", "tags": ["#googlesheets", "#productivity", "#operations", "#automation", "#notion"], "author": "Pooja Srivastava", "author_url": "https://www.linkedin.com/in/pooja-srivastava-bb037649/", "updated_at": "2023-04-12", "created_at": "2022-03-29", "description": "This notebook does the following tasks: \n- Schedule the notebook to run every 15 minutes\n- Connect with Gsheet and get all rows using the gsheet driver's get method\n- Connect with NotionDB and get all pages using the Notion Databases driver's get method\n- Compare the list of pages from notion db with the rows returned from gsheet and add non matching rows to a list\n- Create new pages in Notion db for each row in the non matching list using the Notion Pages driver's create method\n- For each created page, add the properties and values from gsheet and update in notion using the Notion Pages driver's update methods", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Add_items_to_Notion_databases_from_new_rows_in_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Add_items_to_Notion_databases_from_new_rows_in_Google_Sheets.ipynb", "imports": ["pandas", "naas", "naas_drivers.notion, gsheet"], "image_url": ""}, {"objectID": "17edc5fdc7b63b3e6d04eb4faf8645977e854302a90026ec9fd88d666632fc59", "tool": "Google Sheets", "notebook": "Add new github member to team from spreadsheet", "action": "", "tags": ["#github", "#teams", "#automation", "#googlesheets", "#operations"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-05-20", "description": "This notebook demonstrates how to use Google Sheets to add a new GitHub member to a team from a spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Add_new_github_member_to_team_from_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Add_new_github_member_to_team_from_spreadsheet.ipynb", "imports": ["requests", "naas_drivers.github, gsheet", "naas", "pandas"], "image_url": ""}, {"objectID": "b04ee5b4b37c8b2317bef0807a60465579484e42bc08e2d5ccc93e264b98f84d", "tool": "Google Sheets", "notebook": "Calculate distance and price", "action": "", "tags": ["#googlesheets", "#gsheet", "#data", "#naas_drivers", "#operations", "#snippet", "#dataframe", "#google_maps_api", "#routes_api"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This template determines the cost and distance between location extracted from a Google Sheet. It uses the Routes API to estimate the price depending on the distance between sites and outputs the updated Google Sheet with distances and prices.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Calculate_Distance_and_Price.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Calculate_Distance_and_Price.ipynb", "imports": ["naas", "naas_drivers.gsheet", "requests"], "image_url": ""}, {"objectID": "ba4899765b01f9b5812cccd925895c501d58721780bc932b6fc4ff040e190f30", "tool": "Google Sheets", "notebook": "Get data", "action": "", "tags": ["#googlesheets", "#gsheet", "#data", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook demonstrates how to get data from a Google Sheets spreadsheet and return a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Get_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Get_data.ipynb", "imports": ["naas_drivers.gsheet"], "image_url": ""}, {"objectID": "05789b41ffcc541325fae77c8579bb900c997f4f995f9e1d4c65a690d6016683", "tool": "Google Sheets", "notebook": "Send LinkedIn invitations from spreadsheet", "action": "", "tags": ["#googlesheets", "#invitation", "#automation", "#content", "#notification", "#email", "#linkedin"], "author": "Valentin Goulet", "author_url": "https://www.linkedin.com/in/valentin-goulet-3a3070152/", "updated_at": "2023-04-12", "created_at": "2022-04-07", "description": "This notebook allows users to quickly and easily send LinkedIn invitations to contacts stored in a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Send_LinkedIn_invitations_from_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Send_LinkedIn_invitations_from_spreadsheet.ipynb", "imports": ["naas", "naas_drivers.linkedin, gsheet"], "image_url": ""}, {"objectID": "cf32ecf61a1d6fdcae3273e7e70026564087776ace44ace0a939c08a2085586f", "tool": "Google Sheets", "notebook": "Send data", "action": "", "tags": ["#googlesheets", "#gsheet", "#data", "#naas_drivers", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook allows to send data to Google Sheets to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Send_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Send_data.ipynb", "imports": ["naas_drivers.gsheet", "pandas"], "image_url": ""}, {"objectID": "209d34f8faf5b05652f9cb4b3fe1045566401b2257c9e18947473dbb1785b092", "tool": "Google Sheets", "notebook": "Send data to MongoDB", "action": "", "tags": ["#googlesheets", "#mongodb", "#nosql", "#operations", "#automation"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-04-12", "created_at": "2022-03-21", "description": "This notebook will help you send data from your spreadsheet to your MongoDB database collection", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Send_data_to_MongoDB.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Send_data_to_MongoDB.ipynb", "imports": ["naas_drivers.mongo, gsheet", "pandas", "naas"], "image_url": ""}, {"objectID": "1dc4e7406a9def845c9736a3dba795b33642a578d2f4c4b1fca74ca2c075892b", "tool": "Google Sheets", "notebook": "Send emails from sheet", "action": "", "tags": ["#googlesheets", "#gsheet", "#data", "#naas_drivers", "#operations", "#snippet", "#email"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook allows users to send emails directly from a Google Sheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Sheets/Google_Sheets_Send_emails_from_sheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Sheets/Google_Sheets_Send_emails_from_sheet.ipynb", "imports": ["naas_drivers.gsheet", "naas_drivers.email"], "image_url": ""}, {"objectID": "ce8167442d31886b2f8cd299da0d39fd5c26e646f8a734d91fc21a0d3372f5ff", "tool": "Google Slides", "notebook": "Create a Slide", "action": "", "tags": ["#googleslides", "#slides", "#create", "#api", "#developers", "#guides"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-20", "description": "This notebook describes how to insert a blank slide to an existing Google Slides presentation establishing a seamless connection using OAuth consent.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Slides/Google_Slides_Create_a_Slide.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Slides/Google_Slides_Create_a_Slide.ipynb", "imports": ["apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "uuid"], "image_url": ""}, {"objectID": "c18cd5159f738d52c6c4c7b6c95f1cf6bbc69b830505f91e9e82c9d2b99382ee", "tool": "Google Slides", "notebook": "Create a blank presentation", "action": "", "tags": ["#google", "#slides", "#presentation", "#create", "#blank", "#api"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-20", "description": "This notebook creates a blank presentation with a specified title using Google Slides API while connecting with oauth consent.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Slides/Google_Slides_Create_a_blank_presentation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Slides/Google_Slides_Create_a_blank_presentation.ipynb", "imports": ["apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow"], "image_url": ""}, {"objectID": "a397cec39c6fdad00f731f42c05d051037f4b2f52822c0818359408002f7c450", "tool": "Google Slides", "notebook": "Duplicate slide", "action": "", "tags": ["#googleslides", "#slides", "#duplicate", "#copy", "#presentation", "#slideshow"], "author": "Florent Ravenel", "author_url": "https://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-24", "description": "This notebook explains how to duplicate a slide in Google Slides establishing a seamless connection using OAuth consent. It is usefull for organizations that need to quickly create a presentation with similar slides.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Slides/Google_Slides_Duplicate_slide.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Slides/Google_Slides_Duplicate_slide.ipynb", "imports": ["apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "uuid"], "image_url": ""}, {"objectID": "4310bd0e9d59bba6ee8d36901c9519799e4753bb99624ef7f21272d14bc967ac", "tool": "Google Slides", "notebook": "List slides in presentation", "action": "", "tags": ["#googleslides", "#presentation", "#list", "#slides", "#python", "#api"], "author": "Florent Ravenel", "author_url": "https://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-24", "description": "This notebook will list all the slides in a Google Slides presentation and is usefull for organizations that need to quickly access the content of a presentation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Slides/Google_Slides_List_slides_in_presentation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Slides/Google_Slides_List_slides_in_presentation.ipynb", "imports": ["apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow"], "image_url": ""}, {"objectID": "5ee4be70aada8b886738cac583ed13df2be5a8597fa7dc4f811f5a8a12861f36", "tool": "Google Slides", "notebook": "Replace text within a shape", "action": "", "tags": ["#googleslides", "#text", "#shape", "#replace", "#api", "#slides"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-25", "created_at": "2023-04-21", "description": "This notebook explains how to use the Slides API to modify the text content of a shape establishing a seamless connection using OAuth consent.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Google%20Slides/Google_Slides_Replace_text_within_a_shape.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Google%20Slides/Google_Slides_Replace_text_within_a_shape.ipynb", "imports": ["apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "googleapiclient.errors.HttpError", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "googleapiclient.errors.HttpError"], "image_url": ""}, {"objectID": "fcfade8d33f639cee874b1956980bbf1c446054e191bec6e66d7ba12f1e1621d", "tool": "HTML", "notebook": "Create a website", "action": "", "tags": ["#html", "#css", "#website", "#page", "#landing", "#custom", "#snippet", "#marketing"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-10-03", "description": "The objective of this notebook is to create an end-to-end website in 5min.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HTML/HTML_Create_a_website.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HTML/HTML_Create_a_website.ipynb", "imports": ["urllib.request.urlopen", "IPython.display.IFrame", "naas"], "image_url": ""}, {"objectID": "dbd059d8bc4a12b38bd1d41128de9f4b6610c0048c178f8d96b57bb1d852f5b0", "tool": "Harvest", "notebook": "Get Filtered List of Time Entries", "action": "", "tags": ["#harvest", "#timeentries", "#api", "#list", "#python", "#get", "#filter"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-01", "created_at": "2023-08-01", "description": "This notebook will create a filtered list of time entries from the Harvest API v2. It is usefull for organizations to quickly access and display time entries based on a specific filter, such as by time period or project.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Harvest/Harvest_Filtered_time_entries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Harvest/Harvest_Filtered_time_entries.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "8a1dc783cc49a4f89c466a896cc8ec97d86bf1efd9a5f1b945cf97a3d73c3e27", "tool": "Harvest", "notebook": "List all clients", "action": "", "tags": ["#harvest", "#clients", "#api", "#list", "#python", "#get"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-16", "created_at": "2023-06-13", "description": "This notebook will list all clients from Harvest API and is usefull for organizations to get a list of their clients.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Harvest/Harvest_List_all_clients.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Harvest/Harvest_List_all_clients.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "084fd7fb8f4258a75ef4d470a395f3f4012a8b6663332d19546b8940ade827f4", "tool": "Harvest", "notebook": "List all time entries", "action": "", "tags": ["#harvest", "#timeentries", "#api", "#list", "#python", "#v2"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-13", "created_at": "2023-06-13", "description": "This notebook will list all time entries from the Harvest API v2. It is usefull for organizations to quickly access and display time entries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Harvest/Harvest_List_all_time_entries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Harvest/Harvest_List_all_time_entries.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "a4f6376cc053d445a9a1d10372766aeefa9588c710352decfd1af2a049a09310", "tool": "Harvest", "notebook": "List all users", "action": "", "tags": ["#harvest", "#users", "#api", "#list", "#python", "#get"], "author": "Landry Christensen", "author_url": "https://github.com/lchristensen6", "updated_at": "2023-08-03", "created_at": "2023-08-03", "description": "This notebook will list all users from the Harvest API v2. This is helpful as it allows organizations to quickly display all of their users on Harvest.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Harvest/Harvest_List_all_users.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Harvest/Harvest_List_all_users.ipynb", "imports": ["requests", "pandas", "naas"], "image_url": ""}, {"objectID": "7b4313cc79bea4a013f6abcc10f65b57072015ef0036a00f2ec9eb5002243581", "tool": "Healthchecks", "notebook": "Perfom basic actions", "action": "", "tags": ["#healthchecks", "#snippet", "#operations"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "This notebook provides a set of basic actions to help monitor and maintain the health of a system.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Healthchecks/Healthchecks_Perfom_basic_actions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Healthchecks/Healthchecks_Perfom_basic_actions.ipynb", "imports": ["naas_drivers.healthcheck"], "image_url": ""}, {"objectID": "995754444ddb900c81983085697f28649f333866641490313e567b1e0a3c9396", "tool": "HubSpot", "notebook": "Add LinkedIn message to contact", "action": "", "tags": ["#hubspot", "#communications", "#linkedin", "#snippet", "#contact", "#association"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook demonstrates how to add a LinkedIn message to a given contact in HubSpot. It uses the communication endpoint in HubSpot. It could be useful to create integration directly from your LinkedIn messages.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Add_LinkedIn_message_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Add_LinkedIn_message_to_contact.ipynb", "imports": ["requests", "naas", "datetime.datetime, date, timezone", "pprint.pprint"], "image_url": ""}, {"objectID": "84696ceb69fada2dae72389c3da1f4cb0d8ed06cce7d33bf3f1e5772859e4c04", "tool": "HubSpot", "notebook": "Add SMS message to contact", "action": "", "tags": ["#hubspot", "#communications", "#SMS", "#snippet", "#contact", "#association"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook demonstrates how to add SMS message to a given contact in HubSpot. It uses the communication endpoint in HubSpot. It could be useful to integrate with tools like Twilio.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Add_SMS_message_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Add_SMS_message_to_contact.ipynb", "imports": ["requests", "naas", "datetime.datetime, date, timezone", "pprint.pprint"], "image_url": ""}, {"objectID": "09a2fdd2c66a2ffb4736afbf1c4347feac6703273eccc90780482835a14a7760", "tool": "HubSpot", "notebook": "Add WhatsApp message to contact", "action": "", "tags": ["#hubspot", "#communications", "#whatsapp", "#snippet", "#contact", "#association"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook demonstrates how to add WhatsApp message to a given contact in HubSpot. It uses the communication endpoint in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Add_WhatsApp_message_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Add_WhatsApp_message_to_contact.ipynb", "imports": ["requests", "naas", "datetime.datetime, date, timezone", "pprint.pprint"], "image_url": ""}, {"objectID": "fffe7caf1ac0d096638c4e57e74ede411114700e1924b295ad76e864a1104f36", "tool": "HubSpot", "notebook": "Add note to contact", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#notes", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2023-08-29", "description": "This notebook demonstrates how to add a note to one a several contacts in HubSpot using their contact ID. This can be particularly useful for recording details about a contact's engagement with your published content or their usage of your product.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Add_note_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Add_note_to_contact.ipynb", "imports": ["requests", "naas", "datetime.datetime, date, timezone"], "image_url": ""}, {"objectID": "4f9aab526231f9a50b619d844a1e874debbbc1d6aaefc90759cf32850a66a802", "tool": "HubSpot", "notebook": "Associate contact to deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#contact", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook associates a contact to a deal in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Associate_contact_to_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Associate_contact_to_deal.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "a72923734c2d899bdf89bd2d41220b71d265ebd1628d1ec9c7d2df3dc46cae26", "tool": "HubSpot", "notebook": "Chat about a contact", "action": "", "tags": ["#hubspot", "#contact", "#activity", "#notes", "#emails", "#communications", "#meetings", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-21", "description": "This notebook demonstrates how to retrieve all activities from a contact URL in HuSpot in use it in Naas Chat.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Chat_about_a_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Chat_about_a_contact.ipynb", "imports": ["requests", "naas", "naas_drivers.hubspot, naas_chat_plugin", "pandas"], "image_url": ""}, {"objectID": "d5aef083b682b39a162f90c833fb5c6104fe72e3c839a9008e799212f82a8c80", "tool": "HubSpot", "notebook": "Chat about a deal", "action": "", "tags": ["#hubspot", "#chat", "#deals", "#last", "#discussion", "#conversation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-25", "created_at": "2023-09-25", "description": "This notebook assists you in discussing a deal on HubSpot by providing essential insights about the deal and its recent activities. This information will enable you to plan your next steps effectively.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Chat_about_a_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Chat_about_a_deal.ipynb", "imports": ["requests", "naas", "naas_drivers.hubspot, naas_chat_plugin", "pandas", "os"], "image_url": ""}, {"objectID": "21c2ec4f17d5dfd788890b76d6a094c3a8fa3ddd8246a849bd11b1f41f778019", "tool": "HubSpot", "notebook": "Create Task", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#task", "#snippet"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-02-24", "description": "This template will create a task in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_Task.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_Task.ipynb", "imports": ["datetime.datetime, timedelta", "requests", "json", "naas"], "image_url": ""}, {"objectID": "220bf21fcc2f41498798ec5655cdbf42fe612dc4b6d93e9fc11424e48f985b63", "tool": "HubSpot", "notebook": "Create company", "action": "", "tags": ["#hubspot", "#company", "#create", "#crm", "#business", "#management"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-25", "created_at": "2023-09-25", "description": "This notebook will show how to create a company in HubSpot and how it is useful for organizations.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_company.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "41a54dd1b30076c3f50da00bf2b549912f8c38f2209b3752b0c22bd5c465df00", "tool": "HubSpot", "notebook": "Create contact", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#create"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2022-02-21", "description": "This notebook demonstrates how to create a contact in HubSpot using HubSpot default properties.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_contact.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "a10c1080b82d40f568861bec9c4fb24ff42d65d11b78ddc719282e46a2afffaf", "tool": "HubSpot", "notebook": "Create contact from LinkedIn profile", "action": "", "tags": ["#hubspot", "#linkedin", "#profile", "#naas_drivers", "#snippet", "#sales"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-10-13", "description": "This notebook creates a contact in HubSpot from a LinkedIn profile URL with:\n- email\n- linkedinbio\n- phone and mobilephone\n- website\n- twitterhandle\n- firstname\n- lastname\n- info\n- jobtitle\n- industry\n- city\n- state\n- country\n- job_function\n- company\n- field_of_study", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_contact_from_LinkedIn_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_contact_from_LinkedIn_profile.ipynb", "imports": ["naas", "naas_drivers.hubspot, linkedin", "os.path, mkdir"], "image_url": ""}, {"objectID": "e8235f2c41e1848e65b08daadbc4a2c07bb88ad792e876174c4924d1b2a11f3d", "tool": "HubSpot", "notebook": "Create contact using custom properties", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#create"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2023-08-29", "description": "This notebook demonstrates how to create a contact in HubSpot using HubSpot default or custom properties.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_contact_with_custom_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_contact_with_custom_properties.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "d11c4d245d38c72a488cf4ef73f193f8c1c6618dc2aeedd06e3aee9ce8b807ac", "tool": "HubSpot", "notebook": "Create contacts from linkedin post likes", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#linkedin", "#post", "#contact", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook create new contacts based on LinkedIn post likes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_contacts_from_linkedin_post_likes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_contacts_from_linkedin_post_likes.ipynb", "imports": ["naas_drivers.linkedin, hubspot", "naas", "requests"], "image_url": ""}, {"objectID": "e4a548d7f36bef053fe0cb094f83c4eaca4a721fd4b7112548bbce0f8f3b102a", "tool": "HubSpot", "notebook": "Create deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook allows users to create deals in HubSpot, helping them to manage their sales pipeline.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Create_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Create_deal.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "0eafe8fc3415fe94e8707349db0bb4b27d516ecb3850492a06be7d4a0086f2ef", "tool": "HubSpot", "notebook": "Delete Task", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#task", "#snippet"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-03-12", "description": "This template will delete a task in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_Task.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_Task.ipynb", "imports": ["datetime.datetime, timedelta", "requests, math", "json", "naas"], "image_url": ""}, {"objectID": "18ba61523d3000719630fd0b6bc6b478568078713221a8163f89e7eadeb10dee", "tool": "HubSpot", "notebook": "Delete communication", "action": "", "tags": ["#hubspot", "#communications", "#snippet", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook demonstrates how to delete a communication using its ID using HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_communication.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_communication.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "c3a6736f70c48fb0c868fcc904e64f39fe1621cf5cf416d13654970ce52cafa6", "tool": "HubSpot", "notebook": "Delete a company", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#company", "#naas_drivers", "#snippet", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-09-25", "created_at": "2023-09-25", "description": "This notebook demonstrates how to delete a given company in HubSpot using its HubSpot ID.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_company.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "758eceb0755d55869262781c0fdbf0ae8897488501d0c5a019bb29f299889448", "tool": "HubSpot", "notebook": "Delete contact", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2022-02-21", "description": "This notebook demonstrates how to delete a given contact in HubSpot using its HubSpot ID.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_contact.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "297e616568c4e2565a8f512dd5e4db0a922305d4a2d09e26c6a0b22d5c90472e", "tool": "HubSpot", "notebook": "Delete deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook allows users to delete deals from their HubSpot account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_deal.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "42f6566a97e75f9a5683b1536e893e1088ec249bafe87e1601eb982be842a384", "tool": "HubSpot", "notebook": "Delete note", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#note", "#snippet", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2023-08-29", "description": "This notebook demonstrates how to delete a note using its ID using HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Delete_note.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Delete_note.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "dca97b52f36c302df5c197d00895c621c69829e47a41bc1869b310a2795d7deb", "tool": "HubSpot", "notebook": "Get Task", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#task", "#snippet", "#json"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-03-12", "description": "This template will get a task in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_Task.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_Task.ipynb", "imports": ["datetime.datetime, timedelta", "requests, math", "json", "naas"], "image_url": ""}, {"objectID": "06b11cf336c1e0d493eb89898cd3a39adcb000113e2f74b4d12d64c5e7f04932", "tool": "HubSpot", "notebook": "Get activities from contact", "action": "", "tags": ["#hubspot", "#contact", "#activity", "#notes", "#emails", "#communications", "#meetings", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-21", "description": "This notebook demonstrates how to retrieve all activities from a contact URL by combining various HubSpot API endpoints.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_activities_from_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_activities_from_contact.ipynb", "imports": ["requests", "naas", "naas_drivers.hubspot", "pandas"], "image_url": ""}, {"objectID": "c2c189b600c06f1e994fed0b3cfc63d3ea79a7df196d4bd011f46f91ea147905", "tool": "HubSpot", "notebook": "Get all companies", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#companies", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-23", "created_at": "2023-08-23", "description": "This notebook will get all companies from HubSpot CRM using the API and will be usefull to get a list of all companies in the CRM.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_all_companies.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_all_companies.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "2cc7be1f4752e97f41db9463ad356b8ae5c6497c16c15317610dc16372f975a1", "tool": "HubSpot", "notebook": "Get all contacts", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-23", "created_at": "2022-02-21", "description": "This notebook allows you to retrieve all contacts from HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_all_contacts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_all_contacts.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "5e8948b2a218d67932167e52f1709186e5a2d6d230316857c687794715b0db73", "tool": "HubSpot", "notebook": "Get all deals", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook provides a comprehensive overview of all deals in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_all_deals.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_all_deals.ipynb", "imports": ["naas_drivers.hubspot"], "image_url": ""}, {"objectID": "f085c6a0dfb61b23a506b44cb0181599a5bfb15014e5c592e594735aff488582", "tool": "HubSpot", "notebook": "Get all pipelines and dealstages", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#pipelines", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-10", "created_at": "2022-02-21", "description": "This notebook get all your pipelines and dealstages.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_all_pipelines_and_dealstages.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_all_pipelines_and_dealstages.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "29282cfa4a016e0aa6518f975cf5cd5e4fe644c0a94c7073549cea7aaf3676bd", "tool": "HubSpot", "notebook": "Get communications associated to contact", "action": "", "tags": ["#hubspot", "#api", "#contact", "#communications", "#linkedin", "#whatsapp", "#sms", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook demonstrates how to retrieve all communications associated to a contact in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_communications_associated_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_communications_associated_to_contact.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "e8f3175084d60841c26849c105eb3499543dd9b44adb851a790b5a470c44d851", "tool": "HubSpot", "notebook": "Get a company", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#company", "#naas_drivers", "#snippet", "#get"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-09-25", "created_at": "2023-09-25", "description": "This notebook demonstrates how to get a given company in using its hubspot ID.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_company.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "084ee054bd3721c966e8c3bc06217a3c5c7154efef048933eaa4ab0f55a3e84e", "tool": "HubSpot", "notebook": "Get contact brief", "action": "", "tags": ["#hubspot", "#contact", "#activity", "#notes", "#emails", "#communications", "#meetings", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-22", "created_at": "2023-09-22", "description": "This notebook illustrates the process of obtaining a contact brief in HubSpot. It fetches detailed contact information, along with all related activities between you and your sales team. These activities may include emails, notes, meetings, and communications via LinkedIn, WhatsApp, and SMS. The output is conveniently delivered as a text file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_contact_brief.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_contact_brief.ipynb", "imports": ["requests", "naas", "naas_drivers.hubspot, naas_chat_plugin", "pandas", "os"], "image_url": ""}, {"objectID": "9056bb1dcba589051252c2df8a24c91b9109e99293b11c1fe9d0b5d6fbb08197", "tool": "HubSpot", "notebook": "Get contact details from URL", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-21", "created_at": "2022-05-31", "description": "This notebook provides a method to retrieve contact details from a HubSpot contact URL using the HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_contact_details_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_contact_details_from_URL.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "6f72d8f451dccc72ecffed406a64ceab0e710237b87052e324d258e0153a6a3e", "tool": "HubSpot", "notebook": "Get contact details from email", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-21", "created_at": "2022-05-31", "description": "This notebook provides a method to retrieve contact details from a HubSpot contact email using the HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_contact_details_from_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_contact_details_from_email.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "ca0c0d07420d67bbdde9dff74791dd0bcef463a82a10315049cefef33713a892", "tool": "HubSpot", "notebook": "Get contact details from contact id", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-21", "created_at": "2022-05-31", "description": "This notebook provides a method to retrieve contact details from a HubSpot contact ID using the HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_contact_details_from_id.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_contact_details_from_id.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "57e771994762f2f1daf87e33bf4ee92ea4b096811bc09043847d120a66dded70", "tool": "HubSpot", "notebook": "Get contacts associated to deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#contact", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook get association between contacts and deals.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_contacts_associated_to_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_contacts_associated_to_deal.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "c3a9b9d1e98c629b1cb002d88a40903dc4d592e24e830e00c9b484c2bfa25b4a", "tool": "HubSpot", "notebook": "Get deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook provides a comprehensive overview of the HubSpot platform and its features to help you get the best deals.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_deal.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "90427433669e0a447b5aa778552086cdcad6418e1e5a81c0cf6d7a333a430b3f", "tool": "HubSpot", "notebook": "Get deal brief", "action": "", "tags": ["#hubspot", "#deal", "#activity", "#notes", "#emails", "#communications", "#meetings", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-22", "created_at": "2023-09-22", "description": "This notebook illustrates the process of obtaining a deal brief in HubSpot. It fetches detailed detail information, along with all related activities between you and your sales team. These activities may include emails, notes, meetings, and communications via LinkedIn, WhatsApp, and SMS. The output is conveniently delivered as a text file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_deal_brief.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_deal_brief.ipynb", "imports": ["requests", "naas", "naas_drivers.hubspot", "pandas", "os"], "image_url": ""}, {"objectID": "871e457a336ded192521c203bce981c5664048760631a9acb48df8ddca1cf81e", "tool": "HubSpot", "notebook": "Get meetings associated to contact", "action": "", "tags": ["#hubspot", "#api", "#meetings", "#retrieve", "#requests", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-11", "created_at": "2023-08-07", "description": "This notebook demonstrates how to retrieve meetings ID associated with a contact in HubSpot using the HubSpot API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_meetings_associated_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_meetings_associated_to_contact.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "c79e3c28a55e8062cd77c414c2edb9668bd1840467f3586806e81547276cecb5", "tool": "HubSpot", "notebook": "Get notes associated to contact", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#notes", "#snippet", "#json", "#contacts"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2023-08-29", "description": "This notebook demonstrates how to retrieve all notes associated to a contact in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_notes_associated_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_notes_associated_to_contact.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "d468de85f83026e5f3c404ed798b1a95bbbc7def17fc67c2a1f376d5fd7a35e4", "tool": "HubSpot", "notebook": "Get sales emails associated to contact", "action": "", "tags": ["#hubspot", "#api", "#contact", "#sales", "#emails", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-17", "description": "This notebook demonstrates how to retrieve all sales emails associated to a contact in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Get_sales_emails_associated_to_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Get_sales_emails_associated_to_contact.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "6f16b41d94a94ed30a6a592a36584708965f8a7bde0007c3723d973b49c01984", "tool": "HubSpot", "notebook": "List communication properties", "action": "", "tags": ["#hubspot", "#properties", "#communications", "#linkedin", "#whatsapp", "#sms", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook list all communications properties available in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_communication_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_communication_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "8431d65494aca14c3551905b84b6590708ed3d2f57c34243e368fd2cda8bc818", "tool": "HubSpot", "notebook": "List company properties", "action": "", "tags": ["#hubspot", "#properties", "#company", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-23", "created_at": "2023-08-23", "description": "This notebook list company properties in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_company_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_company_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "1cbde3b04095cadc48040885b0752305f813749b15590ff2c287874e3b3fa1a7", "tool": "HubSpot", "notebook": "List contact properties", "action": "", "tags": ["#hubspot", "#properties", "#contact", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-21", "description": "This notebook list the contact properties in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_contact_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_contact_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "e7ec070fd87d2ff5eb89ca90bbbd98c379e5224d217a3c1ceed6cd39a857e1a6", "tool": "HubSpot", "notebook": "List meeting properties", "action": "", "tags": ["#hubspot", "#api", "#meetings", "#retrieve", "#requests", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-11", "created_at": "2023-08-07", "description": "This notebook provides access to the list of meeting properties in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_meeting_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_meeting_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "97f11b70c0c60e6b95fc17a5fadd5030c37c2f97a3e2568cd31238ea6fb5ad34", "tool": "HubSpot", "notebook": "List notes properties", "action": "", "tags": ["#hubspot", "#properties", "#notes", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-21", "description": "This notebook list the notes properties in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_notes_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_notes_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "3c0890cc3cd13e3c6d72bc4ace0a28073c60c6bf770c0d1d68d6119ec12c4fd2", "tool": "HubSpot", "notebook": "List sales emails properties", "action": "", "tags": ["#hubspot", "#api", "#sales", "#emails", "#retrieve", "#requests", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-11", "created_at": "2023-08-07", "description": "This notebook provides access to the list of sales emails properties in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_List_sales_emails_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_List_sales_emails_properties.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "addc66ec405ac0fc7ad20e0d1e0fa3a85fbf06f6aac030dd8f2b4da355d35b1d", "tool": "HubSpot", "notebook": "Retrieve communication details", "action": "", "tags": ["#hubspot", "#get", "#read", "#communication", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook fetches detailed information for a specific communication (Linkedin, SMS or WhatsApp message). It can be helpful in obtaining further details from a communication ID, which can be acquired by extraction from a contact.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Retrieve_communication_details.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Retrieve_communication_details.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "05d1f96265b1e2aecae868c680041a298e4813049fab9f79887b6304fa8fcb40", "tool": "HubSpot", "notebook": "Retrieve meetings", "action": "", "tags": ["#hubspot", "#api", "#meetings", "#retrieve", "#requests", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-07", "created_at": "2023-08-07", "description": "This notebook uses requests to retrieve meetings from HubSpot API. It is usefull for organizations to get information about their meetings.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Retrieve_meetings.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Retrieve_meetings.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "000268b50a5a3408219513347b6002498b5f3680bb09035bc7ea4bdd502916a3", "tool": "HubSpot", "notebook": "Retrieve note details", "action": "", "tags": ["#hubspot", "#get", "#read", "#communication", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-17", "created_at": "2023-08-17", "description": "This notebook fetches detailed information for a specific note. It can be helpful in obtaining further details from a note ID, which can be acquired by extraction from a contact.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Retrieve_note.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Retrieve_note.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "9ca3ba5eae3a47b868a366803ceedd42514a9836b08a41e8e753b1d9f2bfe6cb", "tool": "HubSpot", "notebook": "Score contact from notes", "action": "", "tags": ["#hubspot", "#contact", "#activity", "#notes", "#emails", "#communications", "#meetings", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-21", "created_at": "2023-08-21", "description": "This notebook illustrates the process of scoring a contact in HubSpot based on the count of their notes, which correspond to LinkedIn interactions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Score_contact_from_notes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Score_contact_from_notes.ipynb", "imports": ["naas", "naas_drivers.hubspot", "requests", "pandas"], "image_url": ""}, {"objectID": "c3086aff9615d012c42b6cb7ccc977193b8092d7fdf6b1e49084fa7b519cef76", "tool": "HubSpot", "notebook": "Send LinkedIn invitations from contacts", "action": "", "tags": ["#hubspot", "#invitation", "#automation", "#sales", "#linkedin"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-05-04", "description": "This notebook send LinkedIn invitation to your HubSpot contacts.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_LinkedIn_invitations_from_contacts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_LinkedIn_invitations_from_contacts.ipynb", "imports": ["naas", "naas_drivers.hubspot, linkedin", "pandas", "os"], "image_url": ""}, {"objectID": "e34b8e2c2e86d41d5ff8cf46f34b81878c899d3c389c43d81261fa1b9f64d7e6", "tool": "HubSpot", "notebook": "Send closed deals weekly", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#scheduler", "#asset", "#html", "#png", "#csv", "#naas_drivers", "#naas", "#analytics", "#automation", "#image", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-11-23", "description": "This notebook send a weekly email based on your deals closed.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_closed_deals_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_closed_deals_weekly.ipynb", "imports": ["naas_drivers.hubspot", "datetime.datetime, timedelta", "pandas", "plotly.graph_objects", "plotly.subplots.make_subplots", "naas"], "image_url": ""}, {"objectID": "4063affa21ca76b463fb3696bcd1993679d6e2c91d8614b9e1d0f84d57aec6ef", "tool": "HubSpot", "notebook": "Send contacts to gsheet", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#gsheet", "#snippet", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook allows you to send HubSpot contacts to a Google Sheet for easy tracking and organization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_contacts_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_contacts_to_gsheet.ipynb", "imports": ["naas_drivers.hubspot, gsheet", "naas"], "image_url": ""}, {"objectID": "76a862a59d2f61ce3a6d17fb726390ff287a4c8ab26b8281a7f8e1fa0857de4c", "tool": "HubSpot", "notebook": "Send deals to gsheet", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#gsheet", "#snippet", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook allows you to send HubSpot deals to a Google Sheet for easy tracking and analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_deals_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_deals_to_gsheet.ipynb", "imports": ["naas_drivers.hubspot, gsheet", "naas"], "image_url": ""}, {"objectID": "fb271b446d3f68d5c35323574a36baba6d1c855598494a8807a73829a9641327", "tool": "HubSpot", "notebook": "Send new deals created weekly", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#scheduler", "#asset", "#html", "#png", "#csv", "#naas_drivers", "#naas", "#analytics", "#automation", "#image", "#plotly", "#notification", "#email"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-11-23", "description": "This notebook send a weekly email based on your deals created.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_new_deals_created_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_new_deals_created_weekly.ipynb", "imports": ["naas_drivers.hubspot, emailbuilder", "datetime.datetime, timedelta", "pandas", "plotly.graph_objects", "plotly.subplots.make_subplots", "naas"], "image_url": ""}, {"objectID": "a82cec3af17c939d191f8ce0883159014a63484fd77e1ec01c92c4d6358c90aa", "tool": "HubSpot", "notebook": "Send sales brief", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#notification", "#asset", "#emailbuilder", "#scheduler", "#naas", "#analytics", "#automation", "#email", "#text", "#plotly", "#html", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook send a sales brief based on your HubSpot activity.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_sales_brief.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_sales_brief.ipynb", "imports": ["naas_drivers.emailbuilder, hubspot", "naas", "pandas", "datetime.datetime", "naas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "d49ac09de4eaf9bef7efdf56581a4f54891f80799d0746bfff20181ac130cdf5", "tool": "HubSpot", "notebook": "Send sales pipeline to Notion", "action": "", "tags": ["#hubspot", "#notion", "#sales", "#pipeline", "#automation", "#integration"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-10", "created_at": "2023-04-26", "description": "This notebook automates the process of sending a sales pipeline from HubSpot to Notion. It is useful for organizations that need to keep track of their sales pipeline in both HubSpot and Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Send_sales_pipeline_to_Notion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Send_sales_pipeline_to_Notion.ipynb", "imports": ["naas", "naas_drivers.hubspot, notion", "pandas", "datetime.datetime", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "a0410dbd5e2e886db5230942a8dd104d62fb9101565a66fba5ea54f12ae0a64e", "tool": "HubSpot", "notebook": "Update Task", "action": "", "tags": ["#hubspot", "#sales", "#crm", "#engagements", "#task", "#snippet"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-03-12", "description": "This template will update a task in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_Task.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_Task.ipynb", "imports": ["datetime.datetime, timedelta", "naas_drivers.hubspot", "requests, math", "json", "naas"], "image_url": ""}, {"objectID": "0cde49d174c0baa2b8fdf7be78e7cde303d9bc3e2ea9a4076ba7e01894d316df", "tool": "HubSpot", "notebook": "Update a company using custom properties", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#company", "#naas_drivers", "#snippet", "#update", "#patch"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-09-25", "created_at": "2023-09-25", "description": "This notebook demonstrates how to update a given company in HubSpot using HubSpot default or custom properties.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_company.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "8a175a5d458b09dfe5dbc8c5e40f3a0bbd41192e6a77aa6f922960b017c043e1", "tool": "HubSpot", "notebook": "Update contact", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#update"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2022-02-21", "description": "This notebook allows users to update contact information in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_contact.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "1a66fd4eb09d5f34d95b8451ca85989c9743a9060a6540d11d2c19a559a516bb", "tool": "HubSpot", "notebook": "Update contact using custom properties", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#snippet", "#update", "#patch"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-29", "created_at": "2023-08-29", "description": "This notebook demonstrates how to update a given contact in HubSpot using HubSpot default or custom properties.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_contact_using_custom_properties.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_contact_using_custom_properties.ipynb", "imports": ["naas_drivers.hubspot", "naas"], "image_url": ""}, {"objectID": "fc58ab67c6bf65de49ba644a4fe56839a4aab81c0c594fbfad7fd64ff672f030", "tool": "HubSpot", "notebook": "Update deal", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#deal", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook allows users to update deals in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_deal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_deal.ipynb", "imports": ["naas_drivers.hubspot"], "image_url": ""}, {"objectID": "308ffca5968aaa53ed2e5beaf26fc4270f3ff740e04278f9f51bcaa5b6008cee", "tool": "HubSpot", "notebook": "Update followers from linkedin", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#linkedin", "#network", "#scheduler", "#naas", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook update the LinkedIn followers count for a contact in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_followers_from_linkedin.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_followers_from_linkedin.ipynb", "imports": ["naas_drivers.hubspot, linkedin", "naas", "pandas"], "image_url": ""}, {"objectID": "69dc47c6359ecfdc7f0345ae2afa727bbd0bdea6bd96d614a1d49028f5e87679", "tool": "HubSpot", "notebook": "Update jobtitle country industry from linkedin", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#linkedin", "#identity", "#scheduler", "#naas", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook update the jobtitle, country and industry for a contact in HubSpot.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_jobtitle_country_industry_from_linkedin.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_jobtitle_country_industry_from_linkedin.ipynb", "imports": ["naas_drivers.hubspot, linkedin", "naas", "pandas"], "image_url": ""}, {"objectID": "73b8a92ef19787ace73fd804dc9fffc4cd440670a11edf54097e734a3151e145", "tool": "HubSpot", "notebook": "Update linkedinbio from google", "action": "", "tags": ["#hubspot", "#crm", "#sales", "#contact", "#naas_drivers", "#googlesearch", "#scheduler", "#naas", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-21", "description": "This notebook update HubSpot linkedin URL based on Google Search with firstname and lastname.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/HubSpot/HubSpot_Update_linkedinbio_from_google.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/HubSpot/HubSpot_Update_linkedinbio_from_google.ipynb", "imports": ["naas_drivers.hubspot", "naas", "pandas", "googlesearch.search", "time", "re"], "image_url": ""}, {"objectID": "f86b412a2bb0447988f91dbda5fc2dd925f5d6ec01dc474ecbd1f3be6999ba96", "tool": "Hugging Face", "notebook": "Ask boolean question to T5", "action": "", "tags": ["#huggingface", "#ml", "#sales", "#ai", "#text"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-08", "description": "## T5-base finetuned on BoolQ (superglue task)\nThis notebook is for demonstrating the training and use of the text-to-text-transfer-transformer (better known as T5) on boolean questions (BoolQ). The example use case is a validator indicating if an idea is environmentally friendly. Nearly any question can be passed into the `query` function (see below) as long as a context to a question is given.\n\nAuthor: Maximilian Frank ([script4all.com](//script4all.com)) - Copyleft license\n\nNotes:\n- The model from [huggingface.co/mrm8488/t5-base-finetuned-boolq](//huggingface.co/mrm8488/t5-base-finetuned-boolq) is used in this example as it is an already trained t5-base model on boolean questions (BoolQ task of superglue).\n- Documentation references on [huggingface.co/transformers/model_doc/t5.html#training](//huggingface.co/transformers/model_doc/t5.html#training), template script on [programming-review.com/machine-learning/t5](//programming-review.com/machine-learning/t5)\n- The greater the model, the higher the accuracy on BoolQ (see [arxiv.org/pdf/1910.10683.pdf](//arxiv.org/pdf/1910.10683.pdf)):\n t5-small|t5-base|t5-large|t5-3B|t5-11B\n -|-|-|-|-\n 76.4%|81.4%|85.4%|89.9%|91.2%", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Hugging%20Face/Hugging_Face_Ask_boolean_question_to_T5.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Hugging%20Face/Hugging_Face_Ask_boolean_question_to_T5.ipynb", "imports": ["json", "torch", "operator.itemgetter", "distutils.util.strtobool", "transformers.AutoTokenizer, AutoModelForSeq2SeqLM", "goods.\", # should be false"], "image_url": ""}, {"objectID": "5968f81ee8ac7fab47f97e24e666efeee74dd873bb1c1444a24459ea0fa9cabf", "tool": "Hugging Face", "notebook": "Naas drivers integration", "action": "", "tags": ["#huggingface", "#nlp", "#huggingface", "#api", "#models", "#transformers", "#sales", "#ai", "#text"], "author": "Gagan Bhatia", "author_url": "https://www.linkedin.com/in/gbhatia30/", "updated_at": "2023-04-12", "created_at": "2021-08-31", "description": "In this notebook, you will be able to explore the Hugging Face transformers package with minimal technical knowledge thanks to Naas low-code drivers.
\nHugging Face is an immensely popular Python library providing pretrained models that are extraordinarily useful for a variety of natural language processing (NLP) tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Hugging%20Face/Hugging_Face_Naas_drivers_integration.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Hugging%20Face/Hugging_Face_Naas_drivers_integration.ipynb", "imports": ["naas_drivers.huggingface", "ant thing in your life right now?\""], "image_url": ""}, {"objectID": "6ae02ceb527a779c1815a5254e6a3b1292f024034c61fa1c62c4dfcb88905990", "tool": "Hugging Face", "notebook": "Question Answering from PDF", "action": "", "tags": ["#huggingface", "#ml", "#question_answer", "#ai", "#text"], "author": "Muhammad Talha Khan", "author_url": "https://www.linkedin.com/in/muhtalhakhan/", "updated_at": "2023-04-12", "created_at": "2022-11-02", "description": "This notebook provides a way to answer questions from PDF documents using Hugging Face's natural language processing capabilities.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Hugging%20Face/Hugging_Face_Question_Answering_from_PDF.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Hugging%20Face/Hugging_Face_Question_Answering_from_PDF.ipynb", "imports": ["transformers.pipeline", "urllib.request", "PyPDF2", "io"], "image_url": ""}, {"objectID": "d7b25ccb94399a05e017b4dbcc1175264b9d63a0846fe91c6e98ae73e7464ce5", "tool": "IFTTT", "notebook": "Post on Twitter", "action": "", "tags": ["#ifttt", "#nocode", "#snippet", "#marketing", "#twitter"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows you to post messages to Twitter using IFTTT.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IFTTT/IFTTT_Post_on_Twitter.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IFTTT/IFTTT_Post_on_Twitter.ipynb", "imports": ["naas_drivers.ifttt"], "image_url": ""}, {"objectID": "c2217c4b3eafedeb845aa615041292cacf60fd6aa3366a80e4d85ab17ac0d9a6", "tool": "IFTTT", "notebook": "Trigger workflow", "action": "", "tags": ["#ifttt", "#nocode", "#snippet", "#marketing"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows users to create automated workflows based on triggers from IFTTT.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IFTTT/IFTTT_Trigger_workflow.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IFTTT/IFTTT_Trigger_workflow.ipynb", "imports": ["naas_drivers.ifttt"], "image_url": ""}, {"objectID": "d6489bb4d5adeb7d00bb71c99521b750528eb0d76f94b0007a217d5902623f0e", "tool": "IMDB", "notebook": "Top Movie", "action": "", "tags": ["#imdb", "#python", "#webscraping", "#imdb", "#analytics", "#operations", "#csv"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-04-12", "created_at": "2021-11-23", "description": "This notebook provides a list of the top-rated movies according to IMDB ratings.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IMDB/Top_IMDB_Movie.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IMDB/Top_IMDB_Movie.ipynb", "imports": ["scrapy", "scrapy", "scrapy.crawler.CrawlerProcess", "scrapy.crawler.CrawlerRunner", "crochet.setup, wait_for", "crochet.setup, wait_for"], "image_url": ""}, {"objectID": "9e77de3cd0e1966b9245a077a2cee42c80084a9a388822b57d33a68f0acb6526", "tool": "INPI", "notebook": "Download PDF recap", "action": "", "tags": ["#inpi", "#pdf", "#snippet", "#url", "#naas", "#societe", "#opendata"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-05-04", "description": "This notebook downloads a PDF summary of INPI (Instituto Nacional da Propriedade Industrial) data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/INPI/INPI_Download_PDF_recap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/INPI/INPI_Download_PDF_recap.ipynb", "imports": ["urllib"], "image_url": ""}, {"objectID": "2802ff736a7d9f625d7bb08a6e63f44d451728998bc8eacf923f17faedb940f7", "tool": "IPyWidgets", "notebook": "Create button", "action": "", "tags": ["#ipywidgets", "#naas", "#secret", "#snippet", "#operation", "#button"], "author": "Ismail CHIHAB", "author_url": "https://www.linkedin.com/in/ismail-chihab-4b0a04202/", "updated_at": "2023-04-12", "created_at": "2022-08-05", "description": "This notebook demonstrates how to use IPyWidgets to create an interactive button.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IPyWidgets/IPyWidgets_Create_button.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IPyWidgets/IPyWidgets_Create_button.ipynb", "imports": ["IPython.display.display, clear_output", "ipywidgets.widgets"], "image_url": ""}, {"objectID": "f810583e80c41aba6409ca9a2f9c0af3b653ab7a0d807b424564d03f1fd6a773", "tool": "IPyWidgets", "notebook": "Create input text and submit button", "action": "", "tags": ["#ipywidgets", "#naas", "#secret", "#snippet", "#operation", "#button", "#text"], "author": "Ismail CHIHAB", "author_url": "https://www.linkedin.com/in/ismail-chihab-4b0a04202/", "updated_at": "2023-04-12", "created_at": "2022-08-05", "description": "This notebook demonstrates how to use IPyWidgets to create an interactive input text box and submit button.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IPyWidgets/IPyWidgets_Create_input_text_and_submit_button.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IPyWidgets/IPyWidgets_Create_input_text_and_submit_button.ipynb", "imports": ["IPython.display.display, clear_output", "ipywidgets.widgets"], "image_url": ""}, {"objectID": "a68d46a0afb9b7c23e894afa2019cc7a7a9f4ee51ebf45ca51289f28af308652", "tool": "IPyWidgets", "notebook": "Setup naas secret", "action": "", "tags": ["#ipywidgets", "#naas", "#secret", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-05", "description": "This notebook provides instructions for setting up a secure connection to a NaaS (Network-as-a-Service) using IPyWidgets.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IPyWidgets/IPyWidgets_Setup_naas_secret.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IPyWidgets/IPyWidgets_Setup_naas_secret.ipynb", "imports": ["IPython.display.display, clear_output", "ipywidgets.widgets", "naas"], "image_url": ""}, {"objectID": "5700cab9e7293ba8a0b3a8c5a05507f0e397b5a649dbab6e1c46d4cad7c7ee1a", "tool": "IPython", "notebook": "Display dynamic link in Jupyter Lab", "action": "", "tags": ["#ipython", "#jupyterlab", "#markdown", "#dynamic", "#link"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-09-27", "created_at": "2023-09-27", "description": "This notebook shows how to display a link in Jupyter Lab using Markdown syntax.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IPython/IPython_Display_dynamic_link_in_Jupyter_Lab.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IPython/IPython_Display_dynamic_link_in_Jupyter_Lab.ipynb", "imports": ["IPython.display.Markdown"], "image_url": ""}, {"objectID": "2b6a8399ba0ec449ff89d9613b7c9dbefa5e8eb4c3baf8b472fdbdb7847e2b43", "tool": "IUCN", "notebook": "Extinct species", "action": "", "tags": ["#iucn", "#opendata", "#extinctspecies", "#analytics", "#plotly"], "author": "Martin Delasalle", "author_url": "https://github.com/delasalle-sio-martin", "updated_at": "2023-04-12", "created_at": "2021-05-28", "description": "Source : https://www.iucnredlist.org/statistics", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/IUCN/IUCN_Extinct_species.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/IUCN/IUCN_Extinct_species.ipynb", "imports": ["pandas", "plotly.express"], "image_url": ""}, {"objectID": "63e5f68d32da97478d275e24f56052d1b338bc9447562f7df52aca764f0405cf", "tool": "Insee", "notebook": "Download PDF recap", "action": "", "tags": ["#insee", "#pdf", "#snippet", "#url", "#naas", "#societe", "#opendata"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-05-04", "description": "This notebook downloads PDF summaries of data from the French National Institute of Statistics and Economic Studies (INSEE).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Insee/Insee_Download_PDF_recap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Insee/Insee_Download_PDF_recap.ipynb", "imports": ["urllib"], "image_url": ""}, {"objectID": "8c1d59ba9fc141ddf76ab615ec70620884b5be94f4cde842bd75126ac862db52", "tool": "Instagram", "notebook": "Get stats from posts", "action": "", "tags": ["#instagram", "#snippet", "#dataframe", "#content"], "author": "Mohamed Abidi", "author_url": "https://www.linkedin.com/in/mohamed-abidi-919505192/", "updated_at": "2023-04-12", "created_at": "2022-02-11", "description": "This notebook provides an easy way to analyze Instagram posts and gain insights into their performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Instagram/Instagram_Get_stats_from_posts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Instagram/Instagram_Get_stats_from_posts.ipynb", "imports": ["requests", "json", "datetime", "pandas"], "image_url": ""}, {"objectID": "38c44121d518d242dcfd1209fca1b300a11475f5836b8ae8f214c0b4524816a9", "tool": "Instagram", "notebook": "Post image and caption", "action": "", "tags": ["#instagram", "#snippet", "#content"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows users to post images and captions to their Instagram account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Instagram/Instagram_Post_image_and_caption.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Instagram/Instagram_Post_image_and_caption.ipynb", "imports": ["instabot.Bot", "instabot.Bot", "naas"], "image_url": ""}, {"objectID": "ea1fbba772a47f2a2f57b1c76935f62728ba2bb7749c0edd2edb475b43a35037", "tool": "Integromat", "notebook": "Trigger workflow", "action": "", "tags": ["#integromat", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-23", "description": "This notebook allows you to create automated workflows that are triggered by specific events.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Integromat/Integromat_Trigger_workflow.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Integromat/Integromat_Trigger_workflow.ipynb", "imports": ["naas_drivers.integromat"], "image_url": ""}, {"objectID": "9366cd2a8b5ebabc8fa6722758d297cf0a47d5b09246c09565bfe44c0f0c5350", "tool": "JSON", "notebook": "Convert Python Objects to", "action": "", "tags": ["#json", "#python", "#convert", "#object", "#serialize", "#deserialize"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will show how to convert Python objects to JSON and how to deserialize JSON back into Python objects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Convert_Python_Objects_to_JSON.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Convert_Python_Objects_to_JSON.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "566b67709b26f1097172c3b9c9641f132b8cf9d299ba3b314bda01fa26e3c31f", "tool": "JSON", "notebook": "Pretty print data", "action": "", "tags": ["#json", "#prettyprint", "#data", "#format", "#parse", "#string"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will show how to pretty print JSON data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Pretty_print_JSON_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Pretty_print_JSON_data.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "87d99fa50cdfeb99934671dc8dc2667c10df4a549bcea2874106f99651860146", "tool": "JSON", "notebook": "Read local file", "action": "", "tags": ["#json", "#python", "#read", "#file", "#data", "#parse"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-03-10", "description": "This notebook will demonstrate how to read a json file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Read_local_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Read_local_file.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "9cee4953ea85382e65f4d07efd0a162eb35b120f714fd0da9f0de60f6426bddb", "tool": "JSON", "notebook": "Save dataframe to file", "action": "", "tags": ["#json", "#python", "#file", "#save", "#data"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will demonstrate how to save a DataFrame to a json file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Save_dataframe_to_JSON_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Save_dataframe_to_JSON_file.ipynb", "imports": ["json", "pandas"], "image_url": ""}, {"objectID": "050391ecb5e0318f1aea99870a20423b913b3baef4dfac8b3ecd9d1c32618266", "tool": "JSON", "notebook": "Save dict to file", "action": "", "tags": ["#json", "#python", "#file", "#save", "#data"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-05-09", "created_at": "2023-03-10", "description": "This notebook will demonstrate how to save a dict to a json file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Save_dict_to_JSON_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Save_dict_to_JSON_file.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "c603c422f9e39d2ea960638448b510dbc4027f4cf6c068d0f196a82a161c3fd2", "tool": "JSON", "notebook": "Send to Google Sheets spreadsheet", "action": "", "tags": ["#json", "#gsheet", "#python", "#read", "#file", "#data", "#parse", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook will demonstrate how to send a json file to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/JSON/JSON_Send_to_Google_Sheets_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/JSON/JSON_Send_to_Google_Sheets_spreadsheet.ipynb", "imports": ["json", "naas_drivers.gsheet", "pandas"], "image_url": ""}, {"objectID": "d9501bdba4a7b281ae7e32722e5f7f8e7ad52825702b91f62463c937b0ab9129", "tool": "Johns Hopkins", "notebook": "Covid19 Active Cases", "action": "", "tags": ["#johnshopkins", "#opendata", "#analytics", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-27", "description": "This notebook provides an interactive visualization of the active cases of Covid-19 reported by Johns Hopkins University.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Johns%20Hopkins/Johns_Hopkins_Covid19_Active_Cases.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Johns%20Hopkins/Johns_Hopkins_Covid19_Active_Cases.ipynb", "imports": ["pandas", "plotly.express", "plotly.graph_objects", "matplotlib.pyplot"], "image_url": ""}, {"objectID": "d8d061ddd919705d7ea10dbff535f312aa8690112a7689c30b77706e9b482a93", "tool": "Johns Hopkins", "notebook": "Get Covid19 data", "action": "", "tags": ["#johnshopkins", "#opendata", "#analytics", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an easy way to access and analyze Covid19 data from Johns Hopkins University.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Johns%20Hopkins/Johns_Hopkins_Get_Covid19_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Johns%20Hopkins/Johns_Hopkins_Get_Covid19_data.ipynb", "imports": ["pandas", "naas"], "image_url": ""}, {"objectID": "db5fcbb8c6b35101661e8ce19138d4b5ffe286f326252acd8c9993a4f8ea822b", "tool": "Jupyter Notebooks", "notebook": "Add cells in notebook json", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides instructions on how to add cells to a Jupyter Notebook using JSON.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Add_cells_in_notebook_json.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Add_cells_in_notebook_json.ipynb", "imports": ["json", "pprint.pprint"], "image_url": ""}, {"objectID": "6896c6a7f08c8189f132dadc917d7260fd09df359c2465592db7987056bca0c0", "tool": "Jupyter Notebooks", "notebook": "Add tags in cells", "action": "", "tags": ["#jupyternotebooks", "#jupyter", "#awesome-notebooks", "#tags", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook provides a guide to adding tags to cells in Jupyter Notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Add_tags_in_cells.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Add_tags_in_cells.ipynb", "imports": ["os", "json", "pprint.pprint"], "image_url": ""}, {"objectID": "40bc861fbc7e6401524526236bf9efeebd65f31e1cce745a877aa263ff42ac3f", "tool": "Jupyter Notebooks", "notebook": "Apply black on notebook file", "action": "", "tags": ["#jupyter", "#notebook", "#black", "#python", "#formatting", "#style"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-26", "created_at": "2023-04-26", "description": "This notebook explains how to apply the black formatting style to a Jupyter Notebook file. It is usefull for organizations that want to ensure a consistent coding style across their notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Apply_black_on_notebook_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Apply_black_on_notebook_file.ipynb", "imports": ["json", "subprocess"], "image_url": ""}, {"objectID": "831c231ab1ea59f38424b6201727c2f8c65b45b75bf6e6513944957fe8399b71", "tool": "Jupyter Notebooks", "notebook": "Count code characters", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#read", "#codecharacters", "#snippet", "#operations", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides a tool to count the number of characters in code written in Jupyter Notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Count_code_characters.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Count_code_characters.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "3b184500ce95f1ea2824f7968046188e744c2bf9c912d17b346b15a2831ef97e", "tool": "Jupyter Notebooks", "notebook": "Count code lines", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#read", "#codelines", "#snippet", "#operations", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides a tool to count the number of lines of code in a Jupyter Notebook.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Count_code_lines.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Count_code_lines.ipynb", "imports": ["json"], "image_url": ""}, {"objectID": "4a5084bb5ec4b1b23f29c6699dddb97d95fb5bd81eb9cfbbc9c5241b2575f500", "tool": "Jupyter Notebooks", "notebook": "Get installs", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#read", "#installs", "#snippet", "#operations", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides instructions for installing Jupyter Notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Get_installs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Get_installs.ipynb", "imports": ["json", "pprint.pprint"], "image_url": ""}, {"objectID": "9fbda94a4556947e1be3d9cba5532b7757857f8dc5fab92ec7ab9df63d3a2a7e", "tool": "Jupyter Notebooks", "notebook": "Get libraries", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#read", "#libraries", "#snippet", "#operations", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides instructions on how to install and use libraries in Jupyter Notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Get_libraries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Get_libraries.ipynb", "imports": ["json", "pprint.pprint", "\" in source and \".\" in source:", "\")[0]", "\")[-1]", "\" not in source and \".\" in source:", "\")[-1]"], "image_url": ""}, {"objectID": "49c918990b576442820a51fda634fe182ae747b6379542038cc96566e894c3af", "tool": "Jupyter Notebooks", "notebook": "Read file json", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#read", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook provides a guide to reading and manipulating JSON files using Jupyter Notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Read_file_json.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Read_file_json.ipynb", "imports": ["json", "pprint.pprint"], "image_url": ""}, {"objectID": "69cd935098a7bced50fbde048ea679fadd95403925f92771cbfb08e935f17754", "tool": "Jupyter Notebooks", "notebook": "Save file ipynb", "action": "", "tags": ["#jupyternotebooks", "#naas", "#jupyter-notebooks", "#save", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-04", "description": "This notebook allows users to save their work in an interactive, web-based format (.ipynb).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter%20Notebooks/Jupyter_Notebooks_Save_file_ipynb.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter%20Notebooks/Jupyter_Notebooks_Save_file_ipynb.ipynb", "imports": ["json", "pprint.pprint"], "image_url": ""}, {"objectID": "7e1066808d3b59f72af3abe06bd16360aba9c812315e7d4590b08a5ea7e4cc4a", "tool": "Jupyter", "notebook": "Get server uptime", "action": "", "tags": ["#jupyter", "#server", "#uptime", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook provides a way to check the server uptime using Jupyter.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter/Jupyter_Get_server_uptime.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter/Jupyter_Get_server_uptime.ipynb", "imports": ["naas_drivers.jupyter", "os.environ"], "image_url": ""}, {"objectID": "8b7b0d0e546ea07301fe985252766cfa1c1a046fd3771acf0dba7a1bad478638", "tool": "Jupyter", "notebook": "Get user information", "action": "", "tags": ["#jupyter", "#user", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a way to retrieve user information from Jupyter.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter/Jupyter_Get_user_information.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter/Jupyter_Get_user_information.ipynb", "imports": ["naas_drivers.jupyter", "os.environ"], "image_url": ""}, {"objectID": "8853628334515ac0c222cc72944e39192d0127dea12852762c80ced3ea104901", "tool": "Jupyter", "notebook": "Get user session", "action": "", "tags": ["#jupyter", "#user", "#session", "#kernels", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook provides a way to get information about the current user's Jupyter session.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter/Jupyter_Get_user_session.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter/Jupyter_Get_user_session.ipynb", "imports": ["naas_drivers.jupyter", "os.environ"], "image_url": ""}, {"objectID": "580e2e6eb9052fc667d90d6c2853af8778e963531368f1c22199294e3c7f9da5", "tool": "Jupyter", "notebook": "Get user terminal", "action": "", "tags": ["#jupyter", "#user", "#terminal", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook provides a user-friendly interface to access a terminal for running commands.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter/Jupyter_Get_user_terminal.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter/Jupyter_Get_user_terminal.ipynb", "imports": ["naas_drivers.jupyter", "os.environ"], "image_url": ""}, {"objectID": "6c5de096a088ddb31aecdc20d57173bc5605c61ba81be7298c86cec24288d8c4", "tool": "Jupyter", "notebook": "Restart server", "action": "", "tags": ["#jupyter", "#server", "#restart", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook provides instructions on how to restart a Jupyter server.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Jupyter/Jupyter_Restart_server.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Jupyter/Jupyter_Restart_server.ipynb", "imports": ["naas_drivers.jupyter", "os.environ"], "image_url": ""}, {"objectID": "96e73cf9dc93e28d3e1d87b810d335505e2b1fb7a834579b2aa36f26df1e9f3a", "tool": "Kaggle", "notebook": "Download Data", "action": "", "tags": ["#kaggle", "#dataset", "#download", "#data", "#datascience"], "author": "Muhammad Waqar Gul", "author_url": "https://www.linkedin.com/in/waqar-gul", "updated_at": "2023-04-12", "created_at": "2022-10-11", "description": "This notebook provides instructions on how to download data from Kaggle for use in data analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Kaggle/Kaggle_Download_Data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Kaggle/Kaggle_Download_Data.ipynb", "imports": ["opendatasets", "pandas", "opendatasets", "os.path"], "image_url": ""}, {"objectID": "0c9df728db7a93e2a51b17382bce93ac3e3ac414dc2e0fffb72627a0863f4107", "tool": "Knative", "notebook": "Create command file", "action": "", "tags": ["#knative", "#operations", "#dashboards", "#dash", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-22", "description": "This notebook provides instructions on how to create a command file for Knative.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Knative/Knative_Create_command_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Knative/Knative_Create_command_file.ipynb", "imports": [], "image_url": ""}, {"objectID": "658a8244b01dfe532c4faaf8423ce808aca1020f8afdf491d99810b8e1cb4ba1", "tool": "LangChain", "notebook": "CSV Agent", "action": "", "tags": ["#csv", "#agent", "#langchain", "#questionanswering", "#toolkit", "#example"], "author": "Hamid Mukhtar", "author_url": "https://www.linkedin.com/in/mukhtar-hamid/", "updated_at": "2023-06-21", "created_at": "2023-06-01", "description": "This notebook shows how to use agents to interact with a csv. It is mostly optimized for question answering.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LangChain/LangChain_CSV_Agent.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_CSV_Agent.ipynb", "imports": ["langchain", "langchain.agents.create_csv_agent", "langchain.llms.OpenAI", "langchain.chat_models.ChatOpenAI", "langchain.agents.agent_types.AgentType", "pandas", "naas"], "image_url": ""}, {"objectID": "82653462f187b1612eabf3410fb8c69cd5f3bc64d1b6a7828d840867d3d86cfd", "tool": "LangChain", "notebook": "Gmail Toolkit", "action": "", "tags": ["#langchain", "#gmail", "#toolkit", "#api", "#email", "#connect"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook walks through connecting a LangChain email to the Gmail API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LangChain/LangChain_Gmail_Toolkit.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_Gmail_Toolkit.ipynb", "imports": ["langchain", "langchain.llms.OpenAI", "langchain.agents.agent_toolkits.GmailToolkit", "langchain.agents.initialize_agent, AgentType", "naas"], "image_url": ""}, {"objectID": "97b75457b5be4aa0267637c05db4895ccd911ef922cded10242a313ab1245dbb", "tool": "LangChain", "notebook": "JSON Agent", "action": "", "tags": ["#json", "#agent", "#langchain", "#toolkit", "#example", "#python"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-07-31", "created_at": "2023-07-20", "description": "This notebook showcases an agent designed to interact with large JSON/dict objects. This is useful when you want to answer questions about a JSON blob that\u2019s too large to fit in the context window of an LLM. The agent is able to iteratively explore the blob to find what it needs to answer the user\u2019s question.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LangChain/LangChain_JSON_Agent.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_JSON_Agent.ipynb", "imports": ["langchain", "validators", "langchain.agents.agent_toolkits.JsonToolkit", "langchain.tools.json.tool.JsonSpec", "langchain.agents.create_json_agent", "langchain.llms.openai.OpenAI", "json", "urllib.request.urlopen", "validators", "naas", "pandas"], "image_url": ""}, {"objectID": "cbffbc54c632f632e483b97eefb687edc995365015f26e51df9e55644b0272ac", "tool": "LangChain", "notebook": "Pandas Dataframe Agent", "action": "", "tags": ["#langchain", "#pandas", "#dataframe", "#agent", "#python", "#toolkit"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-21", "created_at": "2023-06-01", "description": "This notebook shows how to use agents to interact with a pandas dataframe. It is mostly optimized for question answering.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LangChain/LangChain_Pandas_Dataframe_Agent.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_Pandas_Dataframe_Agent.ipynb", "imports": ["langchain", "langchain.agents.create_pandas_dataframe_agent", "langchain.llms.OpenAI", "pandas", "naas"], "image_url": ""}, {"objectID": "327f0a8a8dfb334ce84fe3443964d4f1607c5346b593742909d57a379024620f", "tool": "LangChain", "notebook": "Vector Search on PDF", "action": "", "tags": ["#langchain", "#pdf", "#weaviate", "#huggingface", "#llm", "#database", "#embeddings"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil", "updated_at": "2023-09-27", "created_at": "2023-09-27", "description": "This notebook is used to perform vector search on your PDF and it will answer basic questions that are closely related based on the prompt provided.\n\nIt uses:\n- PyPDF2 - Get text from PDF\n- LangChain - Text splitter, document creation\n- HuggingFace - Embeddings\n- Weaviate - Vector Database\n\n\n \"Open\n", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LangChain/LangChain_Vector_Search_on_PDF.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LangChain/LangChain_Vector_Search_on_PDF.ipynb", "imports": ["langchain", "langchain", "PyPDF2", "PyPDF2", "weaviate", "weaviate", "os", "naas", "io", "requests", "langchain.text_splitter.CharacterTextSplitter", "langchain.embeddings.HuggingFaceEmbeddings", "langchain.vectorstores.Weaviate"], "image_url": ""}, {"objectID": "fe3d8478a7a0ec3a8547714e3830c73fe246cb33bbe5bafbf00d39bee94ce2e9", "tool": "LeFigaro", "notebook": "House Price analysis", "action": "", "tags": ["#lefigaro", "#investors", "#immobilier", "#markdown", "#graph", "#chart", "#analytics"], "author": "Mahanamana Andriamiharisoa", "author_url": "https://www.linkedin.com/in/mahanamana/", "updated_at": "2023-04-12", "created_at": "2022-07-08", "description": "This notebook provides an analysis of house prices in France using data from LeFigaro.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LeFigaro/LeFigaro_House_Price_analysis.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LeFigaro/LeFigaro_House_Price_analysis.ipynb", "imports": ["requests", "bs4.BeautifulSoup", "pandas", "numpy", "matplotlib.pyplot", "plotly.express", "naas"], "image_url": ""}, {"objectID": "479b87603a0cbdf9ac2a26af7a59038d199f9ac114b46261f5550b23ab40220d", "tool": "LinkedIn Sales Navigator", "notebook": "Extract Leads List from URL", "action": "", "tags": ["#linkedin", "#salesnavigator", "#extract", "#leads"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-27", "description": "This notebook will show how to extract a list of leads from a URL using LinkedIn Sales Navigator.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn%20Sales%20Navigator/LinkedIn_Sales_Navigator_Extract_Leads_List_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn%20Sales%20Navigator/LinkedIn_Sales_Navigator_Extract_Leads_List_from_URL.ipynb", "imports": ["naas_drivers.linkedin_salesnavigator", "naas"], "image_url": ""}, {"objectID": "1b0477f9d8333372b2c07f480a0d743097d611eff7c7a7600095ae3b813cbded", "tool": "LinkedIn Sales Navigator", "notebook": "Send Leads to Spreadsheet", "action": "", "tags": ["#linkedin", "#salesnavigator", "#extract", "#leads", "#gsheet", "#leadgen"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-02", "description": "This notebook send a list of leads generated by LinkedIn Sales Navigator to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn%20Sales%20Navigator/LinkedIn_Sales_Navigator_Send_Leads_to_Spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn%20Sales%20Navigator/LinkedIn_Sales_Navigator_Send_Leads_to_Spreadsheet.ipynb", "imports": ["naas_drivers.linkedin_salesnavigator", "naas_drivers.gsheet", "naas"], "image_url": ""}, {"objectID": "9f5596b26533283a108fba2a2dfd62794659f196cef87ccc1649802a6a85844d", "tool": "LinkedIn", "notebook": "Accept all invitations and send first message", "action": "", "tags": ["#linkedin", "#content", "#operations", "#automation", "#invitation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-05-29", "created_at": "2022-04-05", "description": "This notebook helps you quickly and easily accept all LinkedIn invitations and send a personalized introductory message to each new connection.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Accept_all_invitations_and_send_first_message.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Accept_all_invitations_and_send_first_message.ipynb", "imports": ["naas", "naas_drivers.linkedin", "pandas"], "image_url": ""}, {"objectID": "e45e2cd2d424c1f1399552df2148f8494e84c0aa7f98f1ab105f7d4cdd0e8a7d", "tool": "LinkedIn", "notebook": "Accept invitation received", "action": "", "tags": ["#linkedin", "#content", "#operations", "#snippet", "#invitation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-05-29", "created_at": "2022-04-05", "description": "This notebook allows you to accept invitations to connect on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Accept_invitation_received.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Accept_invitation_received.ipynb", "imports": ["naas_drivers.linkedin", "pandas"], "image_url": ""}, {"objectID": "8ba17ce043515c04a2f3081afbd6904e272b708e06388b566b4a286a2fd7d785", "tool": "LinkedIn", "notebook": "Chat about my latest profile posts", "action": "", "tags": ["#linkedin", "#profile", "#post", "#stats", "#naas_drivers", "#content", "#automation", "#csv"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-07-26", "created_at": "2023-07-24", "description": "This notebook enables you to converse inside MyChatGPT about your most recent LinkedIn posts using a CSV file stored in your Naas Lab and a JSON plugin asset. Data is updated and replaced with each run.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Chat_about_my_latest_profile_posts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Chat_about_my_latest_profile_posts.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas", "os", "json", "wordcloud.WordCloud", "wordcloud.WordCloud", "matplotlib.pyplot", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b6b615ac66034a7ebfa52b341d1849c0352ec471108d940809c2477e5fa83f15", "tool": "LinkedIn", "notebook": "Create Post", "action": "", "tags": ["#linkedin", "#create", "#api", "#post", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2023-03-20", "description": "This notebook creates a post using Linkedin API and Supabase.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Create_Post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Create_Post.ipynb", "imports": ["os", "supabase.create_client, Client", "supabase.create_client, Client", "naas", "requests", "json", "pprint.pprint"], "image_url": ""}, {"objectID": "78ec6637e7d863b7e458ba7b49172446db1057cb307c1160da7391c0fb19f54c", "tool": "LinkedIn", "notebook": "Create posts metrics dashboard", "action": "", "tags": ["#linkedin", "#dashboard", "#plotly", "#dash", "#naas", "#asset", "#automation", "#analytics"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-09-06", "description": "This notebook provides a dashboard to track the performance metrics of posts created on LinkedIn. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.
", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Create_posts_metrics_dashboard.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Create_posts_metrics_dashboard.ipynb", "imports": ["os", "os.environ", "pandas", "naas", "datetime.datetime", "plotly.graph_objects", "plotly.express", "plotly.subplots.make_subplots", "dash", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "dash.html, dcc, Input, Output, State", "dash_bootstrap_components._components.Container.Container", "dash.exceptions.PreventUpdate"], "image_url": ""}, {"objectID": "11b2c07be26f4a540e850f376dd2cfffa6b41699fbb48e33fd0a5eecd9155e20", "tool": "LinkedIn", "notebook": "Extract content world cloud", "action": "", "tags": ["#linkedin", "#worldcloud", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook provides a way to extract content from LinkedIn and visualize it in a word cloud. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Extract_content_world_cloud.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Extract_content_world_cloud.ipynb", "imports": ["wordcloud.WordCloud", "wordcloud.WordCloud", "matplotlib.pyplot", "pandas"], "image_url": ""}, {"objectID": "f16e388f3fc8807c45263b666b7844f2b411a774e745b508c92314292953a44a", "tool": "LinkedIn", "notebook": "Follow company followers", "action": "", "tags": ["#linkedin", "#company", "#followers", "#naas_drivers", "#analytics", "#automation", "#csv", "#html", "#image", "#content", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-04-22", "description": "This notebook allows you to track and follow the followers of a company on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_company_followers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_company_followers.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "7d69ccdb7722e129fb596d4ac313a428ceb333e3b508039dd77e8d57002d0530", "tool": "LinkedIn", "notebook": "Follow connections from profile", "action": "", "tags": ["#linkedin", "#network", "#connections", "#naas_drivers", "#analytics", "#csv", "#html", "#image", "#content", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-11", "description": "This notebook allows you to follow connections from a LinkedIn profile to build your network.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_connections_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_connections_from_profile.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "0c1887da9a6a5b0e6944b92de5b8d5fe6809cead583534b47781b405fc1ad407", "tool": "LinkedIn", "notebook": "Follow content comments monthly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to track and analyze the comments on your LinkedIn content each month. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_comments_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_comments_monthly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "3add0154c45189d53227375a9eb51eaf962e8d47a92e629fcfdfb5f359658c4c", "tool": "LinkedIn", "notebook": "Follow content comments weekly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to track and follow comments on content posted on LinkedIn on a weekly basis. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_comments_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_comments_weekly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "7bd1a5021d27c602388c8453a5e295b65f4ce4e34ebeb32de85ec94654b656d9", "tool": "LinkedIn", "notebook": "Follow content engagements monthly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook provides a monthly overview of content engagements on LinkedIn. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_engagements_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_engagements_monthly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "5ad7f9c5d30b05a69996fc91685fc7039d55107f55b3b76bb9a640fefdf96d05", "tool": "LinkedIn", "notebook": "Follow content engagements weekly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook helps you track and analyze your weekly content engagements on LinkedIn. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_engagements_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_engagements_weekly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "cc1b4c23ccb3f6694fab05812f8888d458df1076bb27bd5d1406a42e8865b339", "tool": "LinkedIn", "notebook": "Follow content frequency", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows users to track how often they post content on LinkedIn and follow the frequency of their posts. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_frequency.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_frequency.ipynb", "imports": ["naas_drivers.linkedin", "os.path", "naas", "pandas", "datetime.datetime", "plotly.graph_objects", "plotly.subplots.make_subplots"], "image_url": ""}, {"objectID": "86d43a87776a1959277b4f7cbfea2d6a8c9cd83dc103e7ea40196db6c68366e6", "tool": "LinkedIn", "notebook": "Follow content likes monthly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to track and follow content on LinkedIn on a monthly basis. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_likes_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_likes_monthly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "5d645f65d3876fcb8f68ec55b61551bc8fcc9dc16ce4393003cb9355d28022f7", "tool": "LinkedIn", "notebook": "Follow content likes weekly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to keep track of the content you like on LinkedIn and follow it on a weekly basis. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_likes_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_likes_weekly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "09c380b66d03f35f056daeb6875ab67d012a9c943260b272f60ced069ad5998d", "tool": "LinkedIn", "notebook": "Follow content published by weekdays by months", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-08-04", "description": "This notebook allows you to track and follow content published on LinkedIn by day of the week and month. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_published_by_weekdays_by_months.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_published_by_weekdays_by_months.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects", "pandas.tseries.offsets.MonthEnd", "calendar", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "12fcfa952a1daa79c27b82ab8f6061ca506e6b7542ebfee9a844df936c90d21d", "tool": "LinkedIn", "notebook": "Follow content published monthly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to keep track of content published on LinkedIn each month. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_published_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_published_monthly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "eac2762bc29e79db13a5652221c17ebee0b37012a8b88da0af2890c432339322", "tool": "LinkedIn", "notebook": "Follow content published weekly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to stay up-to-date with the latest content published on LinkedIn each week. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_published_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_published_weekly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "435a57172667176064f133da7888849c0f1209e8c22bf789fd0e8ab470c3952a", "tool": "LinkedIn", "notebook": "Follow content views by weekdays by hours", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-08-04", "description": "This notebook provides an analysis of the views of content on LinkedIn by day of the week and hour of the day. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_views_by_weekdays_by_hours.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_views_by_weekdays_by_hours.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects", "pandas.tseries.offsets.MonthEnd", "calendar", "dateutil.relativedelta.relativedelta"], "image_url": ""}, {"objectID": "c480f026f88fcb2491576b76e6e0e861d709dcbed902fea6ab5407a3394358ac", "tool": "LinkedIn", "notebook": "Follow content views monthly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook provides a monthly overview of the content you are following on LinkedIn. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_views_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_views_monthly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "c4ef3bf53e18ed4570a193932e08ef3214f5a9ddb23e526db77550e66bc7963c", "tool": "LinkedIn", "notebook": "Follow content views weekly", "action": "", "tags": ["#linkedin", "#html", "#plotly", "#csv", "#image", "#content", "#analytics", "#dependency"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-30", "description": "This notebook allows you to track and analyze your weekly content views on LinkedIn. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_content_views_weekly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_content_views_weekly.ipynb", "imports": ["naas", "pandas", "datetime.datetime", "plotly.graph_objects"], "image_url": ""}, {"objectID": "c316be559091eb40bdec9c2b23ad51baf7e859b730cd2fbf93b6b0519b3012a7", "tool": "LinkedIn", "notebook": "Follow number of connections monthly", "action": "", "tags": ["#linkedin", "#network", "#connections", "#naas_drivers", "#analytics", "#csv", "#html", "#image", "#content", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-05-17", "description": "This notebook tracks the number of connections made on LinkedIn each month.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Follow_number_of_connections_monthly.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Follow_number_of_connections_monthly.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas", "plotly.graph_objects", "plotly.subplots.make_subplots"], "image_url": ""}, {"objectID": "90e6b184ce0fb7a0025c4af64f6ced3cc38deae800bfed2b23bf3f696371c259", "tool": "LinkedIn", "notebook": "Generate leads from posts", "action": "", "tags": ["#linkedin", "#post", "#comments", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-05-29", "created_at": "2022-01-09", "description": "This notebook provides a guide to leveraging LinkedIn posts to generate leads for your business.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Generate_leads_from_posts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Generate_leads_from_posts.ipynb", "imports": ["naas_drivers.linkedin, hubspot", "pandas", "numpy", "naas", "datetime.datetime, timedelta", "requests", "json"], "image_url": ""}, {"objectID": "38e3a7391f8093e9d1678cb2eb88f6606c087cf81d5dabc31334567fb05b7b55", "tool": "LinkedIn", "notebook": "Get age and gender from profile picture", "action": "", "tags": ["#linkedin", "#machinelearning", "#profile", "#identity", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Nikolaj Groeneweg", "author_url": "https://www.linkedin.com/in/njgroene/", "updated_at": "2023-05-29", "created_at": "2022-06-13", "description": "This notebook estimates a person's age and gender based on their LinkedIn profile picture.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_age_and_gender_from_profile_picture.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_age_and_gender_from_profile_picture.ipynb", "imports": ["naas_drivers.linkedin", "urllib", "naas", "PIL.Image", "pandas", "numpy", "torch", "torch.nn", "torchvision", "torchvision.datasets, models, transforms", "torchvision", "torchvision.datasets, models, transforms", "torch_mtcnn.detect_faces", "torch_mtcnn.show_bboxes", "torch_mtcnn.detect_faces", "torch_mtcnn.show_bboxes"], "image_url": ""}, {"objectID": "1f9e57be7c17bbd6f7630dec0d4bf80fe2e2184897da9ef6eb74849aa2350da2", "tool": "LinkedIn", "notebook": "Get comments from post", "action": "", "tags": ["#linkedin", "#post", "#comments", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-26", "created_at": "2021-06-17", "description": "\"This notebook is designed to extract comments from a specific LinkedIn post and organize the data into a structured format. It generates a DataFrame with various details about each comment and the user who posted it.\n\nThe DataFrame includes the following columns:\n\n- `PROFILE_ID`: The unique identifier associated with the LinkedIn profile of the user who posted the comment.\n- `PROFILE_URL`: The URL leading to the LinkedIn profile of the user who posted the comment.\n- `PUBLIC_ID`: The public identifier visible in the URL of the user's LinkedIn profile.\n- `FIRSTNAME`: The first name of the user who posted the comment.\n- `LASTNAME`: The last name of the user who posted the comment.\n- `FULLNAME`: The full name of the user who posted the comment.\n- `OCCUPATION`: The professional role or job title of the user who posted the comment.\n- `PROFILE_PICTURE`: The URL of the user's LinkedIn profile picture.\n- `BACKGROUND_PICTURE`: The URL of the user's LinkedIn background picture.\n- `PROFILE_TYPE`: The type of LinkedIn profile (e.g., individual, company).\n- `TEXT`: The actual text of the comment posted by the user.\n- `CREATED_TIME`: The timestamp indicating when the comment was posted.\n- `LANGUAGE`: The language in which the comment was written.\n- `DISTANCE`: The degree of connection between the user who posted the comment and the profile viewing the post (e.g., 1st-degree connection, 2nd-degree connection).\n- `COMMENTS`: The number of comments on the user's comment.\n- `LIKES`: The number of likes on the user's comment.\n- `POST_URL`: The URL of the LinkedIn post where the comment was made.\n- `DATE_EXTRACT`: The timestamp indicating when the comment data was extracted.\n\nThe notebook is a useful tool for social media analysis and can help in understanding user engagement on LinkedIn posts.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_comments_from_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_comments_from_post.ipynb", "imports": ["naas", "naas_drivers.linkedin"], "image_url": ""}, {"objectID": "eb94b13f89163a7980a2cf632af1e207573c35271920d52121659af1d90e0aa5", "tool": "LinkedIn", "notebook": "Get company followers", "action": "", "tags": ["#linkedin", "#company", "#followers", "#naas_drivers", "#automation", "#csv", "#content"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-04-22", "description": "This templates will get all followers from your LinkedIn company and save it into a CSV.

\n**Available columns :**\n- FIRSTNAME : First name\n- LASTNAME : Last name\n- OCCUPATION : Text below the name in the profile page\n- PROFILE_PICTURE : Profile picture URL\n- PROFILE_URL : Profile URL\n- PROFILE_ID : LinkedIn profile id\n- PUBLIC_ID : LinkedIn public profile id\n- FOLLOWED_AT : Date of following company\n- DISTANCE : Distance between your profile", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_company_followers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_company_followers.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "naas"], "image_url": ""}, {"objectID": "2ed63b3d62d9a60d7600c9811fcb83034ec2ccf8fcebe4d04a0b84c93e7259bd", "tool": "LinkedIn", "notebook": "Get company posts stats", "action": "", "tags": ["#linkedin", "#company", "#post", "#stats", "#naas_drivers", "#content", "#automation", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-23", "created_at": "2022-06-30", "description": "This notebook fetches your company's post statistics from LinkedIn and stores them in a CSV file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_company_posts_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_company_posts_stats.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "0a0c8e7351a55631596ec7e7867df20d01ab86dacc006501336aeefc3b9ec15c", "tool": "LinkedIn", "notebook": "Get connections from network", "action": "", "tags": ["#linkedin", "#network", "#connections", "#naas_drivers", "#analytics", "#csv", "#html", "#image", "#content", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-26", "created_at": "2022-03-03", "description": "This notebook extracts your connections from your LinkedIn profile. It generates a dataframe that includes the following fields: the first and last name of the connection ('FIRSTNAME', 'LASTNAME'), the description present below the name on the profile page ('OCCUPATION'), the date when the connection was made ('CREATED_AT'), the URL of the profile ('PROFILE_URL'), the URL of the profile picture ('PROFILE_PICTURE'), the LinkedIn profile id of the connection ('PROFILE_ID'), and the LinkedIn public profile id of the connection ('PUBLIC_ID').\"", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_connections_from_network.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_connections_from_network.ipynb", "imports": ["naas_drivers.linkedin", "naas", "os"], "image_url": ""}, {"objectID": "3039c637364b8851d8723243b9ac3792d374d33e6e4aa17d7912f7987a3c9fdf", "tool": "LinkedIn", "notebook": "Get contact from profile", "action": "", "tags": ["#linkedin", "#profile", "#contact", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook allows you to extract contact information from LinkedIn profiles.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_contact_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_contact_from_profile.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "dba7ad6aa93d52b27f68ac38681d27ba843f3eecf2c50d6f79b56cf7a744a87d", "tool": "LinkedIn", "notebook": "Get all your conversations", "action": "", "tags": ["#linkedin", "#messaging", "#conversations", "#sales", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-22", "created_at": "2021-06-18", "description": "This notebook get all your conversations from LinkedIn with the last message sent.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_conversations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_conversations.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "ba5a15c282b5e9189b71ddc1dafa3d17bb78e85e011834fece907fad38a80576", "tool": "LinkedIn", "notebook": "Get followers from network", "action": "", "tags": ["#linkedin", "#network", "#followers", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook provides a guide to gaining followers on LinkedIn by leveraging your existing network.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_followers_from_network.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_followers_from_network.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "46d52b8081ec592286caf79ad464265e2ea170f657d869b90154afebc172fdaa", "tool": "LinkedIn", "notebook": "Get guests from event", "action": "", "tags": ["#linkedin", "#event", "#guests", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook provides a guide to using LinkedIn to connect with attendees of an event.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_guests_from_event.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_guests_from_event.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "28a47ab167568046a591d40544558a84e3385a22f3d151363bc6216f8a0b0159", "tool": "LinkedIn", "notebook": "Get identity from profile", "action": "", "tags": ["#linkedin", "#profile", "#identity", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook helps you extract identity information from LinkedIn profiles.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_identity_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_identity_from_profile.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "7e64f993d24b11cfe449c8b54a0b60cc51fdabf34ef7ecab7303e3f1cf2b46e4", "tool": "LinkedIn", "notebook": "Get info from company", "action": "", "tags": ["#linkedin", "#company", "#info", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-21", "description": "This notebook provides a way to access and analyze data from LinkedIn to gain insights about companies.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_info_from_company.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_info_from_company.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "e810951640a697452790d8df52dcefc6fe0b153852fdbc64b02f6d9d408908dd", "tool": "LinkedIn", "notebook": "Get invitations received", "action": "", "tags": ["#linkedin", "#content", "#operations", "#snippet", "#invitation", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-05-29", "created_at": "2022-04-05", "description": "This notebook provides an overview of invitations received on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_invitations_received.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_invitations_received.ipynb", "imports": ["naas_drivers.linkedin", "pandas"], "image_url": ""}, {"objectID": "0cb2069ad12899638d06c4e58ca80fe82859e4a8b1129cd506a0f5d9cd3f2219", "tool": "LinkedIn", "notebook": "Get invitations sent", "action": "", "tags": ["#linkedin", "#content", "#operations", "#snippet", "#invitation", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-05-29", "created_at": "2022-04-07", "description": "This notebook helps you to send invitations to connect on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_invitations_sent.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_invitations_sent.ipynb", "imports": ["naas_drivers.linkedin", "pandas"], "image_url": ""}, {"objectID": "f4b40da212ddcec161cf5ee03acc8fc0ef067e2d7a6994aac0f9baa88261a3aa", "tool": "LinkedIn", "notebook": "Get likes from post", "action": "", "tags": ["#linkedin", "#post", "#likes", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-26", "created_at": "2021-06-17", "description": "\"This notebook is engineered to compile a list of profiles that have liked a specific LinkedIn post, and it organizes the data into a structured and easily digestible format. It creates a DataFrame that encompasses the following columns:\n\n- `PROFILE_ID`: The unique identifier for each LinkedIn profile.\n- `PROFILE_URL`: The URL of the individual's LinkedIn profile.\n- `PUBLIC_ID`: The public identifier visible in the URL of the user's LinkedIn profile.\n- `FIRSTNAME`: The first name of the LinkedIn user.\n- `LASTNAME`: The last name of the LinkedIn user.\n- `FULLNAME`: The full name of the LinkedIn user.\n- `OCCUPATION`: The professional title or job role of the LinkedIn user.\n- `PROFILE_PICTURE`: The URL of the LinkedIn user's profile picture.\n- `BACKGROUND_PICTURE`: The URL of the LinkedIn user's background picture.\n- `PROFILE_TYPE`: The type of LinkedIn profile (e.g., individual, company).\n- `REACTION_TYPE`: The type of reaction (like, love, insightful, etc.) the user has given to the post.\n- `POST_URL`: The URL of the LinkedIn post that received the reaction.\n- `DATE_EXTRACT`: The timestamp of when the reaction data was extracted.\n\nThis notebook serves as a valuable tool for social media analysis, providing insights into user engagement on LinkedIn posts.\"", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_likes_from_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_likes_from_post.ipynb", "imports": ["naas", "naas_drivers.linkedin"], "image_url": ""}, {"objectID": "fcea0fc5a4922e0261e90f804fc6bfe4af88a3af23e01708e25ad9196bc4e26e", "tool": "LinkedIn", "notebook": "Get messages from conversation", "action": "", "tags": ["#linkedin", "#message", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook allows you to access all messages from a LinkedIn conversation using the conversation URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_messages_from_conversation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_messages_from_conversation.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "40b7886be679eaf7d0c1b0d2f739297554c4a26f467bd3cabe692ae7e200d492", "tool": "LinkedIn", "notebook": "Get network from profile", "action": "", "tags": ["#linkedin", "#profile", "#network", "#followers", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook helps you to quickly and easily build your professional network on LinkedIn by extracting contacts from your profile.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_network_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_network_from_profile.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "772920fe39026c5b2f7ac54cbe59920fd5190a8a331bbdca43cb6d62412e6dfc", "tool": "LinkedIn", "notebook": "Get polls from post", "action": "", "tags": ["#linkedin", "#post", "#polls", "#naas_drivers", "#content", "#analytics", "#image", "#html", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-01-27", "description": "This notebook allows users to get poll results from their LinkedIn posts.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_polls_from_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_polls_from_post.ipynb", "imports": ["naas_drivers.linkedin", "plotly.express"], "image_url": ""}, {"objectID": "c3bbc0a688cb73907fda0ee047c06ac4c28ead5e92bb3c9be20f01a199b9d9c6", "tool": "LinkedIn", "notebook": "Get posts engagements", "action": "", "tags": ["#linkedin", "#posts", "#interactions", "#metrics", "#analytics", "#automation", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-08-04", "description": "This notebook provides insights into how to increase engagement on LinkedIn posts. To run this notebook, you must have already run LinkedIn_Get_profile_posts_stats.ipynb or LinkedIn_Get_company_posts_stats.ipynb to get your post stats in CSV.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_posts_engagements.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_posts_engagements.ipynb", "imports": ["naas", "pandas", "datetime.datetime"], "image_url": ""}, {"objectID": "1da4b1cd630239550bc3c7fab1f27f151766aaec25a552b97308ba1751c8ee8b", "tool": "LinkedIn", "notebook": "Get profile information", "action": "", "tags": ["#linkedin", "#profile", "#resume", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-10-06", "description": "This notebook allows you to access and analyze profile information from LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_profile_information.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_profile_information.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "ff638a6ff20341b8d9c703bd58fb5088b4bfd7df4f07be972ae77d964ad9eb84", "tool": "LinkedIn", "notebook": "Get profile posts stats", "action": "", "tags": ["#linkedin", "#profile", "#post", "#stats", "#naas_drivers", "#content", "#automation", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-23", "created_at": "2022-06-30", "description": "This notebook fetches your profile's post statistics from LinkedIn and stores them in a CSV file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_profile_posts_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_profile_posts_stats.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "8b7569435004cb9dd156456bcf7d1d807f5b4fc77c072b46ebc223f9b671ad18", "tool": "LinkedIn", "notebook": "Get resume from profile", "action": "", "tags": ["#linkedin", "#profile", "#resume", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-10-14", "description": "This notebook allows users to extract resumes from LinkedIn profiles.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_resume_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_resume_from_profile.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "14515451ee7c352417fc76bfd5acc3163dd04872ac20feb2a0a18fe0bda7db51", "tool": "LinkedIn", "notebook": "Get sentiment analysis from post comments", "action": "", "tags": ["#linkedin", "#sentimentanalysis", "#api", "#python", "#nlp", "#textanalysis"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-10", "created_at": "2023-08-10", "description": "This notebook provides a sentiment analysis of comments from LinkedIn post. This is useful to understand the sentiment of their posts and the reactions of their followers. The five adjectives that will be used to analyze comment sentiment on LinkedIn are the following:\n- \"Praise\" - This is for highly positive comments that express admiration or approval. These comments often include compliments or positive feedback.\n- \"Supportive\" - This is for positive comments that may not necessarily contain high praise but show agreement, support, or encouragement.\n- \"Neutral\" - This is for comments that are neither positive nor negative, often factual statements or questions without any clear positive or negative connotations.\n- \"Constructive\" - This is for comments that may seem negative but are intended to provide constructive feedback or suggest improvements.\n- \"Disapproving\" - This is for comments that express disagreement, criticism, or negative feedback.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_sentiment_analysis_from_post_comments.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_sentiment_analysis_from_post_comments.ipynb", "imports": ["naas_drivers.linkedin", "openai", "openai", "pandas", "datetime.datetime", "naas", "plotly.express"], "image_url": ""}, {"objectID": "484bd5a79481d84712cb9422e5af9b6dead06ecd0eb1fb6a1acc01dc13006e29", "tool": "LinkedIn", "notebook": "Get sentiment emotion irony offensiveness from comments", "action": "", "tags": ["#linkedin", "#nlp", "#transformers", "#ai", "#post", "#comments", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Nikolaj Groeneweg", "author_url": "https://www.linkedin.com/in/njgroene/", "updated_at": "2023-05-29", "created_at": "2022-06-20", "description": "This notebook gets all the comments on a LinkedIn post, and performs sentiment analysis, emotion classification and some semantic analysis on them. \nIt classifies each comment and returns the following information:\n\n- is the comment positive, negative or neutral?\n- is the comment ironic?\n- is the comment offensive?\n- does the comment express joy, optimism, anger or sadness?", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_sentiment_emotion_irony_offensiveness_from_comments.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_sentiment_emotion_irony_offensiveness_from_comments.ipynb", "imports": ["naas_drivers.linkedin", "transformers.pipeline", "transformers.AutoModelForSequenceClassification", "transformers.TFAutoModelForSequenceClassification", "transformers.AutoTokenizer", "numpy", "scipy.special.softmax", "csv", "urllib.request", "os.path", "naas"], "image_url": ""}, {"objectID": "e60798c0bb96ef5ed0f5bbc38d36550eb2ca05d7a8db31333acbb4e0829ed36d", "tool": "LinkedIn", "notebook": "Get stats from post", "action": "", "tags": ["#linkedin", "#post", "#stats", "#naas_drivers", "#snippet", "#content", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook provides a way to track and analyze the performance of posts on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Get_stats_from_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Get_stats_from_post.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "454ba60f826a23c1da2e7a14200ba258bc48c26ab0b4e2546278884c5fa1967c", "tool": "LinkedIn", "notebook": "Ignore invitation received", "action": "", "tags": ["#linkedin", "#content", "#operations", "#snippet", "#invitation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-05-29", "created_at": "2022-04-05", "description": "This notebook is for tracking invitations received on LinkedIn that have been ignored.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Ignore_invitation_received.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Ignore_invitation_received.ipynb", "imports": ["naas_drivers.linkedin", "pandas"], "image_url": ""}, {"objectID": "ffa5a37b784ef43241ffda33902293d423ba8d87869bc8b3e82b3420788da443", "tool": "LinkedIn", "notebook": "Maintain company posts stats database", "action": "", "tags": ["#linkedin", "#company", "#post", "#stats", "#naas_drivers", "#content", "#automation", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-23", "created_at": "2022-06-30", "description": "This notebook fetches your company's post statistics from LinkedIn and stores them in a CSV file. It then updates a select number of entries to track the progress of your statistics over time. This method helps to minimize the number of requests made to the LinkedIn API, reducing the risk of being banned due to excessive usage. Additionally, this CSV database can be conveniently reused in other processes, such as retrieving interactions from post URLs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Maintain_company_posts_stats_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Maintain_company_posts_stats_database.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas"], "image_url": ""}, {"objectID": "987989807dcbdb028cbd911edaf7b3f3365602bccc22964ebd83fb60442bba77", "tool": "LinkedIn", "notebook": "Maintain profile posts stats database", "action": "", "tags": ["#linkedin", "#profile", "#post", "#stats", "#naas_drivers", "#content", "#automation", "#csv"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-23", "created_at": "2023-08-23", "description": "This notebook fetches your profile's post statistics from LinkedIn and stores them in a CSV file. It then updates a select number of entries to track the progress of your statistics over time. This method helps to minimize the number of requests made to the LinkedIn API, reducing the risk of being banned due to excessive usage. Additionally, this CSV database can be conveniently reused in other processes, such as retrieving interactions from post URLs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Maintain_profile_posts_stats_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Maintain_profile_posts_stats_database.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas"], "image_url": ""}, {"objectID": "cf79c294525d2cb1495b9d0a19e50676f1eadac2aa2fa738fe2be626f61d807d", "tool": "LinkedIn", "notebook": "Send comments from post to gsheet", "action": "", "tags": ["#linkedin", "#post", "#comments", "#gsheet", "#naas_drivers", "#content", "#snippet", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-17", "description": "This notebook allows users to automatically send comments from a LinkedIn post to a Google Sheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_comments_from_post_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_comments_from_post_to_gsheet.ipynb", "imports": ["naas_drivers.linkedin, gsheet", "random", "time", "pandas", "datetime.datetime"], "image_url": ""}, {"objectID": "0b5da370401973d25b59a20591783fd711110252b8b455cda4e34c1c0be273c1", "tool": "LinkedIn", "notebook": "Send company followers to Google Sheets", "action": "", "tags": ["#linkedin", "#company", "#followers", "#naas_drivers", "#automation", "#googlesheets", "#content"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-04-22", "description": "This notebook allows users to export their LinkedIn company followers to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_company_followers_to_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_company_followers_to_Google_Sheets.ipynb", "imports": ["naas_drivers.linkedin, gsheet", "pandas", "naas"], "image_url": ""}, {"objectID": "197e953f50f2bd29e259cadd4568587ab0f2ee2cff1f47ed233a69253f419c4f", "tool": "LinkedIn", "notebook": "Send connections from network to gsheet", "action": "", "tags": ["#linkedin", "#network", "#connections", "#naas_drivers", "#csv", "#automation", "#content", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-17", "description": "This notebook allows users to export their LinkedIn connections to a Google Sheet for easy organization and tracking.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_connections_from_network_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_connections_from_network_to_gsheet.ipynb", "imports": ["naas_drivers.linkedin, gsheet", "naas", "pandas"], "image_url": ""}, {"objectID": "87b880ff840a772458fb40959783a6f1c58c8ade4b163685888a411f3096a25e", "tool": "LinkedIn", "notebook": "Send conversation to HubSpot communication", "action": "", "tags": ["#linkedin", "#message", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook send a LinkedIn conversation with all messages to a contact HubSpot communication.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_conversation_to_HubSpot_communication.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_conversation_to_HubSpot_communication.ipynb", "imports": ["naas_drivers.linkedin", "naas", "datetime.datetime, timezone", "requests", "pandas"], "image_url": ""}, {"objectID": "085902bb7fa3c3f0814ec7b5309206de2c60937f383c1765d58bd70581f920df", "tool": "LinkedIn", "notebook": "Send event invitations post engagements", "action": "", "tags": ["#linkedin", "#events", "#invitations", "#naas_drivers", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-07-08", "description": "This notebook allows users to send event invitations and post engagements on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_event_invitations_post_engagements.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_event_invitations_post_engagements.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "naas", "requests", "time"], "image_url": ""}, {"objectID": "8f2f7ab311c3b0058af4aa3dfb216fe0e7f1a9f78d14a2f8bff4661f5f46e89c", "tool": "LinkedIn", "notebook": "Send followers demographic data to a Google Sheets spreadsheet", "action": "", "tags": ["#\"linkedin", "#googlesheets", "#gsheet", "#data", "#naas_drivers", "#demographics", "#content", "#snippet"], "author": "Asif Syed", "author_url": "https://www.linkedin.com/in/asifsyd/", "updated_at": "2023-05-29", "created_at": "2022-07-11", "description": "This notebook allows users to easily export demographic data about their LinkedIn followers to a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_followers_demographic_data_to_a_Google_Sheets_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_followers_demographic_data_to_a_Google_Sheets_spreadsheet.ipynb", "imports": ["naas_drivers.gsheet", "naas_drivers.linkedin", "pandas", "numpy", "naas"], "image_url": ""}, {"objectID": "49cfbd24cd629b49f5c61b1411be50d20278f2357b7474b057e6a90ea78e77a1", "tool": "LinkedIn", "notebook": "Send interactions from post URL to HubSpot notes", "action": "", "tags": ["#linkedin", "#hubspot", "#openai", "#interactions", "#post", "#url", "#send", "#notes"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-16", "created_at": "2023-08-16", "description": "This notebook automates the process of sending people interactions (like or comment) on a LinkedIn post URL to a contact notes in HubSpot. If a person doesn't already exist in HubSpot, a new contact is created, complete with their first name, last name, occupation, and LinkedIn URL. We also use a prompt to categorize people by ICP, enriching the HubSpot contact information in the process. This tool proves invaluable for tracking and scoring targets acquired through your LinkedIn post campaigns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_interactions_from_post_URL_to_HubSpot_notes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_interactions_from_post_URL_to_HubSpot_notes.ipynb", "imports": ["naas", "naas_drivers.linkedin, hubspot", "pandas", "openai", "requests", "datetime.datetime, timezone", "difflib.SequenceMatcher"], "image_url": ""}, {"objectID": "b6b084bb3f63093ac35b2d2ddee1537e97e5aa2c5f288f5f1b68baf1871c3eae", "tool": "LinkedIn", "notebook": "Send invitation to company followers", "action": "", "tags": ["#linkedin", "#company", "#followers", "#invitations", "#naas_drivers", "#automation", "#content"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-04-22", "description": "This notebook allows users to send invitations to their company's followers on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_invitation_to_company_followers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_invitation_to_company_followers.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.datetime", "naas", "plotly.graph_objects", "os"], "image_url": ""}, {"objectID": "37c5863ae1a3514167b091d00832094a7c8a267ed37a464de412872cb19c50a6", "tool": "LinkedIn", "notebook": "Send invitation to profile", "action": "", "tags": ["#linkedin", "#invitation", "#naas_drivers", "#content", "#snippet", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-18", "description": "This notebook allows users to send invitations to connect on LinkedIn to other profiles.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_invitation_to_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_invitation_to_profile.ipynb", "imports": ["naas_drivers.linkedin", "naas"], "image_url": ""}, {"objectID": "f0fba0385a33845e76e5bcd0c3a61e1c1b6574dcbec369b6f3cc81f4da639439", "tool": "LinkedIn", "notebook": "Send invitation to profile from post likes", "action": "", "tags": ["#linkedin", "#post", "#likes", "#naas_drivers", "#invitation", "#content", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-05-09", "description": "This notebook allows users to send LinkedIn invitations to profiles based on post likes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_invitation_to_profile_from_post_likes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_invitation_to_profile_from_post_likes.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "naas", "time"], "image_url": ""}, {"objectID": "65002d9da74692480adb03f4deaa5afef7d1561f0bbf6953e2d555eeb1e5837a", "tool": "LinkedIn", "notebook": "Send invitations to post commenters", "action": "", "tags": ["#linkedin", "#post", "#comments", "#invitations", "#connections", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Asif Syed", "author_url": "https://www.linkedin.com/in/asifsyd/", "updated_at": "2023-05-29", "created_at": "2022-07-17", "description": "This notebook allows users to quickly and easily send LinkedIn invitations to people who have commented on their posts.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_invitations_to_post_commenters.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_invitations_to_post_commenters.ipynb", "imports": ["naas_drivers.linkedin", "naas", "time"], "image_url": ""}, {"objectID": "e239ff8280fca693ad120ea9ada41a0df5571b5bb06a39f46f94b0e4a287fb1d", "tool": "LinkedIn", "notebook": "Send like to latest company or profile post", "action": "", "tags": ["#linkedin", "#socialmedia", "#like", "#company", "#profile", "#post", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-23", "created_at": "2023-08-23", "description": "This notebook will follow a company or a profile on LinkedIn and send like to its last posts. The post URL will be hashed using SHA and stored in a directory. This ensures that you don't engage with the same post multiple times.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_like_to_latest_company_or_profile_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_like_to_latest_company_or_profile_post.ipynb", "imports": ["naas_drivers.linkedin", "requests", "naas", "os", "hashlib", "hashlib"], "image_url": ""}, {"objectID": "c4a629732584538be3dec3d986b911d0f95f9932bdc32b9021fcc85778d0fc3a", "tool": "LinkedIn", "notebook": "Send like to latest company post", "action": "", "tags": ["#linkedin", "#socialmedia", "#like", "#company", "#post", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-23", "created_at": "2023-08-03", "description": "This notebook will follow a company on LinkedIn and send like to its last posts. The post URL will be hashed using SHA and stored in a directory. This ensures that you don't engage with the same post multiple times.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_like_to_latest_company_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_like_to_latest_company_post.ipynb", "imports": ["naas_drivers.linkedin", "requests", "naas", "os", "hashlib", "hashlib"], "image_url": ""}, {"objectID": "c85a3805e5e3536844c2b044e45753ced940951c9442c984d6704354a006eabb", "tool": "LinkedIn", "notebook": "Send like to latest profile post", "action": "", "tags": ["#linkedin", "#socialmedia", "#like", "#profile", "#post", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-03", "created_at": "2023-08-03", "description": "This notebook will follow a profile on LinkedIn and send like to its last posts. The post URL will be hashed using SHA and stored in a directory. This ensures that you don't engage with the same post multiple times.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_like_to_latest_profile_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_like_to_latest_profile_post.ipynb", "imports": ["naas_drivers.linkedin", "requests", "naas", "os", "hashlib", "hashlib"], "image_url": ""}, {"objectID": "e3eabf565c9cdb8e722c927522ecfe036376ee19a9d9b119f55a9c5440373e7e", "tool": "LinkedIn", "notebook": "Send like to post", "action": "", "tags": ["#linkedin", "#socialmedia", "#like", "#post", "#python", "#api"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-02", "created_at": "2023-08-02", "description": "This notebook will show how to send a like to a post published on LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_like_to_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_like_to_post.ipynb", "imports": ["naas_drivers.linkedin", "requests", "naas"], "image_url": ""}, {"objectID": "e94667908de603647180dc81387e1c2bcfd5d0ad5397217632d78647873462cf", "tool": "LinkedIn", "notebook": "Send likes from post to gsheet", "action": "", "tags": ["#linkedin", "#post", "#likes", "#gsheet", "#naas_drivers", "#content", "#snippet", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-17", "description": "This notebook automates the process of sending likes from LinkedIn posts to a Google Sheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_likes_from_post_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_likes_from_post_to_gsheet.ipynb", "imports": ["naas_drivers.linkedin, gsheet", "random", "time", "pandas", "datetime.datetime"], "image_url": ""}, {"objectID": "dd529268f794af9c567c6b89ebda05232650474d2045ffd7ba0800fa866f0e1f", "tool": "LinkedIn", "notebook": "Send message to new connections", "action": "", "tags": ["#linkedin", "#message", "#naas_drivers", "#content", "#snippet", "#text"], "author": "Asif Syed", "author_url": "https://www.linkedin.com/in/www.linkedin.com/in/asifsyd/", "updated_at": "2023-05-29", "created_at": "2022-07-06", "description": "This notebook allows users to quickly and easily send messages to their new LinkedIn connections.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_message_to_new_connections.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_message_to_new_connections.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "datetime.date", "naas"], "image_url": ""}, {"objectID": "a3372b8ea91440ad0889bc2f287878a924198874c1e5f00d36a07ebf360a73c2", "tool": "LinkedIn", "notebook": "Send message to profile", "action": "", "tags": ["#linkedin", "#message", "#naas_drivers", "#content", "#snippet", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2021-06-17", "description": "This notebook allows you to send a message to a LinkedIn profile.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_message_to_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_message_to_profile.ipynb", "imports": ["naas_drivers.linkedin"], "image_url": ""}, {"objectID": "a6bf8dc89284ce4e8c4233f645ff59cc200717ca056b7bd1e630a1ed463e9561", "tool": "LinkedIn", "notebook": "Send message to profile from post likes", "action": "", "tags": ["#linkedin", "#post", "#likes", "#naas_drivers", "#message", "#content", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-05-09", "description": "This notebook allows users to send messages to LinkedIn profiles from posts they have liked.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_message_to_profile_from_post_likes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_message_to_profile_from_post_likes.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "naas", "time"], "image_url": ""}, {"objectID": "527096707df50d4a343fc763b05e143cd4f346da125d7cd362696fae92628e05", "tool": "LinkedIn", "notebook": "Send posts feed to gsheet", "action": "", "tags": ["#linkedin", "#profile", "#post", "#stats", "#naas_drivers", "#automation", "#content", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-17", "description": "This notebook automates the process of sending LinkedIn posts to a Google Sheet for easy tracking and analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_posts_feed_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_posts_feed_to_gsheet.ipynb", "imports": ["naas_drivers.linkedin, gsheet", "naas", "pandas"], "image_url": ""}, {"objectID": "1d4114e63bdbb69e6e961f9140c1495707caf472877acb48e79061319b7c58c9", "tool": "LinkedIn", "notebook": "Send profile followers by email", "action": "", "tags": ["#linkedin", "#network", "#followers", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-02", "description": "This notebook allows users to send emails to their LinkedIn profile followers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_profile_followers_by_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_profile_followers_by_email.ipynb", "imports": ["naas_drivers.linkedin, emailbuilder", "naas", "pandas", "datetime.datetime"], "image_url": ""}, {"objectID": "c68448105b3374452761515cae1f4839a8efd59d518fca9b53bae22b2ee6c25c", "tool": "LinkedIn", "notebook": "Send weekly post engagement metrics by email", "action": "", "tags": ["#linkedin", "#tool", "#posts", "#engagement", "#metrics", "#analytics", "#automation", "#email", "#naas", "#notification"], "author": "Nikolaj Groeneweg", "author_url": "https://www.linkedin.com/in/njgroene/", "updated_at": "2023-05-29", "created_at": "2022-05-11", "description": "This notebook automates the process of sending weekly post engagement metrics from LinkedIn via email.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Send_weekly_post_engagement_metrics_by_email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Send_weekly_post_engagement_metrics_by_email.ipynb", "imports": ["naas_drivers.linkedin", "naas", "dateutil.parser.parse", "matplotlib.pyplot", "seaborn", "seaborn", "pandas", "datetime.datetime, date", "random", "time"], "image_url": ""}, {"objectID": "0826bb1d3a9f1983c0684a8cf33240c5bd6edeef1f65bbdfe89a7ced5138ee0c", "tool": "LinkedIn", "notebook": "Update metrics from company posts in Notion content calendar", "action": "", "tags": ["#linkedin", "#profile", "#post", "#feed", "#naas_drivers", "#notion", "#automation", "#analytics", "#naas", "#scheduler", "#content", "#plotly", "#html", "#csv", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-06-08", "description": "This notebook allows users to track the performance of their company's posts on LinkedIn by updating metrics in Notion's content calendar.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Update_metrics_from_company_posts_in_Notion_content_calendar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Update_metrics_from_company_posts_in_Notion_content_calendar.ipynb", "imports": ["naas", "naas_drivers.linkedin, notion", "datetime.datetime", "pandas", "plotly.express", "os", "requests"], "image_url": ""}, {"objectID": "e79fd40c42943142b09858493a155dd89ea2399f5fb45070b0ab28de29153c52", "tool": "LinkedIn", "notebook": "Update metrics from posts in Notion content calendar", "action": "", "tags": ["#linkedin", "#profile", "#post", "#feed", "#naas_drivers", "#notion", "#automation", "#analytics", "#naas", "#scheduler", "#content", "#plotly", "#html", "#csv", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-03-22", "description": "This notebook allows users to track the performance of their LinkedIn posts by automatically updating metrics from their Notion content calendar.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Update_metrics_from_posts_in_Notion_content_calendar.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Update_metrics_from_posts_in_Notion_content_calendar.ipynb", "imports": ["naas", "naas_drivers.linkedin, notion, emailbuilder", "datetime.datetime", "pandas", "plotly.express", "os", "requests"], "image_url": ""}, {"objectID": "04c698d2af7423916c8813d69fb15a47ac877cb56b2f6a3f81aa8c0ebddb5eda", "tool": "LinkedIn", "notebook": "Withdraw pending profile invitations", "action": "", "tags": ["#linkedin", "#invitation", "#pending", "#naas_drivers", "#content", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-29", "created_at": "2022-09-22", "description": "This notebook allows users to view and manage pending profile invitations sent through LinkedIn.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/LinkedIn/LinkedIn_Withdraw_pending_profile_invitations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/LinkedIn/LinkedIn_Withdraw_pending_profile_invitations.ipynb", "imports": ["naas_drivers.linkedin", "pandas", "naas", "time", "datetime.datetime", "dateutil.relativedelta.relativedelta", "json", "requests"], "image_url": ""}, {"objectID": "c4aa64628872dabf26a9f58ad9be5a790a83a704cfcd3b791774f949ce8df046", "tool": "Matplotlib", "notebook": "Create Barchart", "action": "", "tags": ["#matplotlib", "#chart", "#barchart", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "", "updated_at": "2023-07-17", "created_at": "2023-07-17", "description": "This notebook provides instructions on how to create a barchart chart using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Barchart.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "087c2b13300d04d4048791c573da3382591f69fdbeeb3db9d872a17a9c293063", "tool": "Matplotlib", "notebook": "Create Horizontal Barchart", "action": "", "tags": ["#matplotlib", "#chart", "#horizontal barchart", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-17", "created_at": "2023-07-17", "description": "This notebook provides instructions on how to create a horizontal Bar chart using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Horizontal_barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Horizontal_barchart.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "b44c24fa0f9c6a8934b98015860672c84babcf90aabd201045cef089cac9e10b", "tool": "Matplotlib", "notebook": "Create Stacked Barchart", "action": "", "tags": ["#matplotlib", "#chart", "#stacked barchart", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-24", "created_at": "2023-07-17", "description": "This notebook provides instructions on how to create a stacked Bar chart using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Stacked_barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Stacked_barchart.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "6c294eadef488f2bffbf61bdc27d1118210c59ff5131678cf5ea3b9ffb8c8db4", "tool": "Matplotlib", "notebook": "Create Stackplots", "action": "", "tags": ["#matplotlib", "#chart", "#stackplots", "#streamgraphs", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to create stackplots using matplotlib. Stackplots draw multiple datasets as vertically stacked areas. This is useful when the individual data values and additionally their cumulative value are of interest.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Stackplot.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Stackplot.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "1f3fc35bee4b3150b9147bddd14a9ddcc1b03b43e06219f599ffbf03c0670508", "tool": "Matplotlib", "notebook": "Create Step Demo", "action": "", "tags": ["#matplotlib", "#chart", "#step demo", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-25", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to plot the coherence of two signals using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Step_Demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Step_Demo.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "9776fa7b943cf273829c127952e6b3fa77670a7f6964394f776398982b55a76e", "tool": "Matplotlib", "notebook": "Create Streamgraphs", "action": "", "tags": ["#matplotlib", "#chart", "#stackplots", "#streamgraphs", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to create using matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Streamgraphs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Streamgraphs.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "5d656a5d27e392c123ffbf464947fa2704905053ca4492c2f5d4c83b4078df64", "tool": "Matplotlib", "notebook": "Create Waterfall chart", "action": "", "tags": ["#matplotlib", "#chart", "#warterfall", "#dataviz", "#snippet", "#operations", "#image"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a Waterfall chart using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_Waterfall_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_Waterfall_chart.ipynb", "imports": ["numpy", "pandas", "matplotlib.pyplot", "matplotlib.ticker.FuncFormatter"], "image_url": ""}, {"objectID": "d0d75eac84da33d249e5a02389b33b1d1072ec9fa51c3714cc2d1301bce1a15e", "tool": "Matplotlib", "notebook": "Creating a timeline with lines, dates, and text", "action": "", "tags": ["#matplotlib", "#chart", "#timeline", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-25", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to create a simple timeline using Matplotlib release dates.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Create_timeline%20_with_lines_dates_and_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Create_timeline%20_with_lines_dates_and_text.ipynb", "imports": ["matplotlib.pyplot", "numpy", "matplotlib.dates", "datetime.datetime", "naas", "urllib.request", "json"], "image_url": ""}, {"objectID": "c32df804be451c266b92c3ad55937b47476ccfc6f07ce09ac434fce8e1c5f0e1", "tool": "Matplotlib", "notebook": "Errorbar Limit Selection", "action": "", "tags": ["#matplotlib", "#chart", "#errorbar", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to create illustrations of selectively drawing lower and/or upper limit symbols on errorbars using the parameters uplims, lolims of errorbar using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Errorbar_limit_selection.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Errorbar_limit_selection.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "ec9d2f3bc763b8c5dab172f1354acd3ef85d13adbcfe201601c7155547bb3429", "tool": "Matplotlib", "notebook": "Mapping marker properties to multivariate data", "action": "", "tags": ["#matplotlib", "#chart", "#stackplots", "#markers", "#dataviz", "#snippet", "#operations", "#image", "#multivariate datasets"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-25", "created_at": "2023-07-24", "description": "This notebook shows how to use different properties of markers to plot multivariate datasets using Matplotlib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Map_marker_properties_to_plot_multivariate_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Map_marker_properties_to_plot_multivariate_data.ipynb", "imports": ["numpy", "matplotlib.pyplot", "matplotlib.markers.MarkerStyle", "matplotlib.transforms.Affine2D", "matplotlib.text.TextPath", "naas"], "image_url": ""}, {"objectID": "42138b50edc125a7228a7a869f6566ffccf68e03ad9a7f48c4c553f3ff2f00e6", "tool": "Matplotlib", "notebook": "Plotting the Coherence of two signals", "action": "", "tags": ["#matplotlib", "#chart", "#coherence", "#dataviz", "#snippet", "#operations", "#image"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-25", "created_at": "2023-07-24", "description": "This notebook provides instructions on how to plot the coherence of two signals using Matplotlib", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Matplotlib/Matplotlib_Plotting_the_coherence_of_two_signals.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Matplotlib/Matplotlib_Plotting_the_coherence_of_two_signals.ipynb", "imports": ["numpy", "matplotlib.pyplot", "naas"], "image_url": ""}, {"objectID": "4a4589dd47268d7b41670305c96da56350a70ae172778a99f62759ae520ca82d", "tool": "Metrics Store", "notebook": "Content creation Track connections", "action": "", "tags": ["#metricsstore", "#metrics", "#content-creation", "#connections", "#content", "#snippet", "#plotly"], "author": "Riddhi Deshpande", "author_url": "https://www.linkedin.com/in/riddhideshpande/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "This notebook allows users to track connections related to content creation for the Metrics Store.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Metrics%20Store/Content_creation_Track_connections.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Metrics%20Store/Content_creation_Track_connections.ipynb", "imports": ["naas_drivers.notion", "naas", "pandas", "plotly.express"], "image_url": ""}, {"objectID": "32ed25173bd9f466a47c983ffa60c2443f32dfa1abefdb12445840b50f37a01f", "tool": "Microsoft Teams", "notebook": "Send message", "action": "", "tags": ["#microsoftteams", "#snippet", "#operations"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows users to send messages through Microsoft Teams.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Microsoft%20Teams/Microsoft_Teams_Send_message.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Microsoft%20Teams/Microsoft_Teams_Send_message.ipynb", "imports": ["naas_drivers.teams"], "image_url": ""}, {"objectID": "b4452f1b67f4490a67006104ca10458588e76c3188b5d0da2519c9a7d24fcf43", "tool": "Microsoft Word", "notebook": "Convert to HMTL", "action": "", "tags": ["#microsoftword", "#word", "#microsoft", "#html", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook allows users to convert Microsoft Word documents into HTML format.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Microsoft%20Word/Microsoft_Word_Convert_to_HMTL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Microsoft%20Word/Microsoft_Word_Convert_to_HMTL.ipynb", "imports": ["mammoth", "mammoth"], "image_url": ""}, {"objectID": "a53f5b5e6b059ad365cf319b58a4a0d99fd1f954bd7c82bb61bdd9d42b9beebc", "tool": "Mixpanel", "notebook": "Get Profile Event Activity", "action": "", "tags": ["#mixpanel", "#activity", "#stream", "#query", "#api", "#reference"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-06", "created_at": "2023-07-06", "description": "This notebook returns the activity feed for specified users. It is usefull for organizations to track user activity and get insights from it.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Mixpanel/Mixpanel_Get_Profile_Event_Activity.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Mixpanel/Mixpanel_Get_Profile_Event_Activity.ipynb", "imports": ["requests", "json", "naas"], "image_url": ""}, {"objectID": "4252489d2efa2ce3fd0f5a3307c6b97db4ab6744a01716b56f718411ccb7d4a1", "tool": "MongoDB", "notebook": "Get data", "action": "", "tags": ["#mongodb", "#database", "#naas_drivers", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook provides instructions on how to retrieve data from a MongoDB database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/MongoDB/MongoDB_Get_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/MongoDB/MongoDB_Get_data.ipynb", "imports": ["naas_drivers.mongo"], "image_url": ""}, {"objectID": "ec3994d9054fd4ae36571978044ce3caca24fc1912451bb7a8d872dada0831fc", "tool": "MongoDB", "notebook": "Send data", "action": "", "tags": ["#mongodb", "#database", "#naas_drivers", "#snippet", "#operations", "#naas"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-03-03", "description": "This notebook provides instructions on how to send data to a MongoDB database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/MongoDB/MongoDB_Send_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/MongoDB/MongoDB_Send_data.ipynb", "imports": ["naas_drivers.mongo", "pandas"], "image_url": ""}, {"objectID": "d7646a98514c3189281b5bfe97b6c5c639807d7eb9b6d6c1367b0c0934d5d540", "tool": "MongoDB", "notebook": "Send data to Google Sheets", "action": "", "tags": ["#mongodb", "#googlesheets", "#nosql", "#operations", "#automation"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-04-12", "created_at": "2022-03-21", "description": "This notebook will help you send data from your MongoDB database collection to your spreadsheet", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/MongoDB/MongoDB_Send_data_to_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/MongoDB/MongoDB_Send_data_to_Google_Sheets.ipynb", "imports": ["naas_drivers.mongo, gsheet", "pandas", "naas"], "image_url": ""}, {"objectID": "47c0e6657c573a3ff0e9d41a364f948a355dee01276d4dca70e25b179bb648a1", "tool": "MoviePy", "notebook": "Convert audio file M4A to MP3", "action": "", "tags": ["#moviepy", "#audio", "#convert", "#m4a", "#mp3", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-23", "created_at": "2023-07-23", "description": "This notebook would allow you to transform an audio file from M4A to MP3. It can be further used by people who want to use their Iphone voice recording m\u00e9mos file and generate transcripts with AI.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/MoviePy/MoviePy_Convert_audio_file_M4A_to_MP3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/MoviePy/MoviePy_Convert_audio_file_M4A_to_MP3.ipynb", "imports": ["moviepy.editor.AudioFileClip", "moviepy.editor.AudioFileClip", "requests"], "image_url": ""}, {"objectID": "b8efa6e10ef17925c883986434e62e36da03dc7dd1c07b6660016b7ece44f8ba", "tool": "MySQL", "notebook": "Query database", "action": "", "tags": ["#mysql", "#database", "#snippet", "#operations", "#naas"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides an introduction to querying a MySQL database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/MySQL/MySQL_Query_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/MySQL/MySQL_Query_database.ipynb", "imports": ["os", "pymysql", "pandas"], "image_url": ""}, {"objectID": "334f731f131404dea142a3cf7464a96763daa3cd3b8ce4e28e96a6796f25824c", "tool": "NASA", "notebook": "Artic sea ice", "action": "", "tags": ["#nasa", "#naas", "#opendata", "#analytics", "#asset", "#html", "#png", "#operations", "#image", "#plotly"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-05-10", "description": "AVERAGE SEPTEMBER MINIMUM EXTENT
\nData source: Satellite observations. Credit: NSIDC/NASA\n\n**What is Arctic sea ice extent?**
\nSea ice extent is a measure of the surface area of the ocean covered by sea ice. Increases in air and ocean temperatures decrease sea ice extent; in turn, the resulting darker ocean surface absorbs more solar radiation and increases Arctic warming.
\nDate Range: 1979 - 2020.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/NASA/NASA_Artic_sea_ice.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/NASA/NASA_Artic_sea_ice.ipynb", "imports": ["pandas", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "8c8fa4d995ff61138dd01ab17c04bb8001b05cbb2aeb5f0eaab6a5c27c9ed6f4", "tool": "NASA", "notebook": "Display Exoplanet by Light Curves", "action": "", "tags": ["#nasa", "#naas", "#opendata", "#analytics", "#astronomy", "#html", "#png", "#operations", "#image", "#pylab"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-31", "created_at": "2023-07-05", "description": "This notebook is display Exoplanet by light curves. An exoplanet is any planet beyond our solar system. Most orbit other stars, but free-floating exoplanets, called rogue planets, orbit the galactic center and are untethered to any star.
", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/NASA/NASA_Classify_Exoplanet_by_light_curves.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/NASA/NASA_Classify_Exoplanet_by_light_curves.ipynb", "imports": ["pandas", "numpy", "naas"], "image_url": ""}, {"objectID": "1fcde93a2f4eb30a04bb469261370e4772541277ba8e30b726593dd5939d11f6", "tool": "NASA", "notebook": "Global temperature", "action": "", "tags": ["#nasa", "#opendata", "#analytics", "#plotly"], "author": "Colyn TIDMAN", "author_url": "https://www.linkedin.com/in/dylan-pichon/", "updated_at": "2023-04-12", "created_at": "2021-05-28", "description": "This graph illustrates the change in global surface temperature relative to 1951-1980 average temperatures. Nineteen of the warmest years have occurred since 2000, with the exception of 1998. The year 2020 tied with 2016 for the warmest year on record since record-keeping began in 1880 (source: NASA/GISS). This research is broadly consistent with similar constructions prepared by the Climatic Research Unit and the National Oceanic and Atmospheric Administration.\n\nThe time series below shows the five-year average variation of global surface temperatures. Dark blue indicates areas cooler than average. Dark red indicates areas warmer than average.\n\nThe \u201cGlobal Temperature\u201d figure on the home page dashboard shows global temperature change since 1880. One gets this number by subtracting the first data point in the chart from the latest data point.\n\nWebsite : https://climate.nasa.gov/vital-signs/global-temperature/", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/NASA/NASA_Global_temperature.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/NASA/NASA_Global_temperature.ipynb", "imports": ["pandas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "32201bf648e273b41b194575397810ecfb97f21cd37d9d8446341a12f96d0751", "tool": "NASA", "notebook": "Sea level", "action": "", "tags": ["#nasa", "#naas", "#opendata", "#analytics", "#plotly"], "author": "Colyn TIDMAN", "author_url": "https://www.linkedin.com/in/dylan-pichon/", "updated_at": "2023-04-12", "created_at": "2021-05-28", "description": "Sea level rise is caused primarily by two factors related to global warming: the added water from melting ice sheets and glaciers and the expansion of seawater as it warms. The first graph tracks the change in sea level since 1993 as observed by satellites.\n\nThe second graph, derived from coastal tide gauge and satellite data, shows how much sea level changed from about 1900 to 2018. Items with pluses (+) are factors that cause global mean sea level to increase, while minuses (-) are variables that cause sea levels to decrease. These items are displayed at the time they were affecting sea level.\n\nThe data shown are the latest available, with a four- to five-month lag needed for processing.\n\n* You now need to create an Earthdata account to access NASA's sea level data. Register for free by clicking on 'Get data : http'. Once logged in you will access the data.\n\nWebsite : https://climate.nasa.gov/vital-signs/sea-level/", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/NASA/NASA_Sea_level.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/NASA/NASA_Sea_level.ipynb", "imports": ["pandas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "397ec80a5d605618ddb1c746bd5ae1cf2a9cde80101da5a4d1f3b50caf56dd22", "tool": "Naas Auth", "notebook": "Bearer validate", "action": "", "tags": ["#naasauth", "#naas", "#auth", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-01-20", "description": "This notebook provides a way to validate Bearer tokens for authentication with the Naas API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Auth/Naas_Auth_bearer_validate.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Auth/Naas_Auth_bearer_validate.ipynb", "imports": ["naas_drivers.naasauth"], "image_url": ""}, {"objectID": "707ec48e296bbb6f5fcc8033d750087e362ad452a041e95f21c6d735dedfc4c8", "tool": "Naas Auth", "notebook": "Connect", "action": "", "tags": ["#naasauth", "#naas", "#auth", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-01-20", "description": "Naas Auth - Connect is a notebook that allows users to securely authenticate and connect to their Naas account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Auth/Naas_Auth_connect.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Auth/Naas_Auth_connect.ipynb", "imports": ["naas_drivers.naasauth"], "image_url": ""}, {"objectID": "a20de7e2d83d0f89de859559f5cf13c396e48b548762365f135ee5b9711a408f", "tool": "Naas Auth", "notebook": "Users me", "action": "", "tags": ["#naasauth", "#naas", "#auth", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-01-20", "description": "This notebook provides a user-friendly interface for authenticating users with Naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Auth/Naas_Auth_users_me.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Auth/Naas_Auth_users_me.ipynb", "imports": ["naas_drivers.naasauth"], "image_url": ""}, {"objectID": "0868c0a991f66c0a07b9d6f8f005dd86de34a21d6f03a692962537e3cd119dde", "tool": "Naas Dashboard", "notebook": "Financial Consolidation", "action": "", "tags": ["#naasdashboard", "#plotly", "#dash", "#naas", "#asset", "#automation", "#analytics", "#snippet", "#datavizualisation"], "author": "Meriem Si", "author_url": "https://www.linkedin.com/in/meriem-si-104236181/", "updated_at": "2023-04-12", "created_at": "2022-09-12", "description": "This notebook provides a comprehensive dashboard for financial consolidation and analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Dashboard/Naas_Dashboard_Financial_Consolidation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Dashboard/Naas_Dashboard_Financial_Consolidation.ipynb", "imports": ["dash", "dash", "dash.html, dcc, Input, Output, State", "dash_bootstrap_components", "dash_bootstrap_components", "plotly.graph_objects", "plotly.express", "os", "pandas", "naas_drivers.gsheet", "dash_bootstrap_components._components.Container.Container", "plotly.subplots.make_subplots"], "image_url": ""}, {"objectID": "b914e946e624466c61e2bc0891564eedd3c6d8fc5f59c62e5caaff62e612e88b", "tool": "Naas Dashboard", "notebook": "Revenue Cogs by Segment", "action": "", "tags": ["#naasdashboard", "#plotly", "#dash", "#naas", "#asset", "#automation", "#analytics", "#snippet", "#datavizualisation"], "author": "Fernando Chavez Osuna", "author_url": "https://www.linkedin.com/in/fernando-chavez-osuna-1a420a181", "updated_at": "2023-04-12", "created_at": "2022-09-22", "description": "This notebook provides an analysis of revenue cogs by segment for the Naas Dashboard.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Dashboard/Naas_Dashboard_Revenue_Cogs_by_Segment.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Dashboard/Naas_Dashboard_Revenue_Cogs_by_Segment.ipynb", "imports": ["dash", "dash", "dash.html, dcc, Input, Output, State", "dash_bootstrap_components", "dash_bootstrap_components", "plotly.graph_objects", "plotly.express", "os", "naas_drivers", "naas_drivers.gsheet", "dash_bootstrap_components._components.Container.Container", "pandas"], "image_url": ""}, {"objectID": "16c5518def67a82a87c39ce69fd9ab6a967b9e509c063c8e6541f593ed677b01", "tool": "Naas Dashboard", "notebook": "Social Media KPIs ScoreCard", "action": "", "tags": ["#naasdashboard", "#plotly", "#dash", "#naas", "#asset", "#automation", "#analytics", "#snippet", "#datavizualisation"], "author": "Ismail CHIHAB", "author_url": "https://www.linkedin.com/in/ismail-chihab-4b0a04202/", "updated_at": "2023-04-12", "created_at": "2022-09-12", "description": "This notebook provides a comprehensive scorecard of key performance indicators for social media platforms.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas%20Dashboard/Naas_Dashboard_Social_Media_KPIs_ScoreCard.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas%20Dashboard/Naas_Dashboard_Social_Media_KPIs_ScoreCard.ipynb", "imports": ["dash", "dash", "dash.html, dcc, Input, Output, State", "dash_bootstrap_components", "dash_bootstrap_components", "naas", "naas_drivers.gsheet", "dash.html, dash_table", "dash.dependencies.Input, Output, State", "dash.dcc", "pandas", "os"], "image_url": ""}, {"objectID": "49f156224d2f4ba86dc03cb514690634f99d651dd4c8f390d9471bd33666c42e", "tool": "Naas", "notebook": "Add or Update Asset", "action": "", "tags": ["#naas", "#asset", "#snipet", "#operations", "#add", "#update"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to copy in production a file as an asset and allow yourself to get it by calling the returned URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Add_or_Update_Asset.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Add_or_Update_Asset.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "a8e532c51f125b4b806b25baaa49c531492178fb58f0a6f823bf8b33833fab72", "tool": "Naas", "notebook": "Add or Update Dependency", "action": "", "tags": ["#naas", "#dependency", "#add", "#update", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to add or update a dependency in Naas. The naas dependency feature push files (script, csv) into production environment.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Add_or_Update_Dependency.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Add_or_Update_Dependency.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "6324a3458ed02970a57df320b23fe3db9e2b49b779c42a0851a2b64b47ad0948", "tool": "Naas", "notebook": "Add or Update Scheduler", "action": "", "tags": ["#naas", "#scheduler", "#snippet", "#operations", "#add", "#update"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to automate a notebook using the scheduler feature of Naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Add_or_Update_Scheduler.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Add_or_Update_Scheduler.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "9881af429a735a74f8b198299ac81dd7aa1a9f1499269d69dc4673560f47dc67", "tool": "Naas", "notebook": "Add or Update Secret", "action": "", "tags": ["#naas", "#secret", "#add", "#update", "#operation", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to add or uppdate a secret to Naas.\n\nSecrets are an important part of Naas, when you need to interact with other services, you need secret, like any other variable the temptation is big to put it straight in your notebook, but this lead to a big security breach since we replicate a lot the notebook, in the versioning system, the output and your ability to share it or send it to git! \nUse this simple feature instead to have global secure storage share with your sandbox and production.\nSecrets are local to your machine and encoded, that a big layer of security with a little effort.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Add_or_Update_Secret.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Add_or_Update_Secret.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "abd7d33c33240f853371346227a2ae5b2c4b78bec62d783f4ce06e07af02da6f", "tool": "Naas", "notebook": "Add or Update Webhook", "action": "", "tags": ["#naas", "#webhook", "#add", "#update", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to add or update a webhook in production using Naas feature. The notebook will be sent to production and you will get an URL that can be triggered.\n\nWebhooks are useful because they enable real-time communication between applications, allowing for automated notifications or data exchange when specific events occur. This eliminates the need for constant polling and manual data retrieval, making webhooks efficient and scalable for various use cases.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Add_or_Update_Webhook.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Add_or_Update_Webhook.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "a4c7e1cb7a80573d8aeee8b70bd4bb3aa1a2e3ebc220423757dc6330ac876253", "tool": "Naas", "notebook": "Asset demo", "action": "", "tags": ["#naas", "#asset", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-31", "description": "Read the doc on https://naas.gitbook.io/naas/features/asset", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Asset_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Asset_demo.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "7e51dbae8cf766d7bbe70b8e5d811776b60173220ab6eccc75086cf2480daed3", "tool": "Naas", "notebook": "Automate GitHub Auth", "action": "", "tags": ["#naas", "#asset", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-28", "description": "This notebook provides an automated way to authenticate with GitHub using Naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Automate_GitHub_Auth.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Automate_GitHub_Auth.ipynb", "imports": [], "image_url": ""}, {"objectID": "42ed86f1ce38ee92bc5c86740032d85a786e7c249673b9895f0ff3e6c5ee3944", "tool": "Naas", "notebook": "Configure Github with ssh", "action": "", "tags": ["#naas", "#git", "#github", "#jupyterlab", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-04-07", "description": "This notebook provides instructions on how to configure Github with SSH for secure access to the Naas platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Configure_Github_with_ssh.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Configure_Github_with_ssh.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "55207a267c659be8a52dab480828d899bcb20c49f124060ea6c4a6f1d890531c", "tool": "Naas", "notebook": "Create Kernel", "action": "", "tags": ["#naas", "#ipython", "#conda", "#kernel"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-01-11", "description": "This Jupyter Notebook will enable you to establish a new IPython Kernel that you can customize, allowing you to install any desired tools. This kernel, once created, can be selected to run your notebooks and can be used even in a production environment.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Create_Kernel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Create_Kernel.ipynb", "imports": [], "image_url": ""}, {"objectID": "92ddbcf7c74813cc4c906ca6b7d04cc2590230b5fb16082b396de5b9872be0cf", "tool": "Naas", "notebook": "Create Pipeline", "action": "", "tags": ["#naas", "#pipeline", "#jupyter", "#notebook", "#dataanalysis", "#workflow", "#streamline"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-01-20", "description": "This notebook is a guide that teaches you how to create a notebook pipeline using naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Create_Pipeline.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Create_Pipeline.ipynb", "imports": ["naas.pipeline.pipeline.("], "image_url": ""}, {"objectID": "a1b3a685ea98ec4477699d6993219645300070c5f79b8b8cdbedb74c82fc9f9d", "tool": "Naas", "notebook": "Create onboarding plugin using OpenAI", "action": " ", "tags": ["#onboarding", "#naas", "#openai", "#personas", "#ai", "#machinelearning", "#deeplearning", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-15", "created_at": "2023-06-14", "description": "This notebook will create a onboarding plugin into Naas-MyChatGPT app using OpenAI.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Create_onboarding_plugin_using_OpenAI.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Create_onboarding_plugin_using_OpenAI.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Create_onboarding_plugin_using_OpenAI.ipynb", "imports": ["json", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "b8e8498be8e2a6e4ed47256dd6b987fc934f372db1ce9b0ba198bd19514296ca", "tool": "Naas", "notebook": "Credits Get Balance", "action": "", "tags": ["#naas", "#credits", "#snippet", "#operations"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-11-17", "description": "This notebook provides a way to view the balance of credits available for use in the Naas platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Credits_Get_Balance.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Credits_Get_Balance.ipynb", "imports": ["naas_drivers.naascredits"], "image_url": ""}, {"objectID": "faebd17e0e224ea21a9214be8a9831d2b94a5f912ab27836676b26589d608f3f", "tool": "Naas", "notebook": "Delete Asset", "action": "", "tags": ["#naas", "#asset", "#snipet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-08-16", "created_at": "2023-03-21", "description": "This notebook will show how to delete an asset from naas production environment.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_Asset.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_Asset.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "54d4fe233930b6fe96be9c4df3daf94f17ad0a3785c88dc9818b6c126173609f", "tool": "Naas", "notebook": "Delete Dependency", "action": "", "tags": ["#naas", "#dependency", "#snipet", "#operations", "#delete"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to delete a dependency from naas production environment.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_Dependency.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_Dependency.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "e5801f9ba44fba35f2b6845fb88f7e660692550236c17ba3b6189300fdbd905b", "tool": "Naas", "notebook": "Delete Scheduler", "action": "", "tags": ["#naas", "#scheduler", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-16", "created_at": "2023-03-15", "description": "This notebook will show how to delete a naas scheduler.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_Scheduler.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_Scheduler.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "13f4b5a9bef18a2771e6e56c4ecd486c68e6b83c5b8be85e302ec59fcb4fc4ad", "tool": "Naas", "notebook": "Delete Secret", "action": "", "tags": ["#naas", "#secret", "#delete", "#api", "#python", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-27", "created_at": "2023-04-27", "description": "This notebook will show how to delete a secret in Naas.\n\nSecrets are an important part of Naas, when you need to interact with other services, you need secret, like any other variable the temptation is big to put it straight in your notebook, but this lead to a big security breach since we replicate a lot the notebook, in the versioning system, the output and your ability to share it or send it to git! \nUse this simple feature instead to have global secure storage share with your sandbox and production.\nSecrets are local to your machine and encoded, that a big layer of security with a little effort.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_Secret.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_Secret.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "27ea4180c03a08d23d80e1786c1b59542fa459be8170a2aac537979178d4bdfc", "tool": "Naas", "notebook": "Delete Webhook", "action": "", "tags": ["#naas", "#scheduler", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-24", "description": "This notebook will show how to delete a naas webhook.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_Webhook.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_Webhook.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "ad17062d674c08958e8d52d2c391a621c91ce8ce90e01be930c7fec90dc78a84", "tool": "Naas", "notebook": "Delete all assets", "action": "", "tags": ["#naas", "#assets", "#delete", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-16", "created_at": "2023-08-16", "description": "This notebook deletes all assets in Naas Lab.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_all_assets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_all_assets.ipynb", "imports": ["naas", "os"], "image_url": ""}, {"objectID": "8c929e981ea24e0ea05c39e9bb399e341431ef3b5c9533df80b4292b78269a2f", "tool": "Naas", "notebook": "Delete all schedulers", "action": "", "tags": ["#naas", "#scheduler", "#delete", "#automation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-16", "created_at": "2023-08-16", "description": "This notebook deletes all schedulers in Naas Lab.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Delete_all_schedulers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Delete_all_schedulers.ipynb", "imports": ["naas", "os"], "image_url": ""}, {"objectID": "2b6603209c8adc27d4663ce554cdc239d6eca437c4cbdd0a30923eeca573b888", "tool": "Naas", "notebook": "Dependency demo", "action": "", "tags": ["#naas", "#dependency", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook demonstrates how to use Naas to manage dependencies in a project.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Dependency_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Dependency_demo.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "19034fbe5e15fb13de9738e02f6a5292dd1fcd6cac4aed92315fee5c458c3f95", "tool": "Naas", "notebook": "Doc demo", "action": "", "tags": ["#naas", "#doc", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook provides a demonstration of how to use the Naas Docs API to create, update, and delete documents.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Doc_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Doc_demo.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "1f6c374e05c5935ce272c9d5dc0ae45735b9d21beb8ca9f23fef22cd9a190ff7", "tool": "Naas", "notebook": "Download Content Engine", "action": "", "tags": ["#naas", "#automation", "#linkedin", "#youtube", "#twitter", "#snapchat", "#instagram", "#facebook", "#tiktok", "#dataproduct"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-08-02", "description": "Naas is a content engine that enables users to easily download and manage digital content.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Download_Content_Engine.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Download_Content_Engine.ipynb", "imports": ["IPython.display.display", "ipywidgets.widgets", "naas", "os.path"], "image_url": ""}, {"objectID": "e74b8806f7d7fbcafe79c6713182bc3c7d29e00f8f2e299adb90b2388baadad0", "tool": "Naas", "notebook": "Emailbuilder demo", "action": "", "tags": ["#naas", "#emailbuilder", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-05-28", "description": "This notebook provides a demonstration of the Naas Emailbuilder, a tool for creating and managing email campaigns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Emailbuilder_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Emailbuilder_demo.ipynb", "imports": ["naas_drivers", "naas", "pandas"], "image_url": ""}, {"objectID": "1149e5c1a3d183a41ab530f754117157d2f86e1719516b99e4a263256a582065", "tool": "Naas", "notebook": "Find Asset link from path", "action": "", "tags": ["#naas", "#asset", "#path", "#link", "#find", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-04", "created_at": "2023-05-04", "description": "This notebook will help you find the asset link generated with naas from a given file path.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Find_Asset_link_from_path.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Find_Asset_link_from_path.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "5df9412ae66fd7ab475df0c83cd5f8a2f36ca695bb4292dd5433aded3dc2e890", "tool": "Naas", "notebook": "Get Transactions", "action": "", "tags": ["#naas", "#credits", "#snippet", "#operations"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-11-17", "description": "This notebook provides an easy way to access and analyze transaction data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Get_Transactions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Get_Transactions.ipynb", "imports": ["naas_drivers.naascredits", "pandas"], "image_url": ""}, {"objectID": "ff3a18474c57d0d2d83b9948b2019155f36de2170d1269c715e4bbee2be82c30", "tool": "Naas", "notebook": "Get help", "action": "", "tags": ["#naas", "#help", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook provides helpful resources and guidance for navigating the Naas platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Get_help.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Get_help.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "bafc9570d7378763e028d2cc37280a8b0358f2e1e876500ea2b2f26622c6fed4", "tool": "Naas", "notebook": "Get number of downloads naas drivers package", "action": "", "tags": ["#pypi", "#downloads", "#package", "#operations", "#analytics", "#plotly", "#html", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-27", "description": "This notebook provides a way to get the number of downloads for the Naas drivers package.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Get_number_of_downloads_naas_drivers_package.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Get_number_of_downloads_naas_drivers_package.ipynb", "imports": ["pypistats", "pypistats", "pprint.pprint", "datetime.datetime", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "a3c80e86afed6d77dcb6463c1a64986dd6506f0b0e67063d62ece0219df17ea7", "tool": "Naas", "notebook": "Get number of downloads naas package", "action": "", "tags": ["#pypi", "#downloads", "#package", "#operations", "#analytics", "#plotly", "#html", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-27", "description": "This notebook provides a way to track the number of downloads of the Naas package.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Get_number_of_downloads_naas_package.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Get_number_of_downloads_naas_package.ipynb", "imports": ["pypistats", "pypistats", "pprint.pprint", "datetime.datetime", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "cdc37edf1d19e1738a9b7d3ba99776a599632e661bce3cb24a35e684bf673089", "tool": "Naas", "notebook": "Get total downloads naas libraries", "action": "", "tags": ["#pypi", "#downloads", "#package", "#operations", "#analytics", "#plotly", "#html", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-27", "description": "This notebook provides a way to track the total number of downloads for Naas libraries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Get_total_downloads_naas_libraries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Get_total_downloads_naas_libraries.ipynb", "imports": ["pypistats", "pypistats", "pprint.pprint", "datetime.datetime", "plotly.graph_objects", "naas", "pandas"], "image_url": ""}, {"objectID": "0f98f0161ed02bf496879b2648647afefc830264ade798125d0bc1025eb23164", "tool": "Naas", "notebook": "List Assets", "action": "", "tags": ["#naas", "#asset", "#snipet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-21", "description": "This notebook will show how to list current assets in production.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Assets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Assets.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "d140789cfd7892de0efe6e8a0bc0dfe7f63e1bcca0670e3125f08ec0e453ff9e", "tool": "Naas", "notebook": "List Dependencies", "action": "", "tags": ["#naas", "#dependency", "#snipet", "#operations", "#list"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook will show how to list current dependencies in production.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Dependencies.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Dependencies.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "6739d81dea060c5e005aa5b45c062c5babcfc372f44b53065a79051c0caa932d", "tool": "Naas", "notebook": "List Schedulers", "action": "", "tags": ["#naas", "#schedulers", "#list", "#production", "#tool", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-01", "created_at": "2023-06-01", "description": "This notebook will show how to list current schedulers running in production.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Schedulers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Schedulers.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "7cf4e74bd33a75a559cc1e22ecc9bb70366bde9d0c458855d41f445cb1b8f8a4", "tool": "Naas", "notebook": "List Schedulers with all executions", "action": "", "tags": ["#naas", "#schedulers", "#list", "#production", "#tool", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-01", "created_at": "2023-06-01", "description": "This notebook will show how to list current schedulers running in production with all their executions meta data and return a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Schedulers_with_all_executions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Schedulers_with_all_executions.ipynb", "imports": ["naas", "pandas"], "image_url": ""}, {"objectID": "6e0e66eeeef53f91e97285ff107f1c3101bfa1142186dec4122d51dfda1e01e2", "tool": "Naas", "notebook": "List Schedulers with last execution", "action": "", "tags": ["#naas", "#schedulers", "#list", "#production", "#tool", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-01", "created_at": "2023-06-01", "description": "This notebook will show how to list current schedulers running in production with their last execution meta data and return a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Schedulers_with_last_execution.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Schedulers_with_last_execution.ipynb", "imports": ["naas", "pandas"], "image_url": ""}, {"objectID": "ce518a817ab35c537e18a42c72d3e128ed9c8631f2a01ae33c7371e9e2191c13", "tool": "Naas", "notebook": "List Secrets", "action": "", "tags": ["#naas", "#secret", "#list", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-27", "created_at": "2023-04-27", "description": "This notebook will show how to list of your secrets stored in Naas.\nA dataframe with the following column will be retunred:\n- \"id\"\n- \"lastUpdate\"\n- \"name\"\n- \"secret\"", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Secrets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Secrets.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "745b5079821ad22ad9dffd2bb51faa5e200ff047045a7ce416742854c85e0508", "tool": "Naas", "notebook": "List Webhooks", "action": "", "tags": ["#naas", "#asset", "#snipet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-24", "created_at": "2023-04-24", "description": "**References:**\n- [Naas Documentation](https://docs.naas.ai/)\n- [Naas Webhook Documentation](https://docs.naas.ai/features/api)", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_List_Webhooks.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_List_Webhooks.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "1f256fb50ad384b7ca469fca4ec3af4d9e67a7d37dee4022ea3e74246dfc01aa", "tool": "Naas", "notebook": "Manage Pipeline Errors", "action": "", "tags": ["#naas", "#pipeline", "#jupyter", "#notebook", "#dataanalysis", "#workflow", "#streamline"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-01-25", "description": "This notebook is a guide that teaches you how to manage errors on your notebook pipeline using naas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Manage_Pipeline_Errors.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Manage_Pipeline_Errors.ipynb", "imports": ["naas.pipeline.pipeline.("], "image_url": ""}, {"objectID": "e26291e9d6bfb6a7d09e27a665447ed0ea75c57dde69de0957353a0ba7e6ad0c", "tool": "Naas", "notebook": "NLP Examples", "action": "", "tags": ["#naas", "#nlp", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-16", "description": "This notebook provides examples of Natural Language Processing (NLP) using the Naas framework.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_NLP_Examples.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_NLP_Examples.ipynb", "imports": ["naas_drivers.nlp", "ant thing in your life right now?\""], "image_url": ""}, {"objectID": "0262344937e5af7b41831767036ab89858af4db92075018b0924478c1fa68804", "tool": "Naas", "notebook": "Notification demo", "action": "", "tags": ["#naas", "#notification", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-31", "description": "This notebook demonstrates how to use Naas to send notifications.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Notification_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Notification_demo.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "e60642c7688856536bd0f8d94b21ef04b589583f51b99100ca685605f1a977b5", "tool": "Naas", "notebook": "Remove Pipeline Executions Outputs", "action": "", "tags": ["#naas", "#scheduler", "#automation", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2023-01-24", "description": "This notebook removes your production pipeline executions outputs automatically.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Remove_Pipeline_Executions_Outputs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Remove_Pipeline_Executions_Outputs.ipynb", "imports": ["glob", "os", "naas", "datetime.datetime", "dateutil.relativedelta.relativedelta", "shutil"], "image_url": ""}, {"objectID": "9ee266e99f40eace87c3aecf7828455a65b7bc2218e3c1420619d6f48d959a85", "tool": "Naas", "notebook": "Remove Scheduler Outputs", "action": "", "tags": ["#naas", "#scheduler", "#automation", "#operations"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-03-14", "description": "This notebook allows users to remove scheduler outputs from the Naas platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Remove_Scheduler_Outputs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Remove_Scheduler_Outputs.ipynb", "imports": ["glob", "os", "naas"], "image_url": ""}, {"objectID": "7a441dc7940c8af0eef50ca209a5b3ed87153419adf5048a7845589a86a0b2e7", "tool": "Naas", "notebook": "Reset Instance", "action": "", "tags": ["#naas", "#scheduler", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-03-14", "description": "This notebook provides a way to reset an instance of Naas, allowing users to start fresh with a clean slate.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Reset_Instance.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Reset_Instance.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "cc6f6c0bb7460dec3abd5121eacdcd5761d972c7525d7ee9ff630df5c532f576", "tool": "Naas", "notebook": "Scheduler demo", "action": "", "tags": ["#naas", "#scheduler", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-06-28", "description": "Transform all your work routines in notebooks and run them even when you sleep.
\nHere we are going to use the Notifications feature to test Scheduler.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Scheduler_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Scheduler_demo.ipynb", "imports": ["IPython.display.IFrame", "naas", "IPython.display.HTML"], "image_url": ""}, {"objectID": "73ad193419ed4c56bb0430e8bd15af0b0c998e973b50790e89b450e08cfc49ca", "tool": "Naas", "notebook": "Secret demo", "action": "", "tags": ["#naas", "#secret", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-31", "description": "Read the doc: https://naas.gitbook.io/naas/features/secret", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Secret_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Secret_demo.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "ebdd845a8c40505f123a9e8cbe5afdd1d1acbef753489ec61a74b133e7973c53", "tool": "Naas", "notebook": "Send Asset image to Notion page", "action": "", "tags": ["#naas", "#notion", "#image", "#asset", "#send", "#vizualise"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook sends an naas image asset to a Notion page. It could be usefull to push chart created in plotly to Notion. If your page is in a notion database, you will be able to vizualise the chart in Gallery (display page content). The image asset will be updated (deleted and added) to make sure the graph display is always up to date in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Send_Asset_image_to_Notion_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Send_Asset_image_to_Notion_page.ipynb", "imports": ["naas_drivers.notion", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "551be4f36d8e50ce4395892079f25ea4f86bc3f5057eb9c3b85f5664ed741aef", "tool": "Naas", "notebook": "Send notifications from Google Sheets", "action": "", "tags": ["#naas", "#productivity", "#gsheet", "#naas_drivers", "#operations", "#snippet", "#email"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-05-12", "created_at": "2023-05-12", "description": "This notebook allows users to send emails from a Google Sheets spreadsheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Send_notifications_from_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Send_notifications_from_Google_Sheets.ipynb", "imports": ["naas_drivers", "naas_drivers.gsheet, emailbuilder, naasauth", "naas"], "image_url": ""}, {"objectID": "a6491850e181fce4c10f4673acf7b7a3ba172aa9246dca51b7408803e66ee3dd", "tool": "Naas", "notebook": "Set timezone", "action": "", "tags": ["#naas", "#timezone", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook allows users to set the timezone for their Naas instance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Set_timezone.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Set_timezone.ipynb", "imports": ["naas"], "image_url": ""}, {"objectID": "17a6818193a07da83c5d6e09deb7bc618424cfbb53e9405b8661bceabcdadd91", "tool": "Naas", "notebook": "Start data product", "action": "", "tags": ["#naas", "#dataproduct", "#automation"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-04-11", "description": "In this notebook, we'll walk you through the process of starting a data product using the Naas data product framework and integrating awesome-notebooks into your project. \n\nPlease note that this notebook can only be used while connected to your Naas account. If you'd like to perform these steps locally, please don't hesitate to contact us \u2013 we're more than happy to assist you.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Start_data_product.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Start_data_product.ipynb", "imports": ["urllib.request", "zipfile", "glob", "os", "shutil", "pandas", "re"], "image_url": ""}, {"objectID": "d9094479c5bfd3f36bf674ca012c3b174702051ba15319d9bd9213fd3454fd9f", "tool": "Naas", "notebook": "Use SSH tunnel to reach network protected resources", "action": "", "tags": ["#naas", "#ssh", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-06-01", "description": "This notebook provides instructions on how to use an SSH tunnel to securely access resources on a network that is otherwise protected.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Use_SSH_tunnel_to_reach_network_protected_resources.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Use_SSH_tunnel_to_reach_network_protected_resources.ipynb", "imports": ["sshtunnel", "sshtunnel", "psycopg2", "psycopg2"], "image_url": ""}, {"objectID": "def658c3a83d17228a73685b81bbf7979a78a6c56aba2b79ba99b414bacbc26a", "tool": "Naas", "notebook": "Webhook demo", "action": "", "tags": ["#naas", "#webhook", "#snippet", "#operations"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-31", "description": "## Basic formulas\nRunning this command will add your this notebook to the \"\u26a1\ufe0f Production\" folder.
\nYou can then, trigger it with the generated URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Naas/Naas_Webhook_demo.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Naas/Naas_Webhook_demo.ipynb", "imports": ["naas", "naas", "naas"], "image_url": ""}, {"objectID": "615ec6a8a79947d3ad3332806a73e9d47724fb113848dfdbff7166e70b84e367", "tool": "Neo", "notebook": "Get currencies live prices", "action": "", "tags": ["#neo", "#bank", "#snippet", "#finance", "#csv"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides live currency prices for various currencies.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Neo/Neo_Get_currencies_live_prices.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Neo/Neo_Get_currencies_live_prices.ipynb", "imports": ["pathlib.Path", "pandas", "requests"], "image_url": ""}, {"objectID": "ad988b3acb38ff32d1a21f78c88a01d3436a580add95cb262464d26b5b65eb39", "tool": "Newsapi", "notebook": "Get data", "action": "", "tags": ["#newsapi", "#news", "#snippet", "#opendata", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a guide to using the Newsapi service to access and retrieve data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Newsapi/Newsapi_Get_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Newsapi/Newsapi_Get_data.ipynb", "imports": ["naas_drivers.newsapi"], "image_url": ""}, {"objectID": "8c7a4d82d6c655fc8c32095c16c53da8d6a524084ffa01fc55f762ffe5e37c8b", "tool": "Newsapi", "notebook": "Run sentiment analysis", "action": "", "tags": ["#newsapi", "#news", "#sentimentanalysis", "#ai", "#opendata", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-10", "description": "This notebook uses Newsapi to analyze the sentiment of news articles.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Newsapi/Newsapi_Run_sentiment_analysis.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Newsapi/Newsapi_Run_sentiment_analysis.ipynb", "imports": ["naas_drivers.newsapi, sentiment"], "image_url": ""}, {"objectID": "ad3d5031c222cb811084f9a2641946b57cd17649f5b03f8a92a93e9dc8e41b09", "tool": "Newsapi", "notebook": "Send emails briefs", "action": "", "tags": ["#newsapi", "#news", "#emailbrief", "#automation", "#notification", "#opendata", "#email", "#image", "#html", "#text"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-10", "description": "This notebook allows users to send automated email briefs based on news articles from the Newsapi API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Newsapi/Newsapi_Send_emails_briefs.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Newsapi/Newsapi_Send_emails_briefs.ipynb", "imports": ["naas_drivers.newsapi, emailbuilder", "naas"], "image_url": ""}, {"objectID": "4aa241b693f1246fa34f81ec73340d9e657d507c316332d862408e86fed3942b", "tool": "Notion", "notebook": "Add bulleted list in page", "action": "", "tags": ["#notion", "#list", "#page", "#organization", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-30", "created_at": "2023-04-30", "description": "This notebook explains how to add a bulleted list in a Notion page from a list object using naas_drivers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_bulleted_list_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_bulleted_list_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "788383d93e10f1f9b502ed7ff62013a2bf073f2cfeac45af26371468ddfdd8b1", "tool": "Notion", "notebook": "Add code block in page", "action": "", "tags": ["#notion", "#code", "#page", "#organization", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-30", "created_at": "2023-04-30", "description": "This notebook explains how to add a code block in a Notion page using naas_drivers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_code_block_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_code_block_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "bb1c62a68b1e8bed37eb699e857a6e8c1670d91567737b8a3840184e186ff29d", "tool": "Notion", "notebook": "Add cover image to page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook allows you to add a cover image to a page in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_cover_image_to_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_cover_image_to_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "931f3ae1a90765ff01a284401428ad56c74361da0b992df5a610e52026fd44c4", "tool": "Notion", "notebook": "Add equation in page", "action": "", "tags": ["#notion", "#equation", "#page", "#organization", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-30", "created_at": "2023-04-30", "description": "This notebook explains how to add an equation in a Notion page using naas_drivers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_equation_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_equation_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "d0f211ded04e761c43109a9fbfd6aec9e38174a7ed52fe67e1a08acf1ebdbe25", "tool": "Notion", "notebook": "Add heading in page", "action": "", "tags": ["#notion", "#heading", "#page", "#organization", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-30", "created_at": "2023-04-30", "description": "This notebook explains how to add headings in a Notion page using naas_drivers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_heading_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_heading_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "c4808da990d67ce7069e2d1f01e33141b6d6609af3c3bb90fe732ce8dc98ae8f", "tool": "Notion", "notebook": "Add icon image to page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook allows users to add an icon image to a Notion page.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_icon_image_to_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_icon_image_to_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "93987b3107b56dd9a02b79dcba1e47e3af68eaba6f0492e3eb8de9e42684400a", "tool": "Notion", "notebook": "Add new github member to team from database", "action": "", "tags": ["#github", "#teams", "#automation", "#notion", "#operations"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-05-21", "description": "This notebook allows users to add new GitHub members to their team from a database in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_new_github_member_to_team_from_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_new_github_member_to_team_from_database.ipynb", "imports": ["requests", "naas_drivers.github, notion", "naas", "pandas"], "image_url": ""}, {"objectID": "56ee3de913cfdbf390142378217d08ff30cf5c01c780d9811b8a15593e60e2a4", "tool": "Notion", "notebook": "Add numbered list in page", "action": "", "tags": ["#notion", "#list", "#page", "#organization", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-30", "created_at": "2023-04-30", "description": "This notebook explains how to add a numbered list in a Notion page from a list object using naas_drivers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_numbered_list_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_numbered_list_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "d23f9df5b983b569726995526e7659c222c8899834f4b7b5b0e5a79f7ca0bd8a", "tool": "Notion", "notebook": "Add paragraph with link in page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#block", "#paragraph", "#link", "#snippet", "#operations"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-03-17", "description": "This notebook allows you to add a paragraph with a link to a page in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_paragraph_with_link_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_paragraph_with_link_in_page.ipynb", "imports": ["naas_drivers.notion", "naas_drivers.tools.notion.Link"], "image_url": ""}, {"objectID": "a325c9e4b91d0842ed3a531aaf5e9e21c0ff0652bab97a3f95a3eb62cc3ffd1a", "tool": "Notion", "notebook": "Add to do list in page", "action": "", "tags": ["#notion", "#todo", "#page", "#snippet", "#naas_drivers"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-28", "created_at": "2023-04-28", "description": "This notebook explains how to add a to do list in a Notion page using naas_drivers from a list.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Add_to_do_list_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Add_to_do_list_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "97611fe6842bbe2afb50f53ddebbffd33454595b869913c9d6249105197b4530", "tool": "Notion", "notebook": "Automate transcript generation from recording link in page property", "action": "", "tags": ["#notion", "#aws", "#transcribe", "#S3", "#automation"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-05-12", "description": "This notebook allows users to automatically generate transcripts from audio recordings by linking the recording to a page property in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Automate_transcript_generation_from_recording_link_in_page_property.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Automate_transcript_generation_from_recording_link_in_page_property.ipynb", "imports": ["pydash", "threading, queue", "uuid", "rich.print", "rich.print", "sys", "json", "datetime", "codecs", "time", "os", "markdown", "gdown", "gdown", "boto3", "naas_drivers.notion", "naas_drivers.tools.notion.BlockTypeFactory", "naas"], "image_url": ""}, {"objectID": "7597da846b5c5a212d1fe3763deaf09315f9358b9b04523cbea93045eba467e1", "tool": "Notion", "notebook": "Create page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-09-13", "description": "Notion is a powerful tool for creating and organizing digital pages to help you stay organized and productive.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Create_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Create_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "429365440a90db93a370330df99e41a4718d24029f7a2a3e24990304ce409614", "tool": "Notion", "notebook": "Create pages in database from dataframe", "action": "", "tags": ["#notion", "#database", "#dataframe", "#python", "#create", "#pages"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-15", "description": "This notebook will show how to create pages in Notion database from a dataframe. It could be very usefull to kick start a new database in Notion with historical data stored in CSV, Excel or Google Sheets.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Create_pages_in_database_from_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Create_pages_in_database_from_dataframe.ipynb", "imports": ["naas", "pandas", "naas_drivers.notion"], "image_url": ""}, {"objectID": "bf17bd2f86490d3fbed728c4a602153d357748a2ab81f5e3385f32c116d6fd78", "tool": "Notion", "notebook": "Delete all pages from database", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#database"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-24", "description": "This notebook deletes all page from a Notion database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Delete_all_pages_from_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Delete_all_pages_from_database.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "458696751173998a5878523a07bf2866a1d97db0aae077ae663183415f6c7178", "tool": "Notion", "notebook": "Delete blocks from page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#page"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook allows users to quickly and easily delete blocks from their Notion page.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Delete_blocks_from_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Delete_blocks_from_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "4be524b722d7eabf85ecb8dcda5e06cd8559567a9c5ccb55eba8915fb982f337", "tool": "Notion", "notebook": "Delete page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#page"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook allows you to delete a page in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Delete_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Delete_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "47be8362b5f8f8d9db5c0a9dfbc4f912f4f4593f332adfb7f9ae174fceb42ce5", "tool": "Notion", "notebook": "Duplicate page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#duplicate", "#page"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-05-26", "description": "This notebook allows you to quickly and easily duplicate a page in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Duplicate_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Duplicate_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "80547ec83f52f9ee3c926af6f709f3d25b583d2d6d2f4be6d6c7a60f0106f5d5", "tool": "Notion", "notebook": "Explore API", "action": "", "tags": ["#notion", "#productivity", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-08-04", "description": "This notebook provides an exploration of the Notion API, allowing users to access and manipulate data from Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Explore_API.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Explore_API.ipynb", "imports": ["requests", "pandas", "json"], "image_url": ""}, {"objectID": "98ab1c462dc32c96d8a60d3f8fa617498096792f891ac48924fc03d4b059d655", "tool": "Notion", "notebook": "Generate Google Sheets rows for new items in database", "action": "", "tags": ["#notion", "#operations", "#automation", "#googlesheets"], "author": "Pooja Srivastava", "author_url": "https://www.linkedin.com/in/pooja-srivastava-in/", "updated_at": "2023-04-12", "created_at": "2022-04-05", "description": "This notebook allows users to automatically generate Google Sheets rows for new items added to a database using Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Generate_Google_Sheets_rows_for_new_items_in_Notion_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Generate_Google_Sheets_rows_for_new_items_in_Notion_database.ipynb", "imports": ["naas_drivers.notion, gsheet", "pandas"], "image_url": ""}, {"objectID": "68a8540ec1e573bbc2c31b844cc383fa99b73ec2781df0f494fdb9f41965b46a", "tool": "Notion", "notebook": "Get blocks from page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#page"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook allows users to quickly and easily add blocks from a page to their Notion workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Get_blocks_from_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Get_blocks_from_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "7c5540e6853c6605a0a64c7bd1860d3bcf4b7843ecbae96ae22a318b4f2fa5dc", "tool": "Notion", "notebook": "Get database", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-08-23", "description": "Notion is a powerful database tool that helps you organize and store your data in an intuitive and efficient way.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Get_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Get_database.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "42775adb8e2a5be84c11094169c73f67378aa924d6030d5b0e5cdbcf84e84980", "tool": "Notion", "notebook": "Get page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet", "#page"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-08-16", "description": "This notebook allows you to quickly and easily create and organize webpages for any purpose.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Get_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Get_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "cf37eca2469767cb53d562a97383fb6cad12c0691fb3b44fabdbfc1030ec3d5d", "tool": "Notion", "notebook": "Get users", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-11-01", "description": "Notion is a powerful tool that helps users organize their thoughts, tasks, and projects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Get_users.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Get_users.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "77e598f0bed1b6807032066684a6b6aceed5057fd135e73b41791915c998bea3", "tool": "Notion", "notebook": "Send LinkedIn invitations from database", "action": "", "tags": ["#notion", "#invitation", "#automation", "#content", "#linkedin"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-04-07", "description": "This notebook allows users to quickly and easily send LinkedIn invitations to contacts stored in a database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Send_LinkedIn_invitations_from_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Send_LinkedIn_invitations_from_database.ipynb", "imports": ["naas", "naas_drivers.notion, linkedin", "pandas", "os", "datetime.datetime", "requests"], "image_url": ""}, {"objectID": "e07ad2e7f764a2bd25534ca5e6a87a54d39d7a73d4b297b21b44cc8a4e51518e", "tool": "Notion", "notebook": "Send Slack Messages For New Database Items", "action": "", "tags": ["#notion", "#slack", "#operations", "#automation"], "author": "Sanjeet Attili", "author_url": "https://api.slack.com/authentication/basics\n\n- For this use case we need to create & use user token, rather than bot token with the following permissions/scopes -> [channels: history, channels: read, chat: write, users: read]", "updated_at": "2023-04-12", "created_at": "2022-03-31", "description": "## Input", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Send_Slack_Messages_For_New_Notion_Database_Items.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Send_Slack_Messages_For_New_Notion_Database_Items.ipynb", "imports": ["naas_drivers.notion, slack", "naas"], "image_url": ""}, {"objectID": "906dd0ec9b68828a094cc58111e34dd14acf152e2491afde7116537297f31733", "tool": "Notion", "notebook": "Sent Gmail On New Item", "action": "", "tags": ["#notion", "#gsheet", "#productivity", "#naas_drivers", "#operations", "#automation", "#email"], "author": "Arun K C", "author_url": "https://www.linkedin.com/in/arun-kc/", "updated_at": "2023-04-12", "created_at": "2022-01-20", "description": "This notebook allows you to quickly send an email notification when a new item is added to Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Sent_Gmail_On_New_Item.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Sent_Gmail_On_New_Item.ipynb", "imports": ["naas", "naas_drivers.notion, gsheet", "naas_drivers.html", "pandas"], "image_url": ""}, {"objectID": "647d794df1c42fc8ef111f4ab6109a20bf4dd82da1279723111080e06d84f250", "tool": "Notion", "notebook": "Update database with GitHub repositories info", "action": "", "tags": ["#notion", "#database", "#update", "#github", "#repositories", "#automation", "#scheduler"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-13", "created_at": "2023-04-12", "description": "This notebook updates a Notion database with information from all repositories within your GitHub organization. The following data will be updated in your Notion database:\n- Name: The name of the repository.\n- GitHub URL: The URL for the repository on GitHub.\n- Description: A brief description of what the repository is for.\n- Default branch: The default branch for the repository (i.e., the branch that is checked out when someone first clones the repository).\n- Visibility: The visibility status of the repository (e.g., public, private, or internal).\n- Created date: The date when the repository was created.\n- Last updated date: The date when the repository was last updated.\n- Open Issues: The number of unresolved issues (i.e., bug reports, feature requests, or other tasks) in the repository.\n- Forks: The number of times the repository has been forked (i.e., copied to another GitHub account).\n- Stargazers: The number of GitHub users who have \"starred\" the repository (i.e., marked it as a favorite).\n- Size: The size of the repository in terms of disk space used.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_database_with_GitHub_repositories_info.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_database_with_GitHub_repositories_info.ipynb", "imports": ["naas", "naas_drivers.notion", "pandas", "re", "datetime.datetime", "os", "requests", "naas", "github"], "image_url": ""}, {"objectID": "3d62f956e5054214458eaa0d181bcdcf3eb6992b59688563cc9eeb75c60e0ed3", "tool": "Notion", "notebook": "Update database with LinkedIn company info", "action": "", "tags": ["#notion", "#database", "#update", "#linkedin", "#company", "#automation", "#scheduler"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-13", "created_at": "2023-04-07", "description": "This notebook streamlines the process of updating a Notion database containing company names by extracting relevant information from LinkedIn using Google search, as well as utilizing Naas_Drivers.Notion and Naas_Drivers.LinkedIn.The following data will be updated in your Notion database:\n- Name: The name of the company or organization.\n- LinkedIn: The company's LinkedIn page.\n- Website: The company's website URL.\n- Industry: The industry or industries that the company operates in.\n- Specialties: The areas of expertise or specialization for the company or its products/services.\n- Tagline: A brief statement that summarizes the purpose or mission of the company or organization.\n- City: The city or cities where the company is headquartered or operates.\n- Country: The country where the company is headquartered or operates.\n- Staff Count: The number of employees or staff members employed by the company.\n- Staff Range: The range of employee count (e.g., 1-10, 11-50, 51-200, etc.) that the company falls into.\n- Followers: The number of LinkedIn users who follow the company's page or profile.\n\nOverall, this notebook can be useful for any business or individual who needs to keep track of company information for various purposes:\n- Sales prospecting: Sales teams could use the updated database to identify potential new leads and target them with personalized outreach based on their company information.\n- Competitor analysis: Marketers could use the updated database to track changes in their competitors' company information, such as changes in leadership or expansion into new markets.\n- Industry research: Researchers could use the updated database to gather information on companies within a particular industry, such as their size, location, and areas of expertise.\n- Investor relations: Investors could use the updated database to identify potential investment opportunities and track the performance of companies they are interested in.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_database_with_LinkedIn_company_info.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_database_with_LinkedIn_company_info.ipynb", "imports": ["naas", "naas_drivers.linkedin, notion", "googlesearch.search", "googlesearch.search", "re", "datetime.datetime", "os", "requests", "pandas", "time"], "image_url": ""}, {"objectID": "1033382f0063e3cfe04100c99b1780a7eda0ca450d3e26f634e50217db5c1f0d", "tool": "Notion", "notebook": "Update database with LinkedIn profile info", "action": "", "tags": ["#notion", "#database", "#update", "#linkedin", "#company", "#automation", "#scheduler"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-13", "created_at": "2023-04-13", "description": "This notebook streamlines the process of updating a Notion database containing profile names by extracting relevant information from LinkedIn using Google search, as well as utilizing Naas_Drivers.Notion and Naas_Drivers.LinkedIn. The following data will be updated in your Notion database:\n- Name: The name of the person who owns the LinkedIn profile.\n- LinkedIn: LinkedIn unique URL\n- Occupation: The job or profession that a person is engaged in, listed on their LinkedIn profile.\n- Industry: The field or sector in which a person works, listed on their LinkedIn profile.\n- City: The specific city where a person lives or works, listed on their LinkedIn profile.\n- Region: A broader geographic area that a person's city may be located in, such as a state or province, listed on their LinkedIn profile.\n- Country: The nation where a person is located or from, listed on their LinkedIn profile.\n- Location: The overall geographic location of a person, which may include their city, region, and country, listed on their LinkedIn profile.\nAdditionally, the background picture will be refreshed as the page cover, the profile picture will serve as the page icon, and the occupation and summary will be included in the page block.\n\nOverall, this notebook can be useful for any business or individual who needs to keep track of company information for various purposes:\n- Lead generation: Sales teams could use the updated Notion database to identify potential leads based on their LinkedIn profiles, and initiate targeted outreach to convert them into customers.\n- Talent sourcing: Recruiters could use the updated Notion database to find and evaluate potential job candidates based on their LinkedIn profiles and relevant information stored in the database.\n- Social media marketing: Marketers could use the updated Notion database to build custom audiences for their social media campaigns based on the information stored in the database and on LinkedIn.\n\nDisclamer:\n\nWhen using this script to scrape profiles from LinkedIn, it's important to set a limit on the number of API calls made to avoid being temporarily banned. LinkedIn heavily monitors scraping activities, and excessive usage can result in a ban. We recommend setting a limit of no more than 5 calls per hour to minimize the risk of being banned. As the owner of the script, it's your responsibility to use it responsibly and abide by LinkedIn's terms of service. We assume no liability for any consequences resulting from your use of this script.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_database_with_LinkedIn_profile_info.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_database_with_LinkedIn_profile_info.ipynb", "imports": ["naas", "naas_drivers.linkedin, notion", "googlesearch.search", "googlesearch.search", "re", "datetime.datetime", "os", "requests", "pandas", "time"], "image_url": ""}, {"objectID": "43d0796ae3f58df0ec5a640ddf8e9f266d824f70fa69f7c5040b370b38891ce0", "tool": "Notion", "notebook": "Update page", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-11-01", "description": "This page allows you to update existing content in Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_page.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "235b5d348b55afe007e3513452df95b030d2cc3d20d5b5fcb660fca90b2bb5cc", "tool": "Notion", "notebook": "Update page relation", "action": "", "tags": ["#notion", "#update", "#page", "#relation", "#requests", "#api"], "author": "Florent Ravenel", "author_url": "https://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-24", "created_at": "2023-04-24", "description": "This notebook will show how to update page relation using requests. It is usefull for organization to link different database in Notion and keep track of their data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_page_relation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_page_relation.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "0f1c3555b4539891a61581be2563e3fd819cdb141143895228ae433671329520", "tool": "Notion", "notebook": "Update pages from database", "action": "", "tags": ["#notion", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-02-07", "description": "This notebook allows users to easily update Notion pages with data from a database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Update_pages_from_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Update_pages_from_database.ipynb", "imports": ["naas_drivers.notion"], "image_url": ""}, {"objectID": "f31df883dd65a1a2a6c484ade655deba402bdba6d0e39ad0c1c39134cd906e05", "tool": "Notion", "notebook": "Upload PDF in page", "action": "", "tags": ["#notion", "#upload", "#pdf", "#page", "#snippet", "#naas_drivers"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-28", "created_at": "2023-04-28", "description": "This notebook explains how to upload a PDF in a Notion page using naas_drivers. It is usefull for organizations that need to share PDFs to their Notion pages.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Upload_PDF_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Upload_PDF_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "07b01cd0416973045c2e923af3028b3a426dc84dfc193499ee839e0e47bedaba", "tool": "Notion", "notebook": "Upload image in page", "action": "", "tags": ["#notion", "#upload", "#image", "#page", "#snippet", "#naas_drivers"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-28", "created_at": "2023-04-28", "description": "This notebook explains how to upload an image in a Notion page using naas_drivers. It is usefull for organizations that need to add visuals to their Notion pages.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Upload_image_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Upload_image_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "c0cc2a6a750077e302585962ecee4b2ae5eb1195392b4b4477497044184b4bb2", "tool": "Notion", "notebook": "Upload video in page", "action": "", "tags": ["#notion", "#upload", "#video", "#page", "#snippet", "#naas_drivers"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-28", "created_at": "2023-04-28", "description": "This notebook explains how to upload a video in a Notion page using naas_drivers. It is usefull for organizations that need to add videos to their Notion pages.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Notion/Notion_Upload_video_in_page.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Notion/Notion_Upload_video_in_page.ipynb", "imports": ["naas_drivers.notion", "naas"], "image_url": ""}, {"objectID": "977ec013ec588028ac032ba6a88411db2b70ed9108e892a74d52b4bacec388ac", "tool": "OS", "notebook": "Access environment variable", "action": "", "tags": ["#python", "#environment", "#variables", "#os", "#environ", "#object", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook explains how to access a particular environment variable using the Python `os.environ` object. Environment variables are useful in several ways:\n- Portability: Environment variables are independent of the code and can be easily ported across systems. This means that you can define an environment variable once, and use it in multiple scripts, applications, or systems without having to hardcode the variable's value.\n- Security: Environment variables can be used to store sensitive information like passwords or API keys, which can be accessed by the code without exposing them in the script. This is particularly useful when you need to deploy your code to a server or share it with others.\n- Flexibility: Environment variables allow you to change the behavior of your code without modifying the code itself. This is useful when you need to modify the behavior of your code based on different scenarios, such as development, testing, or production environments.\n- Configuration: Environment variables can be used to configure your code, by providing default values for variables that can be overridden by environment variables. This makes your code more flexible and easier to customize.\n\nOverall, environment variables are a useful tool for managing configuration settings and sensitive information in your code, and can make your code more portable, secure, and flexible.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Access_environment_variable.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Access_environment_variable.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "7bb2bd353adc40ef26a95c190775b078cdc6c910196b17c68f2f8b700bcaa585", "tool": "OS", "notebook": "Add new environment variable", "action": "", "tags": ["#python", "#environment", "#variables", "#os", "#environ", "#object", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook explains how to add or update variables in environment using the Python `os.environ` object. Environment variables are useful in several ways:\n- Portability: Environment variables are independent of the code and can be easily ported across systems. This means that you can define an environment variable once, and use it in multiple scripts, applications, or systems without having to hardcode the variable's value.\n- Security: Environment variables can be used to store sensitive information like passwords or API keys, which can be accessed by the code without exposing them in the script. This is particularly useful when you need to deploy your code to a server or share it with others.\n- Flexibility: Environment variables allow you to change the behavior of your code without modifying the code itself. This is useful when you need to modify the behavior of your code based on different scenarios, such as development, testing, or production environments.\n- Configuration: Environment variables can be used to configure your code, by providing default values for variables that can be overridden by environment variables. This makes your code more flexible and easier to customize.\n\nOverall, environment variables are a useful tool for managing configuration settings and sensitive information in your code, and can make your code more portable, secure, and flexible.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Add_new_environment_variable.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Add_new_environment_variable.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "141f931922bdd2a673d198df328243e7aed56d0ecd1f1c4c83a1b08a2ba263f5", "tool": "OS", "notebook": "Check path exist", "action": "", "tags": ["#os", "#python", "#path", "#file", "#system", "#library", "#snippet", "#operations", "#check"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-08", "created_at": "2023-06-08", "description": "This notebook will show how to check a path exist using os library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Check_path_exist.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Check_path_exist.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "86ee474d174e9f2394b370c69bd4c0de68646b8b9c45c02cbce83cf4edde0a74", "tool": "OS", "notebook": "Create directory", "action": "", "tags": ["#os", "#snippet", "#python", "#operations"], "author": "Moemen Ebdelli", "author_url": "https://www.linkedin.com/in/moemen-ebdelli", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook provides instructions on how to create a directory in Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Create_directory.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Create_directory.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "2eca9945533598a7b77fba6dd42d083942103cf78ce933470cfdedc5f385d6da", "tool": "OS", "notebook": "Get access of environment variables", "action": "", "tags": ["#python", "#environment", "#variables", "#os", "#environ", "#object"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook explains how to use of `os.environ` to get access of environment variables. Environment variables are useful in several ways:\n- Portability: Environment variables are independent of the code and can be easily ported across systems. This means that you can define an environment variable once, and use it in multiple scripts, applications, or systems without having to hardcode the variable's value.\n- Security: Environment variables can be used to store sensitive information like passwords or API keys, which can be accessed by the code without exposing them in the script. This is particularly useful when you need to deploy your code to a server or share it with others.\n- Flexibility: Environment variables allow you to change the behavior of your code without modifying the code itself. This is useful when you need to modify the behavior of your code based on different scenarios, such as development, testing, or production environments.\n- Configuration: Environment variables can be used to configure your code, by providing default values for variables that can be overridden by environment variables. This makes your code more flexible and easier to customize.\n\nOverall, environment variables are a useful tool for managing configuration settings and sensitive information in your code, and can make your code more portable, secure, and flexible.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Get_access_of_environment_variables.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Get_access_of_environment_variables.ipynb", "imports": ["os", "pprint"], "image_url": ""}, {"objectID": "c7bf168e0033b04e424d24283c3804f677d20958b8a7519e60e69f4a176cddc1", "tool": "OS", "notebook": "Get current working directory", "action": "", "tags": ["#os", "#python", "#snippet", "#operations", "#operatingsystem"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook demonstrates how to get the current working directory using `os` module. The main purpose of the OS module is to interact with your operating system. The primary use I find for it is to create folders, remove folders, move folders, and sometimes change the working directory. You can also access the names of files within a file path by doing listdir(). We do not cover that in this video, but that's an option.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Get_current_working_directory.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Get_current_working_directory.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "9527abdf0d80d051bbee0006c3948f220d4254591ef205fbd310d2e5f672e8e3", "tool": "OS", "notebook": "Get folder stats", "action": "", "tags": ["#os", "#folder", "#stats", "#python", "#library", "#filesystem"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-05", "created_at": "2023-07-05", "description": "This notebook will get the stats of a folder and its content.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Get_folder_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Get_folder_stats.ipynb", "imports": ["os", "datetime.datetime"], "image_url": ""}, {"objectID": "17ab0d4319f5f16b54359cb73279a21fea85248f5b54e3e982edc251fe0735df", "tool": "OS", "notebook": "List entries in directory", "action": "", "tags": ["#os", "#listdir", "#directory", "#python", "#entries", "#list"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-13", "created_at": "2023-06-13", "description": "This notebook explains how to use the Python method listdir() to list entries in a directory. It is usefull for organizations to quickly access the content of a directory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_List_entries_in_directory.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_List_entries_in_directory.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "fa208f2a6760c8f1d61394c59eb08948b2421d0ca23668df0927b40b12a0ee11", "tool": "OS", "notebook": "Remove file", "action": "", "tags": ["#os", "#python", "#remove", "#file", "#system", "#library", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook will show how to remove file from system using os library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Remove_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Remove_file.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "41e782306e5647529deb821db88d07feef810caef4389f00189aaaf47a7207c8", "tool": "OS", "notebook": "Rename file", "action": "", "tags": ["#os", "#python", "#snippet", "#operations"], "author": "Divakar", "author_url": "https://www.linkedin.com/in/divakar-r-9b34b86b/", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook will show how to rename file using os library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OS/OS_Rename_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OS/OS_Rename_file.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "b536a539006dced496f5dee0a0054d535f4880f440631c3b26f6f8d5f626c7d6", "tool": "OWID", "notebook": "Visualize GDP per capita through the years", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's GDP per capita data. The values are calculated by taking the expenditure-side real GDP at chained PPPs and dividing by the population.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_GDP_per_capita_through_the_years.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_GDP_per_capita_through_the_years.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "6e7757204de2a51a6e8288197ddf9daa841e3eb0df0cbf09e51e26d7ed655035", "tool": "OWID", "notebook": "Visualize Human Development Index", "action": "", "tags": ["#owid", "#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-08-07", "created_at": "2023-08-07", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's HDI data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_Human_Development_Index.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_Human_Development_Index.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "efd4c086cffe158c960a2bc7ea8dc9f71663b0deca619bccc47ec7ce81729245", "tool": "OWID", "notebook": "Visualize oil consumption throughout the years", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-06-26", "created_at": "2023-06-26", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's oil consumption data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_Oil_Consumption_through_the_Years.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_Oil_Consumption_through_the_Years.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "4b06d4ef00af69ff2b94b5dd3745d5d6b9d2544014f0e2f317599a3a4174f360", "tool": "OWID", "notebook": "Visualize Population of Different Age Groups", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-08-04", "created_at": "2023-07-12", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's popultion by age group data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_Population_of_Different_Age_Groups.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_Population_of_Different_Age_Groups.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express", "naas"], "image_url": ""}, {"objectID": "7db31d10c4b5b92d0d39f1d3dc6ee14dc4e511f4718304f9cfb63394215ce6e8", "tool": "OWID", "notebook": "Visualize economic freedom through the years", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's economic freedom ranking data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_economic_freedom_through_the_years.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_economic_freedom_through_the_years.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "54dbdfd194259317e5cc940745c978c24d6b9369f598c3db583326036b883167", "tool": "OWID", "notebook": "Visualize greenhouse gas per capita", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's greenhouse gas emissions per capita data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_greenhouse_gas_per_capita.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_greenhouse_gas_per_capita.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "cc3affc15c3291bab55e3463dfad9686c656e095970dbcfdce0e1000938d1b0e", "tool": "OWID", "notebook": "Visualize Life expectancy at birth for both sexes throughout the years", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's life exepctancy data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_life_expectancy_at_birth_for_both_sexes_through_out_the_years.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_life_expectancy_at_birth_for_both_sexes_through_out_the_years.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "cdf2fb54787b4191d2516b1cc6e7000a531dfa63a2142118ccd6c91cf6435684", "tool": "OWID", "notebook": "Tourist depature per 1000", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's tourist departures per 1000 data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_tourist_departures_per_1000.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_tourist_departures_per_1000.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "304c492a6ad755b2370ccec6705ca275e6fd9dd894580e1e4f7663bb73341059", "tool": "OWID", "notebook": "Visualize wealth distribuition of certain major economic powers", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-07-31", "created_at": "2023-07-31", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's wealth distribution data. It shows the percentage of personal wealth obtained by the top 1% and the top 10%.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_wealth_distribution.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_wealth_distribution.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "b0de207f2a64ae314c14994522d6994a3c3cbae7fc6d5b79be15da7d8e223d0e", "tool": "OWID", "notebook": "Visualize world population growth", "action": "", "tags": ["#dash", "#dashboard", "#plotly", "#naas", "#asset", "#analytics", "#dropdown", "#callback", "#bootstrap", "#snippet"], "author": "Zihui Ouyang", "author_url": "https://www.linkedin.com/in/zihui-ouyang-539626227/", "updated_at": "2023-08-07", "created_at": "2023-08-07", "description": "This notebook creates an interactive plot using Dash app infrastructure with OWID's world population growth data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OWID/OWID_Visualize_world_population_growth.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OWID/OWID_Visualize_world_population_growth.ipynb", "imports": ["dash", "os", "dash", "dash_bootstrap_components", "dash_bootstrap_components", "pandas", "numpy", "dash.Dash, html, dcc, callback, Output, Input", "plotly.express"], "image_url": ""}, {"objectID": "dd67e8c7161225db2d49f17a8c6a4a6cc7271cedae8a67457fd0c8f93a77fe27", "tool": "OpenAI", "notebook": "Act as a AI enthusiast", "action": " ", "tags": ["#ai", "#aienthusiast", "#artificialintelligence", "#aitrends", "#aiconcepts", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as an AI enthusiast.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_AI_enthusiast.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_AI_enthusiast.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_AI_enthusiast.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "e089ce867bca0f37f131ec352c85601eff2db8edd0911052eac3475fc655090e", "tool": "OpenAI", "notebook": "Act as a Business Analyst", "action": " ", "tags": ["#ai", "#businessanalyst", "#businessdata", "#businessprocess", "#strategicrecommendations", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Business Analyst.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Business_Analyst.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Business_Analyst.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Business_Analyst.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "fd738792e7b58c349a01bc30c83d122ce30392568a232eda55191d80dc6814d9", "tool": "OpenAI", "notebook": "Act as a CEO", "action": " ", "tags": ["#ai", "#ceo", "#businessstrategy", "#leadership", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a CEO.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_CEO.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_CEO.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_CEO.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "3e28fb1c0bcee19d8c363e9e8addc7cee4ad8969a4f6c9921f2a3e8ce96b9e83", "tool": "OpenAI", "notebook": "Act as a COO", "action": " ", "tags": ["#ai", "#coo", "#operationsmanagement", "#processimprovement", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a COO.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_COO.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_COO.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_COO.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "eec5d99cbc73d38ea2e7400ca902510b35ec5ebdbe153092031f147f43267fbc", "tool": "OpenAI", "notebook": "Act as a CTO", "action": " ", "tags": ["#ai", "#cto", "#technologystrategy", "#innovation", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a CTO.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_CTO.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_CTO.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_CTO.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "65dc3f7dae157ebebe828bd8061d78213f87fc22fc9fd49d327c35513ec477cd", "tool": "OpenAI", "notebook": "Act as a Creative Writer or Artist", "action": " ", "tags": ["#ai", "#creativewriter", "#artist", "#creativity", "#artistictechniques", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Creative Writer or Artist.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Creative_Writer_or_Artist.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Creative_Writer_or_Artist.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Creative_Writer_or_Artist.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "1afec4ff0f173c25314065d105a85838b48804ff47595ce2444ccfb5ca26fcb6", "tool": "OpenAI", "notebook": "Act as a Data Analyst", "action": " ", "tags": ["#ai", "#dataanalyst", "#datadrivendecisions", "#datamining", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Data Analyst.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Data_Analyst.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Data_Analyst.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Data_Analyst.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "a6c10ae13d722f012562c528deb87b8e69e98b94554d16adbd3f38269cbe5b51", "tool": "OpenAI", "notebook": "Act as a Data Scientist", "action": " ", "tags": ["#ai", "#datascientist", "#predictivemodels", "#machinelearning", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Data Scientist.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Data_Scientist.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Data_Scientist.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Data_Scientist.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "55fd10670c15ad9320e3aa49bcb93b4c066c52f0cf509efd9fc98c280d6ddfe7", "tool": "OpenAI", "notebook": "Act as a Educator or student", "action": " ", "tags": ["#ai", "#educator", "#student", "#academictopics", "#teachingstrategies", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as an Educator or Student.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Educator_or_student.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Educator_or_student.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Educator_or_student.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "55eae5ebdc323c73316e2e081956e9eac4bbeb2a0839a125a3cfe59b862194ca", "tool": "OpenAI", "notebook": "Act as a Hobbyist", "action": " ", "tags": ["#ai", "#hobbyist", "#personalprojects", "#hobbyimprovement", "#skilllearning", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Hobbyist.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Hobbyist.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Hobbyist.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Hobbyist.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "940a2ff7ae284b98d7de3461aa5d1e39e7f81da8c48e3625eee2a2f0489a1733", "tool": "OpenAI", "notebook": "Act as a Homeowner", "action": " ", "tags": ["#ai", "#homeowner", "#homeimprovement", "#homemaintenance", "#interiordesign", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Homeowner.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Homeowner.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Homeowner.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Homeowner.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "43d678efc249da05fe4325e50508c8b2b8daa6223fbb14959a550c6266f8ae6f", "tool": "OpenAI", "notebook": "Act as a IT Professional", "action": " ", "tags": ["#ai", "#itprofessional", "#technicalsupport", "#itinfrastructure", "#ittrends", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as an IT Professional.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_IT_Professional.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_IT_Professional.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_IT_Professional.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "99f62044e567ead43fe936c1e72f88cd37d15b79a0c89cca5a9e21c00ef98a13", "tool": "OpenAI", "notebook": "Act as a Lifelong learner", "action": " ", "tags": ["#ai", "#lifelonglearner", "#knowledgeseeker", "#skilllearning", "#subjectexploration", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Lifelong Learner.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Lifelong_learner.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Lifelong_learner.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Lifelong_learner.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "f54c6d7a2daa62c82a631fa4ab51c338f914000cd3f1d19da7c969fff7d188a2", "tool": "OpenAI", "notebook": "Act as a Marketer", "action": " ", "tags": ["#ai", "#marketer", "#marketingstrategy", "#markettrends", "#brandengagement", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Marketer.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Marketer.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Marketer.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Marketer.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "084134f6feae47a6c539c638604e7d552f8893513c977ff459d76fced826328e", "tool": "OpenAI", "notebook": "Act as a Parent or Child", "action": " ", "tags": ["#ai", "#parent", "#child", "#parentingchallenges", "#schoolwork", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Parent or Child.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Parent_or_Child.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Parent_or_Child.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Parent_or_Child.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "ca91e684a5fc178a0b1dbb80ab49c3e5386ce19b51eda90c63427cb68e6b5025", "tool": "OpenAI", "notebook": "Act as a Product Manager", "action": " ", "tags": ["#ai", "#productmanager", "#productdevelopment", "#marketresearch", "#userexperience", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Product Manager.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Product_Manager.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Product_Manager.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Product_Manager.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "24bd8cd6a348ded1f22936aec33f1a0522c76226c9a996dddd8c73dad98049f3", "tool": "OpenAI", "notebook": "Act as a Project Manager", "action": " ", "tags": ["#ai", "#projectmanager", "#projectplanning", "#resourcemanagement", "#riskmanagement", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Project Manager.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Project_Manager.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Project_Manager.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Project_Manager.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "3c3958d3f040b8f3d30c0d40b70f64c1af78aa46103f47a7d10b2c2af6072c7b", "tool": "OpenAI", "notebook": "Act as a Retiree", "action": " ", "tags": ["#ai", "#retiree", "#retirementactivities", "#newskills", "#retirementmanagement", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Retiree.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Retiree.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Retiree.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Retiree.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "bca43175667c72622b34f1fb4feac25f63315fda2ec00144181e56f6620145b4", "tool": "OpenAI", "notebook": "Act as a Sales Professional", "action": " ", "tags": ["#ai", "#salesprofessional", "#salesstrategies", "#customerrelations", "#salestechniques", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Sales Professional.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Sales_Professional.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Sales_Professional.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Sales_Professional.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "12d9e1e7fe7284ba1cd450267f66313c8eb3580426bcac8b44048910f6870162", "tool": "OpenAI", "notebook": "Act as a Software Developer", "action": " ", "tags": ["#ai", "#softwaredeveloper", "#coding", "#softwaredevelopment", "#programminglanguages", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Software Developer.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Software_Developer.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Software_Developer.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Software_Developer.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "1e73b76a7ed2ddd2004c409dcfa0e5b4d768f38ba91a690233b9fe071ec97e8a", "tool": "OpenAI", "notebook": "Act as a Software Engineer", "action": " ", "tags": ["#ai", "#softwareengineer", "#softwareengineering", "#systemdesign", "#scalability", "#optimization", "#plugin"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will create a plugin to act as a Software Engineer.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Software_Engineer.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_Software_Engineer.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_Software_Engineer.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "f35bc89e26b1b3cffbedd7e3dee835cbd5a12a497b536b2399f7c82462ec2953", "tool": "OpenAI", "notebook": "Act as a chef", "action": " ", "tags": ["#openai", "#chef", "#cooking", "#ai", "#machinelearning", "#deeplearning", "#plugin"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-19", "created_at": "2023-05-29", "description": "This notebook will create a plugin to act as a chef and use OpenAI to create delicious recipes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_chef.ipynb", "open_in_chat": "https://naas.ai/chat/use?plugin_url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Act_as_a_chef.ipynb", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Act_as_a_chef.ipynb", "imports": ["json", "naas"], "image_url": ""}, {"objectID": "2b4754fa5dd2c8e1691f721e48e3e11917c629c0fb2438ffd78503ee63e4bc57", "tool": "OpenAI", "notebook": "Brainstorm ideas", "action": "", "tags": ["#openai", "#brainstorm", "#ideas", "#ai", "#machinelearning", "#deeplearning"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will help brainstorm ideas on a specific topic using OpenAI.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Brainstorm_ideas.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Brainstorm_ideas.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "64991d5e7374c52b3e71bbb365667239daea4ce7f872425c483d7da87c59b9f0", "tool": "OpenAI", "notebook": "Count tokens with tiktoken", "action": "", "tags": ["#openai", "#tiktoken", "#count", "#token", "#tokens", "#cookbook"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-16", "created_at": "2023-06-16", "description": "This notebook shows how to count tokens used from a string with tiktoken to use OpenAI API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Count_tokens_with_tiktoken.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Count_tokens_with_tiktoken.ipynb", "imports": ["tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "af9a04ddc27f4c638f42e4ea923fc3a24aad1d38516af8f9dc4ad3b262d29647", "tool": "OpenAI", "notebook": "Create Completion", "action": "", "tags": ["#openai", "#gpt3", "#textcompletion", "#ai", "#machinelearning", "#deeplearning", "#nlp", "#datascience", "#artificialintelligence", "#tech", "#innovation", "#creativity"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-31", "created_at": "2023-02-06", "description": "This notebook guides you through the process of using OpenAI's Generative Pretrained Transformer 3 (GPT-3) model to build a text completion application. This notebook will show you how to fine-tune GPT-3 to generate text based on a given prompt, and then integrate it into a web application for easy usage. The end result will be a working text completion tool that can be used to generate new ideas, suggestions, or even entire texts with just a few inputs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Create_Completion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Create_Completion.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "ce29f2ffe243c1ea092cd43ea7e5e42e8d39d6180230ab0ab9db873d168cbb4b", "tool": "OpenAI", "notebook": "Create chat completion", "action": "", "tags": ["#openai", "#chat", "#completion", "#model", "#response", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-31", "created_at": "2023-05-12", "description": "This notebook creates a model response for the given chat conversation. It uses OpenAI's API to generate a response based on the conversation context. This is useful for organizations that need to generate automated responses to customer inquiries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Create_chat_completion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Create_chat_completion.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "80af0a91b7797150d190e1dbab405133c6fb5be12cf1043b33c2709ee7eacdaa", "tool": "OpenAI", "notebook": "Create chatbot", "action": "", "tags": ["#openai", "#chatbot", "#conversation", "#ai", "#nlp", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-31", "created_at": "2023-05-31", "description": "This notebook create a chat conversation with OpenAI based on the initial system information. To stop it, just write \"STOP\" in the user input section.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Create_chatbot.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Create_chatbot.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "c51c4610007ed74a0ecde9c8fd0a9fc269e96164e2ba4f6fe7fc971bf86943e6", "tool": "OpenAI", "notebook": "Generate_Act_as_a_x_notebook", "action": "", "tags": ["#openai", "#ai", "#machinelearning", "#deeplearning", "#notebooks", "#automation", "#gsheet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook creates \"Act as a ...\" notebooks from a Google Sheets spreadsheet using OpenAI_Act_as_a_chef.ipynb as template.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_Act_as_a_x_notebook.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_Act_as_a_x_notebook.ipynb", "imports": ["papermill.iorw.(", "naas", "naas_drivers.gsheet", "copy", "json", "subprocess"], "image_url": ""}, {"objectID": "00885f380a5e98de1dfc84407a532f4ee99e7db3944644806fe32800b7c70a17", "tool": "OpenAI", "notebook": "Generate Dialogue", "action": "", "tags": ["#openai", "#gpt", "#api", "#prompt"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-03-18", "description": "This template shows how to use the OpenAI API to generate responses to user input within a Naas notebook, allowing users to create interactive chatbots or dialogue systems.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_Dialogue.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_Dialogue.ipynb", "imports": ["naas", "openai", "openai"], "image_url": ""}, {"objectID": "388967283e9e6cc7c2fb3566e6e171bf2d3a1ec9a74ee315d6751e0efe6e850c", "tool": "OpenAI", "notebook": "Generate Q&A", "action": "", "tags": ["#openai", "#q&a"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-04-12", "created_at": "2023-03-16", "description": "This notebook shows how to use the OpenAI API to generate answer to a question.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_Q%26A.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_Q%26A.ipynb", "imports": ["naas", "os", "openai", "openai"], "image_url": ""}, {"objectID": "f4334e52da15c82c96fa2ba1ebc2a7e0e769de9f92ed2b06ff6db3e4ac828cb3", "tool": "OpenAI", "notebook": "Generate README for GitHub repository", "action": "", "tags": ["#openai", "#github", "#readme", "#repository", "#generate", "#automation"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-04-11", "description": "This notebook will generate a README for a GitHub repository based on the project name and description.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_README_for_GitHub_repository.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_README_for_GitHub_repository.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "5435d7164828670bd059f0d88f7fad45e8ccd8ed1ae0893b4685b6b3d5debbbd", "tool": "OpenAI", "notebook": "Generate Text to Speech", "action": "", "tags": ["#openai"], "author": "Sriniketh Jayasendil", "author_url": "http://linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-02-10", "description": "This notebook focusses on using OpenAI for text-to-speech generation using [gTTS](https://pypi.org/project/gTTS/)", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_Text_to_Speech.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_Text_to_Speech.ipynb", "imports": ["os", "naas", "openai", "openai", "gtts.gTTS", "gtts.gTTS"], "image_url": ""}, {"objectID": "7c89c1b529294dde50d26637c99788c03044af0f901bd4986f554996a3e2e8f3", "tool": "OpenAI", "notebook": "Generate image from text", "action": "", "tags": ["#openai", "#image", "#text", "#generation"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel", "updated_at": "2023-06-09", "created_at": "2023-06-06", "description": "This notebook shows how to use the OpenAI API to make create images from text using Dall-E.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_image_from_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_image_from_text.ipynb", "imports": ["os", "openai # OpenAI Python library to make API calls", "requests # used to download images", "os # used to access filepaths", "PIL.Image # used to print and edit images", "naas # used to generate shareable image link", "openai"], "image_url": ""}, {"objectID": "60e910eeeaabf738f5c0852cc429357d0e707b935b2cd1fbbbae96d09e0ccca6", "tool": "OpenAI", "notebook": "Generate language translations", "action": "", "tags": ["#openai", "#language", "#translation", "#ai", "#translator", "#operations", "#snippet"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2023-02-05", "description": "This notebook translates a given text to a language of choice using OpenAI.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_language_translations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_language_translations.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "5e3fa80c5c4704e4070b51b8cc7f3b4cd631b82a81621d798a826780aa00e474", "tool": "OpenAI", "notebook": "Generate text based prediction", "action": "", "tags": ["#openai", "#prediction", "#text"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-04-12", "created_at": "2023-03-08", "description": "This notebook shows how to use the OpenAI API to make predictions based on text data", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_text_based_prediction.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_text_based_prediction.ipynb", "imports": ["os", "openai", "openai"], "image_url": ""}, {"objectID": "fd2a1ab9606a02f8b8004c754a617821290a3e99ba1f9c7e610be1423d93a261", "tool": "OpenAI", "notebook": "Generate text replacements", "action": "", "tags": ["#openai", "#text_replacement"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-04-12", "created_at": "2023-03-23", "description": "This notebook shows how to use the OpenAI API to generate text replacements such as correcting grammatical errors or making text more formal.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_text_replacements.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_text_replacements.ipynb", "imports": ["naas", "os", "openai", "openai"], "image_url": ""}, {"objectID": "2961a8fa985173e1fe7bc9ecd7dded9230b4249964c082484466ef3c7e8b95d5", "tool": "OpenAI", "notebook": "Generate text summaries", "action": "", "tags": ["#openai", "#text", "#summary"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-05-24", "created_at": "2023-05-24", "description": "This notebook shows how to use the OpenAI API to generate text summaries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Generate_text_summaries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Generate_text_summaries.ipynb", "imports": ["naas", "openai", "openai"], "image_url": ""}, {"objectID": "b9e07c5aa5d74211244f408194927ef89fa7cb5a191606fe230c798269d684f9", "tool": "OpenAI", "notebook": "Write a blog post", "action": "", "tags": ["#openai", "#blogpost", "#writing", "#ai", "#machinelearning", "#deeplearning"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will provide a step-by-step guide to writing a blog post using OpenAI.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Write_a_blog_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Write_a_blog_post.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "3afca0fde41d0b659bad065a920c3475ddfb1367a5df0fa4d2cb7a5a32143e49", "tool": "OpenAI", "notebook": "Write a job description", "action": "", "tags": ["#openai", "#jobdescription", "#writing", "#hiring", "#recruiting", "#position"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook provides a guide to write a job description for a specific position for your company.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Write_a_job_description.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Write_a_job_description.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "5b4533cb454ccc100d98e31d949ea6ba5d605e25d4f166a169bc1444facce745", "tool": "OpenAI", "notebook": "Write a press release", "action": "", "tags": ["#openai", "#pressrelease", "#writing", "#communication", "#publicrelations", "#journalism"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will provide a guide to write using OpenAI API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Write_a_press_release.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Write_a_press_release.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "96e1ff47c1c4011d1a31e25cba022771284016208eec7cdb625e49d2a326f65e", "tool": "OpenAI", "notebook": "Write a social media post", "action": "", "tags": ["#openai", "#socialmedia", "#post", "#prompt", "#tone", "#platform"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will create a prompt to write a social media post and be able to set the topic, the tone and the platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Write_a_social_media_post.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Write_a_social_media_post.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "77e886f6f04a14ced07e702a5722295c4ad6dd3ce080c11e25dd2f7d5cbc5874", "tool": "OpenAI", "notebook": "Write an outline", "action": "", "tags": ["#openai", "#outline", "#writing", "#topic", "#structure", "#organize"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-24", "description": "This notebook will provide an outline for writing a specific topic. An outline is a structured plan or framework that serves as a blueprint for organizing and presenting information in a clear and logical way. Outlines can be used for a variety of purposes, such as organizing an essay or research paper, preparing a speech or presentation, or planning a project.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAI/OpenAI_Write_an_outline.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAI/OpenAI_Write_an_outline.ipynb", "imports": ["openai", "openai", "naas"], "image_url": ""}, {"objectID": "29a4f52536d76475d169c74de659e2d0d3f557860ecc062b0374adbf28db05c2", "tool": "OpenAlex", "notebook": "Get lists of authors", "action": "", "tags": ["#openalex", "#api", "#entities", "#authors", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of authors from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_authors.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_authors.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "37dd53baf05766a23edd9b0c3d2efd0e35997d2ea98448c2649d27533c46348a", "tool": "OpenAlex", "notebook": "Get lists of concepts", "action": "", "tags": ["#openalex", "#api", "#entities", "#concepts", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of concepts from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_concepts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_concepts.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "0f7ad43306b5ffe0ac30096d2e74b67a4e2e968aba801e33bfb33de97dffc902", "tool": "OpenAlex", "notebook": "Get lists of funders", "action": "", "tags": ["#openalex", "#api", "#entities", "#funders", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of funders from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_funders.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_funders.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "daa55946917d46e91f745d8bb80015bb01c9b089f8d593cb295f068eba737713", "tool": "OpenAlex", "notebook": "Get lists of institutions", "action": "", "tags": ["#openalex", "#api", "#entities", "#institutions", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of institutions from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_institutions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_institutions.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "deac59c6ef3ad57a0c139099d6e1967888bf53c250eae9228230aacbcff5aa3e", "tool": "OpenAlex", "notebook": "Get lists of publishers", "action": "", "tags": ["#openalex", "#api", "#entities", "#publishers", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of publishers from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_publishers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_publishers.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "c7d44879bd6ddfd704a5edeea24d1aa2ad3f3a2f31e01e96559faa13274465b3", "tool": "OpenAlex", "notebook": "Get lists of sources", "action": "", "tags": ["#openalex", "#api", "#entities", "#sources", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of sources from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_sources.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_sources.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "c7d23e7145aa523f18b4b2d09a9c05ed3a857b0fc3a2fd9ad417256bed440d3c", "tool": "OpenAlex", "notebook": "Get lists of works", "action": "", "tags": ["#openalex", "#api", "#entities", "#works", "#get", "#lists"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook will show how to get lists of works from OpenAlex API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenAlex/OpenAlex_Get_lists_of_works.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenAlex/OpenAlex_Get_lists_of_works.ipynb", "imports": ["requests", "pandas"], "image_url": ""}, {"objectID": "4aba3ab8d023730a829408b7fa52a3ae14366326c9e47fa801a2384e5569c73d", "tool": "OpenBB", "notebook": "Create an kernel on Naas", "action": "", "tags": ["#openbb", "#naas", "#ipython", "#conda", "#kernel"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-01-11", "description": "This Jupyter Notebook will enable you to establish a new IPython Kernel that you can customize, allowing you to install any desired tools, here OpenBB. This kernel, once created, can be selected to run your notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenBB/OpenBB_Create_an_OpenBB_kernel_on_Naas.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenBB/OpenBB_Create_an_OpenBB_kernel_on_Naas.ipynb", "imports": [], "image_url": ""}, {"objectID": "bdebeee1fe5060091a5671ca9ea02112b9539ad2f8e26b584f668c3339c30745", "tool": "OpenPIV", "notebook": "Openpiv-python-template", "action": "", "tags": ["#piv", "#openpiv", "#fluidmechanics", "#openpiv-python"], "author": "Alex Liberzon", "author_url": "https://www.linkedin.com/in/alexliberzon/", "updated_at": "2023-04-12", "created_at": "2022-12-07", "description": "This notebook provides a template for using the open source Python library OpenPIV to analyze particle image velocimetry data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenPIV/openpiv-python-template.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenPIV/openpiv-python-template.ipynb", "imports": ["openpiv.tools, validation, filters, scaling, pyprocess", "numpy", "matplotlib.pyplot", "IPython.display.display", "ipywidgets.interact_manual, interactive, fixed, IntSlider, HBox, VBox, Layout", "openpiv.piv, tools", "ipywidgets.interact, interactive, fixed, interact_manual", "IPython.display.Image", "imageio", "skimage.img_as_uint"], "image_url": ""}, {"objectID": "84c4cccf44f66d7957f7c938252f5b5582637a13eed6818af52b2dbd038d582c", "tool": "OpenWeatherMap", "notebook": "Get City Weather", "action": "", "tags": ["#openweathermap", "#opendata", "#snippet", "#dataframe"], "author": "Christophe Blefari", "author_url": "https://www.linkedin.com/in/christopheblefari/", "updated_at": "2023-04-12", "created_at": "2021-07-21", "description": "This notebook provides an easy way to access current weather data for any city using the OpenWeatherMap API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenWeatherMap/OpenWeatherMap_Get_City_Weather.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenWeatherMap/OpenWeatherMap_Get_City_Weather.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "f4d4d561d540e27d1820edc3f73ffc5d3cffab1fb7d280c1c6fb8780c3804056", "tool": "OpenWeatherMap", "notebook": "Get City temperature weather-type wind-speed", "action": "", "tags": ["#openweathermap", "#opendata", "#snippet", "#dataframe"], "author": "Kanishk Pareek", "author_url": "https://in.linkedin.com/in/kanishkpareek", "updated_at": "2023-06-14", "created_at": "2022-10-06", "description": "This notebook helps to get the temperature and wind speed of your city by only giving the city as input.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenWeatherMap/OpenWeatherMap_Get_City_temperature_weather-type_wind-speed.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenWeatherMap/OpenWeatherMap_Get_City_temperature_weather-type_wind-speed.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "7ed1b4da0f14ddd2edc45c590983df0307cbbfe311cd4289de3e9d39765c6a41", "tool": "OpenWeatherMap", "notebook": "Send daily email with predictions", "action": "", "tags": ["#openweathermap", "#weather", "#plotly", "#prediction", "#email", "#naas_drivers", "#automation", "#opendata", "#analytics", "#ai", "#image", "#html", "#text"], "author": "Gautier Vivard", "author_url": "https://www.linkedin.com/in/gautier-vivard-1811b877/", "updated_at": "2023-04-12", "created_at": "2022-02-11", "description": "This notebook sends a daily email with weather predictions from OpenWeatherMap.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OpenWeatherMap/OpenWeatherMap_Send_daily_email_with_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OpenWeatherMap/OpenWeatherMap_Send_daily_email_with_predictions.ipynb", "imports": ["requests", "markdown2", "time", "pandas", "naas", "naas_drivers.plotly, prediction"], "image_url": ""}, {"objectID": "a01f17dcdd69a089120f8effd220d3a92241221e9c143270fe441934be4d8e67", "tool": "OwnCloud", "notebook": "Download file", "action": "", "tags": ["#owncloud", "#cloud", "#storage", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-08", "description": "This notebook allows users to download files from their OwnCloud account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OwnCloud/OwnCloud_Download_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OwnCloud/OwnCloud_Download_file.ipynb", "imports": ["naas", "owncloud"], "image_url": ""}, {"objectID": "80e640b22b8ac5254779988dbd2db06195ea2efa222ca5076c6cd225b76fb848", "tool": "OwnCloud", "notebook": "Upload file", "action": "", "tags": ["#owncloud", "#cloud", "#storage", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-08", "description": "This notebook allows users to securely upload files to their own personal cloud storage.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/OwnCloud/OwnCloud_Upload_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/OwnCloud/OwnCloud_Upload_file.ipynb", "imports": ["naas", "owncloud"], "image_url": ""}, {"objectID": "24264f1dc83845e25fdf023a95210e84987b196ef0a99dfd78a662d984443f96", "tool": "PDF", "notebook": "Extract Text from file", "action": "", "tags": ["#pdf", "#extract", "#snippet", "#operations", "#text"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-07-04", "created_at": "2022-10-03", "description": "This notebook extracts text from a PDF file in local or an URL.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PDF/PDF_Extract_Text_from_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PDF/PDF_Extract_Text_from_file.ipynb", "imports": ["io", "requests", "urllib.parse.urlparse", "urllib", "PyPDF2.PdfReader", "PyPDF2.PdfReader"], "image_url": ""}, {"objectID": "8bb6225a686349e47e170097cd65d15a077192613a84eeadafb1747d28342177", "tool": "PDF", "notebook": "Merge multiple documents", "action": "", "tags": ["#pdf", "#extract", "#snippet", "#operations", "#text"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-10-05", "description": "This notebook allows users to combine multiple PDF documents into a single file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PDF/PDF_Merge_multiple_PDF_documents.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PDF/PDF_Merge_multiple_PDF_documents.ipynb", "imports": ["io", "requests", "urllib.parse.urlparse", "PyPDF2.PdfFileReader, PdfFileWriter", "PyPDF2.PdfFileReader, PdfFileWriter"], "image_url": ""}, {"objectID": "260f8c6ceef5c7c165c4591bc6db22389b0eb540c849af035040ff3f31230c28", "tool": "PDF", "notebook": "Transform to MP3", "action": "", "tags": ["#pdf", "#text2audio", "#snippet", "#operations", "#mp3"], "author": "Sanjay Sabu", "author_url": "https://www.linkedin.com/in/sanjay-sabu-4205/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook converts PDF documents into MP3 audio files.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PDF/PDF_Transform_to_MP3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PDF/PDF_Transform_to_MP3.ipynb", "imports": ["io.StringIO", "pdfminer.converter.TextConverter", "pdfminer.layout.LAParams", "pdfminer.pdfdocument.PDFDocument", "pdfminer.pdfinterp.PDFResourceManager, PDFPageInterpreter", "pdfminer.pdfpage.PDFPage", "pdfminer.pdfparser.PDFParser", "gtts.gTTS"], "image_url": ""}, {"objectID": "5d27e3bd7fdfda696205d0e879b9a00e31ece1a64cae3c864ab22b006a0ab495", "tool": "Pandas", "notebook": "Apply custom styles on column", "action": "", "tags": ["#pandas", "#dataframe", "#style", "#column", "#apply", "#custom"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-25", "created_at": "2023-07-24", "description": "This notebook will show how to apply custom styles on a column of a Pandas DataFrame. It is usefull for data analysis and data visualization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Apply_custom_styles_on_column.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Apply_custom_styles_on_column.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "3f4e8e954fbc8a7f0e0ef3c8d8fc7e2296a180433067b08baee8d3258699f2fc", "tool": "Pandas", "notebook": "Check Columns type", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-11-29", "description": "This notebook checks columns in a dataframe. It could be very usefull to apply specific rules regarding columns format.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Check_Columns_type.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Check_Columns_type.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "1cdf0c27d04d84326ec48579541ee6ba9fb14172a2854e61231d11721984cea2", "tool": "Pandas", "notebook": "Check if column is in date format", "action": "", "tags": ["#pandas", "#dataframe", "#date", "#datetime", "#column", "#format"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-27", "created_at": "2023-06-13", "description": "This notebook will check if a column of a Pandas DataFrame is in date format. It is usefull for organizations to quickly check if a column is in the right format.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Check_if_column_is_in_date_format.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Check_if_column_is_in_date_format.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "01ec5aa3d067f1b4fe7b0e50d1a69fbffe59bb202fb9162ccdada4e82ef1174b", "tool": "Pandas", "notebook": "Concatenate dataframes", "action": "", "tags": ["#pandas", "#concatenate", "#dataframe", "#snippet", "#operations"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-30", "created_at": "2023-06-06", "description": "This notebook demonstrates how to concatenate dataframes across rows or columns using the Pandas library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Concatenate_dataframes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Concatenate_dataframes.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "3747b1ba5d9239ad75873c8918a7988f1253b0d87fe30db99b29078203d3fd2f", "tool": "Pandas", "notebook": "Convert datetime series", "action": "", "tags": ["#pandas", "#python", "#date", "#conversion", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2022-05-12", "description": "This notebook provides instructions on how to use the Pandas library to convert a datetime series into a usable format.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Convert_datetime_series.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Convert_datetime_series.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "9af61c9bfbaa205ab7a89d08fd076daa97551b36e768b0e2e388f71702a8d4e4", "tool": "Pandas", "notebook": "Create Pivot Table", "action": "", "tags": ["#pandas", "#pivot", "#operations", "#snippet", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-10-06", "description": "This notebook provides an example of how to use the Pandas library to create a pivot table.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Create_Pivot_Table.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Create_Pivot_Table.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "5dea1727d2325c2d39e0c97291eaad55fbaac39738b6f9870fcc25d9994de449", "tool": "Pandas", "notebook": "Create conditional column enrichment using DataFrame.loc", "action": "", "tags": ["#pandas", "#snippet", "#datenrichment", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-04", "created_at": "2023-06-04", "description": "This notebook demonstrates the practical application of `DataFrame.loc` for implementing conditions, enabling users to seamlessly enrich a DataFrame by generating new columns based on conditions derived from existing ones. Its versatility makes it an invaluable tool for DataFrame manipulation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Create_conditional_column_enrichment_using_DataFrame.loc.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Create_conditional_column_enrichment_using_DataFrame.loc.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "08aa6d5c2fcc85a4d1298f7c041485ceae994f6a8646b16f49dc3a1dd2c737c6", "tool": "Pandas", "notebook": "Create dataframe from dict", "action": "", "tags": ["#pandas", "#dict", "#snippet", "#dataframe", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-06-07", "created_at": "2022-03-07", "description": "This notebook provides a step-by-step guide to creating a dataframe from a dictionary using the Pandas library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Create_dataframe_from_dict.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Create_dataframe_from_dict.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "3b5664bbc6d912853acf24f4abd081bf5d0f7be6dc03b6c64adb8d2a0ef347af", "tool": "Pandas", "notebook": "Drop Columns By Index", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Sunny Chugh", "author_url": "https://www.linkedin.com/in/sunny-chugh-ab1630177/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook shows how to drop columns in Pandas DataFrame by index.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Drop_Columns_By_Index.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Drop_Columns_By_Index.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "9dc849f238938acd6d80c65a1dc602684a11c7650ba75ad919d1f36e183ceca1", "tool": "Pandas", "notebook": "Drop First column", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-11-28", "description": "This notebook shows how to drop First Column in Pandas DataFrame (3 Methods).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Drop_First_column.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Drop_First_column.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "10766514d077aaf045278657b7690bc7719fc6962cd9a47afe2312f1c3e9b91a", "tool": "Pandas", "notebook": "Drop columns", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook shows how to define a new DataFrame that drops columns defined in Input section.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Drop_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Drop_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "d6fb1e632b01ef9b6537987e8a40f196a59dbe2dc049961dbfaeeea7833d9f17", "tool": "Pandas", "notebook": "Drop duplicates", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Sunny Chugh", "author_url": "https://www.linkedin.com/in/sunny-chugh-ab1630177/", "updated_at": "2023-06-04", "created_at": "2023-06-04", "description": "This notebook shows how to drop duplicates in a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Drop_duplicates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Drop_duplicates.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "24261058569d9db319d5a70d1be2371ff1cc19b5b47bf391fdc996437e3d2506", "tool": "Pandas", "notebook": "Enforce data types to columns", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-04", "created_at": "2023-06-04", "description": "This notebook enforces specific data types to columns using Pandas, elevating your data consistency and accuracy. Availables types:\n- Numeric types: int, float, complex\n- Textual types: str\n- Date and time types: datetime, timedelta\n- Categorical types: category\n- Boolean type: bool\n- Object type: object", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Enforce_data_types_to_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Enforce_data_types_to_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "b412dd6032e5b39b130a8a012daaa8edda669ca6a9ff60187cdd86e1a8140a35", "tool": "Pandas", "notebook": "Fill emtpy values", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2022-11-29", "description": "This notebook fill empty values in dataframe columns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Fill_emtpy_values.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Fill_emtpy_values.ipynb", "imports": ["pandas", "numpy"], "image_url": ""}, {"objectID": "314b97f33ad0926c9bcdc4dd545c9bee424e648c6e041e35454f084d140fa51f", "tool": "Pandas", "notebook": "Filter DataFrame", "action": "", "tags": ["#pandas", "#dataframe", "#filter", "#python", "#dataanalysis"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-04", "created_at": "2023-03-02", "description": "This notebook will show how to filter a DataFrame using Pandas.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Filter_DataFrame.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Filter_DataFrame.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "17af8c0029b88a375ce0ca2eada983c97f6d6c0f4bab83a36a524026cc5e74d4", "tool": "Pandas", "notebook": "Flatten MultiIndex Columns", "action": "", "tags": ["#pandas", "#dataframe", "#multiindex", "#flatten", "#columns"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook explains how to flatten a MultiIndex column in a Pandas DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Flatten_MultiIndex_Columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Flatten_MultiIndex_Columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "58c0be4a754b9695c5d1bb790222ff5c3d8426dc0fa876d1f948fce48d4730c5", "tool": "Pandas", "notebook": "Format URL as clickable link on column", "action": "", "tags": ["#pandas", "#dataframe", "#url", "#link", "#column", "#format"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-24", "created_at": "2023-07-24", "description": "This notebook will show how to format a URL as a clickable link on a column of a Pandas DataFrame. This is usefull for organizations to quickly access to a website from a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Format_URL_as_clickable_link_on_column.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Format_URL_as_clickable_link_on_column.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "2ddb6eb54c1253c857cef66aeec26ee3d1fe3c61864951d3b23ca2dfda2f3cf6", "tool": "Pandas", "notebook": "Format number to string", "action": "", "tags": ["#pandas", "#dataframe", "#format", "#snippet", "#yahoofinance", "#naas_drivers", "#operations", "#jupyternotebooks"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an example of how to convert numerical values to strings using the Pandas library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Format_number_to_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Format_number_to_string.ipynb", "imports": ["naas_drivers.yahoofinance"], "image_url": ""}, {"objectID": "15c411f00d45474fa8f6c3e97c526d6e56dfd00b2dbebacafc15823ff5ea5618", "tool": "Pandas", "notebook": "Get n largest", "action": "", "tags": ["#pandas", "#dataframe", "#nlargest", "#python", "#data", "#analysis"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-14", "created_at": "2023-06-13", "description": "This notebook will demonstrate how to use the `nlargest` function in Pandas to get the n largest values from a DataFrame. This is useful for data analysis and data manipulation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Get_n_largest.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Get_n_largest.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "11148b2df16b8fc1df13c6aaa2928e94e1335bda5e3cb7410191d4772db14fc1", "tool": "Pandas", "notebook": "Get n smallest", "action": "", "tags": ["#pandas", "#dataframe", "#nsmallest", "#python", "#data", "#analysis"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-13", "created_at": "2023-06-13", "description": "This notebook explains how to use the `nsmallest` function from the Pandas library to get the n smallest values from column in a DataFrame.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Get_n_smallest.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Get_n_smallest.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "2f781b99d1e3e490fc5110f16be03119b1ab962d2b8ec93cfaf384332518ec74", "tool": "Pandas", "notebook": "Groupby and Aggregate", "action": "", "tags": ["#pandas", "#snippet", "#datamining", "#dataaggragation", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2022-11-30", "description": "This notebook groups and perform aggregation on columns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Groupby_and_Aggregate.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Groupby_and_Aggregate.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "bbc337a0d36c172e2e37ae7f50ffe79583936213893f036e3e538450012a1a46", "tool": "Pandas", "notebook": "ISO Date Conversion", "action": "", "tags": ["#pandas", "#python", "#date", "#conversion", "#isoformat", "#dateconversion", "#operations", "#snippet", "#dataframe"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-04-12", "created_at": "2021-10-06", "description": "This notebook provides a guide to converting ISO dates into Pandas-compatible formats.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_ISO_Date_Conversion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_ISO_Date_Conversion.ipynb", "imports": ["pandas", "dateutil.parser.parse"], "image_url": ""}, {"objectID": "dff9d7790f99b4c6981061774c7fcfc49b0814bc0b161ec88d96f69c857a6af2", "tool": "Pandas", "notebook": "Insert column", "action": "", "tags": ["#pandas", "#column", "#insert", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-04", "created_at": "2023-06-04", "description": "This notebook show how to insert column into DataFrame at specified location.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Insert_column.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Insert_column.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "c27a3508278911a39eefd92d7cbd38a4a34ff68c0ca048ad6a5871647f86af3d", "tool": "Pandas", "notebook": "Iterate over DataFrame rows", "action": "", "tags": ["#pandas", "#python", "#loops", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook demonstrates how to iterate over DataFrame rows as (index, Series) pairs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Iterate_over_DataFrame_rows.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Iterate_over_DataFrame_rows.ipynb", "imports": ["pandas", "numpy"], "image_url": ""}, {"objectID": "56f61acbe2bb3fb0a64d18a0d1d86efe024967f9d0f7640c21efbc6fab85d961", "tool": "Pandas", "notebook": "Iterate over DataFrame rows as namedtuples", "action": "", "tags": ["#pandas", "#python", "#loops", "#snippet", "#operations", "#namedtuples", "#dataframe"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-08", "created_at": "2023-06-07", "description": "This notebook demonstrates how to iterate over DataFrame rows as namedtuples", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Iterate_over_DataFrame_rows_as_namedtuples.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Iterate_over_DataFrame_rows_as_namedtuples.ipynb", "imports": ["pandas", "numpy", "collections.namedtuple"], "image_url": ""}, {"objectID": "66637c0e78b1cafa7d6ad81906a679a160528a45efad2fc436c804d12b40ca49", "tool": "Pandas", "notebook": "Keep columns", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook shows how to define a new DataFrame that only keeps columns defined in Input section.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Keep_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Keep_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "0b45752d1f47b9ea195133d22bb8a86066c2eb1baad4a0308a994c5a424e9fbc", "tool": "Pandas", "notebook": "Looping Over Dataframe", "action": "", "tags": ["#pandas", "#python", "#loops", "#dataframes", "#forloop", "#loop", "#snippet", "#operations"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-06-06", "created_at": "2021-10-07", "description": "This notebook provides an overview of multiples ways to use loops to iterate over a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Looping_Over_Dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Looping_Over_Dataframe.ipynb", "imports": ["pandas", "numpy"], "image_url": ""}, {"objectID": "4ad864c7c502f13639fafe2b968aa7346943bb6330ba7557259e9e431848adcc", "tool": "Pandas", "notebook": "Map column with values in dict", "action": "", "tags": ["#pandas", "#dict", "#map", "#series"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-08", "description": "This notebook shows how to map a column of a Pandas DataFrame with values from a dictionary.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Map_column_with_values_in_dict.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Map_column_with_values_in_dict.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "ea957a5f2454415ccc337c1c056b1e7a9e2cb345f786c1938a3ef0b4a434955e", "tool": "Pandas", "notebook": "Merge Dataframes", "action": "", "tags": ["#pandas", "#python", "#merging", "#merge", "#dataframes", "#consolidate", "#operations", "#snippet", "#dataframe"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-06-04", "created_at": "2021-10-07", "description": "This notebook provides an overview of how to use the Pandas library to merge two or more dataframes.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Merge_Dataframes.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Merge_Dataframes.ipynb", "imports": ["pandas", "numpy"], "image_url": ""}, {"objectID": "dfd4c9e70e3517613da38637dc496216b24dd65e6305d5edc6f1eae5d0172d6c", "tool": "Pandas", "notebook": "Pivot rows to columns", "action": "", "tags": ["#pandas", "#pivot", "#snippet", "#operations", "#utils", "#data"], "author": "Ismail Chihab", "author_url": "https://www.linkedin.com/in/ismail-chihab-4b0a04202/", "updated_at": "2023-04-12", "created_at": "2022-09-09", "description": "This notebook demonstrates how to use the Pandas library to transform data by pivoting rows into columns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Pivot_rows_to_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Pivot_rows_to_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "4932d57368797cb77d7866263669d24705499a09d49a57e4c15f334eba2cf2a1", "tool": "Pandas", "notebook": "Read CSV", "action": "", "tags": ["#pandas", "#csv", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook show how to read a CSV file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Read_CSV.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Read_CSV.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "de43d3c8b9aa8a86b8179624cf2d7dc2cfeb49e5c922858f7419de9daa6b2dc2", "tool": "Pandas", "notebook": "Read Excel", "action": "", "tags": ["#pandas", "#excel", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook show how to read a Excel file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Read_Excel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Read_Excel.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "846a0b00f4ab77df51ec9a47797b3a4440bb682426600b7a7a3b7b5fbdf0c652", "tool": "Pandas", "notebook": "Rename columns", "action": "", "tags": ["#pandas", "#snippet", "#datacleaning", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook renames columns in a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Rename_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Rename_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "5af9dafa2814c72a3b62ec58dbe2de6fc94c096c7cf3ec68e341701bed102914", "tool": "Pandas", "notebook": "Save dataframe to CSV", "action": "", "tags": ["#pandas", "#csv", "#snippet", "#operation"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-03", "created_at": "2023-06-03", "description": "This notebook show how to save a dataframe to a CSV file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Save_dataframe_to_CSV.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Save_dataframe_to_CSV.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "c2f8f6055e4d62602616107e3d9098ce962d1a64c169978495b1ffe2b51ac751", "tool": "Pandas", "notebook": "Save dataframe to Excel", "action": "", "tags": ["#pandas", "#excel", "#snippet", "#operation", "#dataframe", "#save"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-09", "created_at": "2023-06-07", "description": "This notebook show how to save a dataframe to Excel.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Save_dataframe_to_Excel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Save_dataframe_to_Excel.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "1d2d1155e7b45a7959095737ba4ecd08e96ffc02a72d097d5271eae4b71902a5", "tool": "Pandas", "notebook": "Sort values by multiples columns", "action": "", "tags": ["#pandas", "#dataframe", "#sort", "#columns", "#values", "#multiples"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-16", "created_at": "2023-06-13", "description": "This notebook will show how to sort values by multiples columns in Pandas. It is usefull for data analysis and data manipulation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Sort_values_by_multiples_columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Sort_values_by_multiples_columns.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "b27675b70ee0475d12381be158a83a7888089de73a76f6f28e4f4d3c1088bfad", "tool": "Pandas", "notebook": "Transform DataFrame to json file", "action": "", "tags": ["#pandas", "#dataframe", "#json", "#transform", "#file", "#dict", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-09", "created_at": "2023-05-09", "description": "This notebook will show how to transform a DataFrame into a json file. It is usefull for organizations that need to store data in a json format.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Transform_DataFrame_to_json_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Transform_DataFrame_to_json_file.ipynb", "imports": ["pandas", "json"], "image_url": ""}, {"objectID": "1961a79a86f4ee0ee0e0b29f136404431cb29587979223fe04ef6dec574cbc69", "tool": "Pandas", "notebook": "Transform Dataframe to dict", "action": "", "tags": ["#pandas", "#dataframe", "#dict", "#snippet", "#yahoofinance", "#naas_drivers", "#operations", "#jupyternotebooks"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-09", "created_at": "2023-05-09", "description": "This notebook provides an example of how to use the Pandas library to convert a dataframe into a dictionary.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandas/Pandas_Transform_Dataframe_to_dict.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandas/Pandas_Transform_Dataframe_to_dict.ipynb", "imports": ["naas_drivers.yahoofinance"], "image_url": ""}, {"objectID": "76ce3d48a02d92cc6ef4e068ea8883a5381c4583f32d993f672106b1f295be90", "tool": "Pandasql", "notebook": "Query CSV Using SQL", "action": "", "tags": ["#pandas", "#csv", "#snippet", "#read", "#dataframe", "#sql", "#pandasql", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2023-02-04", "description": "This notebook demonstrates how to use Pandasql to query CSV files as if they were relational databases, using SQL syntax. The aim is to provide an alternative to traditional Pandas methods for filtering, grouping, and aggregating data, and make it easier for users who are familiar with SQL to perform these tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandasql/Pandasql_Query_CSV_Using_SQL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandasql/Pandasql_Query_CSV_Using_SQL.ipynb", "imports": ["pandas", "pandasql.sqldf", "pandasql.sqldf"], "image_url": ""}, {"objectID": "bb199c1091a4a9f5a538365d093d290b3d47e406206122d2fbe8fec17af8ab0a", "tool": "Pandasql", "notebook": "Query Excel Using SQL", "action": "", "tags": ["#pandas", "#excel", "#snippet", "#read", "#dataframe", "#sql", "#pandasql", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2023-04-07", "description": "This notebook demonstrates how to use Pandasql to query Excel files as if they were relational databases, using SQL syntax. The aim is to provide an alternative to traditional Pandas methods for filtering, grouping, and aggregating data, and make it easier for users who are familiar with SQL to perform these tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandasql/Pandasql_Query_Excel_Using_SQL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandasql/Pandasql_Query_Excel_Using_SQL.ipynb", "imports": ["pandas", "pandasql.sqldf", "pandasql.sqldf"], "image_url": ""}, {"objectID": "6a9d3147aa50285ac5a92cd7539565be2378fdb41aea7a36da585c2187e03632", "tool": "Pandasql", "notebook": "Query Parquet Using SQL", "action": "", "tags": ["#pandas", "#parquet", "#snippet", "#read", "#dataframe", "#sql", "#pandasql", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2023-04-07", "description": "This notebook demonstrates how to use Pandasql to query Parquet files as if they were relational databases, using SQL syntax. The aim is to provide an alternative to traditional Pandas methods for filtering, grouping, and aggregating data, and make it easier for users who are familiar with SQL to perform these tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pandasql/Pandasql_Query_Parquet_Using_SQL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pandasql/Pandasql_Query_Parquet_Using_SQL.ipynb", "imports": ["pandas", "pandasql.sqldf", "pandasql.sqldf"], "image_url": ""}, {"objectID": "1f5b6f5d2d919274a737d5b13f4427d7cc779367fb8efffbd61ea6c7d767a2b0", "tool": "Panel", "notebook": "Create a kernel on Naas", "action": "", "tags": ["#panel", "#ipython", "#conda", "#naas", "#kernel"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2023-01-11", "description": "This Jupyter Notebook will enable you to establish a new IPython Kernel that you can customize, allowing you to install any desired tools. This kernel, once created, can be selected to run your notebooks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Panel/Panel_Create_a_Panel_kernel_on_Naas.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Panel/Panel_Create_a_Panel_kernel_on_Naas.ipynb", "imports": [], "image_url": ""}, {"objectID": "43a2d5488f55091c2a69c598836fe3680e4003c3117c71b687912fc67b7611c0", "tool": "Pillow", "notebook": "Add data to image", "action": "", "tags": ["#pillow", "#opendata", "#snippet", "#data", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-04-19", "description": "This notebook demonstrates how to use the Pillow library to add data to an existing image.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pillow/Pillow_Add_data_to_image.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pillow/Pillow_Add_data_to_image.ipynb", "imports": ["PIL.Image, ImageDraw, ImageFont", "naas"], "image_url": ""}, {"objectID": "5ac6df900da4dc00365e842c34cceb80b361d19e824618b4b49ddc8275d355cf", "tool": "Pillow", "notebook": "Create indicator", "action": "", "tags": ["#pillow", "#opendata", "#snippet", "#data", "#image", "#indicator", "#kpi"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-12-06", "description": "This notebook creates an indicator with title and kpi using Pillow.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pillow/Pillow_Create_indicator.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pillow/Pillow_Create_indicator.ipynb", "imports": ["PIL.Image, ImageDraw, ImageFont", "urllib"], "image_url": ""}, {"objectID": "36a46b8dea31448e6c96ce86e134eb3596ca9606f23ba38d98c952a3bc8246b4", "tool": "Pillow", "notebook": "Create new image", "action": "", "tags": ["#pillow", "#opendata", "#snippet", "#data", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-12-06", "description": "This notebook creates and saves an image using Pillow. You can setup its width, height and background color.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pillow/Pillow_Create_new_image.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pillow/Pillow_Create_new_image.ipynb", "imports": ["PIL.Image"], "image_url": ""}, {"objectID": "ed2a0acd5f746906d09577c801960c8a21014484ac59e04b2875b57fad351e2c", "tool": "Pillow", "notebook": "Generate A Certificate Template", "action": "", "tags": ["#Pillow", "#Python", "#certificate-template", "#naas"], "author": "Suhas B", "author_url": "https://www.linkedin.com/in/suhasbrao/", "updated_at": "2023-04-12", "created_at": "2022-10-06", "description": "This notebook provides a template for generating a personalized certificate using the Pillow library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pillow/Pillow_Generate_A_Certificate_Template.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pillow/Pillow_Generate_A_Certificate_Template.ipynb", "imports": ["PIL.Image, ImageDraw, ImageFont", "requests", "io.BytesIO", "bs4.BeautifulSoup"], "image_url": ""}, {"objectID": "f67f0e92ee4940e9983e194e6375686842a22bcbc68eec6f4066e69b528aeaf0", "tool": "Pipedrive", "notebook": "Get contact", "action": "", "tags": ["#pipedrive", "#crm", "#contact", "#sales", "#snippet", "#dataframe"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2021-10-18", "description": "This notebook provides a way to quickly and easily get contact information from Pipedrive.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pipedrive/Pipedrive_Get_contact.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pipedrive/Pipedrive_Get_contact.ipynb", "imports": ["pipedrive.client.Client", "pipedrive.client.Client", "pandas"], "image_url": ""}, {"objectID": "d6e7f95dbe41f7777d676406ded33033d8f4320cf952759eb61fc8638a3f7f28", "tool": "Plaid", "notebook": "Get accounts", "action": "", "tags": ["#plaid", "#bank", "#accounts", "#snippet", "#finance", "#dataframe"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides an easy way to access financial accounts and transactions through Plaid's API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plaid/Plaid_Get_accounts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plaid/Plaid_Get_accounts.ipynb", "imports": ["os", "plaid", "IPython.core.display", "uuid", "naas", "json", "pandas"], "image_url": ""}, {"objectID": "1c0a3c221963dae426dec4dcc8f110df19362ac20b1950d88159dcc05db17305", "tool": "Plaid", "notebook": "Get transactions", "action": "", "tags": ["#plaid", "#bank", "#transactions", "#snippet", "#finance", "#dataframe"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a guide to retrieving financial transaction data from Plaid.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plaid/Plaid_Get_transactions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plaid/Plaid_Get_transactions.ipynb", "imports": ["os", "plaid", "naas", "IPython.core.display", "uuid", "json"], "image_url": ""}, {"objectID": "8c98be6f5ca47cc8237544ca1fd6637230bb0e9ec0d7d55da7e49d0aa05cbe82", "tool": "Plotly", "notebook": "Create Balance Sheet Treemaps", "action": "", "tags": ["#plotly", "#treemap", "#snippet", "#dataviz", "#balancesheet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-31", "description": "This notebook displays Balance Sheet items into treemap graphs. In a balance sheet, treemap templates can be used to show the distribution of assets and liabilities. The assets can be divided into smaller categories such as cash, marketable securities, accounts receivable, and inventory, while the liabilities can be separated into categories like loans payable, bonds payable, and accounts payable. With a treemap, it is easy to see the relative proportions of each category, making it easier to identify any trends or patterns in the data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Balance_Sheet_Treemaps.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Balance_Sheet_Treemaps.ipynb", "imports": ["plotly.graph_objects", "plotly.subplots.make_subplots", "pandas", "naas"], "image_url": ""}, {"objectID": "c484ebf9f234ef9eee9185595ec6d6d402641b76aade153dd892444ef3b299c9", "tool": "Plotly", "notebook": "Create Barline chart", "action": "", "tags": ["#plotly", "#naas", "#snippet", "#operations", "#barline"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2022-05-26", "description": "This notebook provides instructions on how to create a barline chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Barline_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Barline_chart.ipynb", "imports": ["pandas", "plotly.graph_objects", "plotly.subplots.make_subplots", "naas"], "image_url": ""}, {"objectID": "f6d7102dbaeec65604e69539224a108362eacf8079a71cc0dbd46bf166fc0062", "tool": "Plotly", "notebook": "Create Bubblechart", "action": "", "tags": ["#plotly", "#chart", "#bubblechart", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a bubble chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Bubblechart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Bubblechart.ipynb", "imports": ["naas", "plotly.express", "pandas"], "image_url": ""}, {"objectID": "662519b80629a12be69f987f9d8875dddf515b461d05e9055158e24ff7fc2207", "tool": "Plotly", "notebook": "Create Bubblemap by City", "action": "", "tags": ["#plotly", "#bubblemap", "#city", "#python", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will show how to creates a bubblemap with values by city using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Bubblemap_by_City.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Bubblemap_by_City.ipynb", "imports": ["pandas", "plotly.express", "naas"], "image_url": ""}, {"objectID": "517e1dc7f83b92be09f8be6d565dc49f1b608178f833c7e3aa8b30f5b4687c7f", "tool": "Plotly", "notebook": "Create Candlestick", "action": "", "tags": ["#plotly", "#chart", "#candlestick", "#group", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an example of how to create a candlestick chart using the Plotly library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Candlestick.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Candlestick.ipynb", "imports": ["naas", "naas_drivers.yahoofinance", "plotly.graph_objects", "pandas"], "image_url": ""}, {"objectID": "d4631b09503ea4ffa69803e63b11d3c51800ee8a8468c962406c93f0398abbde", "tool": "Plotly", "notebook": "Create Gantt chart", "action": "", "tags": ["#plotly", "#chart", "#gant", "#project", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a Gantt chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Gantt_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Gantt_chart.ipynb", "imports": ["plotly.express", "pandas"], "image_url": ""}, {"objectID": "38ddb9935318bf5698eae5b352037f790c225ef788173972b6896f6f028a0814", "tool": "Plotly", "notebook": "Create Heatmap", "action": "", "tags": ["#plotly", "#chart", "#heatmap", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an example of how to create a heatmap using the Plotly library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Heatmap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Heatmap.ipynb", "imports": ["naas", "plotly.graph_objects", "plotly.express", "pandas"], "image_url": ""}, {"objectID": "f71d07001cfdc2d67718ef0fd91d6bcab1b1c98e043fdbf770d52276f6449f3b", "tool": "Plotly", "notebook": "Create Horizontal Barchart", "action": "", "tags": ["#plotly", "#chart", "#horizontalbar", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a horizontal bar chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Horizontal_Barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Horizontal_Barchart.ipynb", "imports": ["plotly.graph_objects"], "image_url": ""}, {"objectID": "363d1b3f489a134479cfec35ff780e213e571c9d2356959cc5daff21d5dea34a", "tool": "Plotly", "notebook": "Create Leaderboard", "action": "", "tags": ["#plotly", "#chart", "#horizontalbar", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an interactive way to visualize and compare data using Plotly to create a leaderboard.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Leaderboard.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Leaderboard.ipynb", "imports": ["plotly.express", "pandas"], "image_url": ""}, {"objectID": "a64b46ba602d154f700f434315aea461c9170c8f939d1062ae9277dd131941c8", "tool": "Plotly", "notebook": "Create Leaderboard stacked", "action": "", "tags": ["#plotly", "#chart", "#horizontalbar", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides an example of how to create a leaderboard using Plotly's stacked bar chart visualization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Leaderboard_stacked.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Leaderboard_stacked.ipynb", "imports": ["plotly.express", "pandas"], "image_url": ""}, {"objectID": "e83171a9bd64008af6a5ea1e0510c738dc249f6741a28092160b5e3f3e8a68a9", "tool": "Plotly", "notebook": "Create Linechart", "action": "", "tags": ["#plotly", "#chart", "#linechart", "#trend", "#dataviz", "#yahoofinance", "#naas_drivers", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-11-23", "description": "This notebook provides instructions on how to create a line chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Linechart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Linechart.ipynb", "imports": ["naas", "naas_drivers.yahoofinance, plotly"], "image_url": ""}, {"objectID": "ae9899cd48c331274221a68cb0007765c4f1f79dbb8a197ffc9e19729393b3ff", "tool": "Plotly", "notebook": "Create Mapchart world", "action": "", "tags": ["#plotly", "#chart", "#worldmap", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides a step-by-step guide to creating an interactive mapchart of the world using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Mapchart_world.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Mapchart_world.ipynb", "imports": ["naas", "plotly.graph_objects", "pandas"], "image_url": ""}, {"objectID": "77b1042719f22bd7aec139151ff411e84fa83863e854fddce69e34042a4b90fa", "tool": "Plotly", "notebook": "Create Treemaps with plotly.express", "action": "", "tags": ["#plotly", "#treemap", "#snippet", "#dataviz", "#plotly.express", "#px"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-31", "description": "This notebook creates Treemaps with plotly.express. Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Treemaps_with_plotly.express.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Treemaps_with_plotly.express.ipynb", "imports": ["plotly.express", "numpy", "pandas", "naas"], "image_url": ""}, {"objectID": "33642dbaa758ab80c8d181a5e069bbd51c833d71d3f5b8802bd45cd6f7062ff9", "tool": "Plotly", "notebook": "Create Treemaps with plotly.graph objects", "action": "", "tags": ["#plotly", "#treemap", "#snippet", "#dataviz", "#plotly.graph_objects", "#go"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-31", "description": "This notebook creates Treemaps with plotly.graph_objects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Treemaps_with_plotly.graph_objects.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Treemaps_with_plotly.graph_objects.ipynb", "imports": ["plotly.graph_objects", "plotly.subplots.make_subplots", "numpy", "pandas", "naas"], "image_url": ""}, {"objectID": "63c55ffff60a0fc449fa140924c522ce65f38ad178f439c9bdd11f61817b50aa", "tool": "Plotly", "notebook": "Create Vertical Barchart", "action": "", "tags": ["#plotly", "#chart", "#verticalbarchart", "#group", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a vertical barchart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Vertical_Barchart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Vertical_Barchart.ipynb", "imports": ["naas", "plotly.graph_objects", "pandas"], "image_url": ""}, {"objectID": "f71af3953b75a90bc666f15072437705826d17bad8625bdc8561353a683b6931", "tool": "Plotly", "notebook": "Create Vertical Barchart group", "action": "", "tags": ["#plotly", "#chart", "#verticalbarchart", "#group", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a vertical barchart group using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Vertical_Barchart_group.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Vertical_Barchart_group.ipynb", "imports": ["naas", "plotly.graph_objects", "pandas"], "image_url": ""}, {"objectID": "ad519db0908de78d9d45a66e5b96a2682fe6b2a85fc2ea9410841cae78e0247a", "tool": "Plotly", "notebook": "Create Vertical Barchart stacked", "action": "", "tags": ["#plotly", "#chart", "#verticalbarchart", "#group", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a vertical barchart with stacked bars using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Vertical_Barchart_stacked.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Vertical_Barchart_stacked.ipynb", "imports": ["naas", "plotly.graph_objects", "pandas"], "image_url": ""}, {"objectID": "e90ce80fa0c56a2714a58552d3ca00e07d35d53d5d2a89216f1449170e347e6d", "tool": "Plotly", "notebook": "Create Waterfall chart", "action": "", "tags": ["#plotly", "#chart", "#warterfall", "#dataviz", "#snippet", "#operations", "#image", "#html"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a Waterfall chart using Plotly.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Plotly/Plotly_Create_Waterfall_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Plotly/Plotly_Create_Waterfall_chart.ipynb", "imports": ["naas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "49ed2a1b8e8e4d090e53319021c0d31dff5664db5991ffdf6ec49d5620eec924", "tool": "Polars", "notebook": "Concatenate DataFrames", "action": "", "tags": ["#polars", "#dataframes", "#concatenate", "#python", "#pandas", "#data", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook explains how to concatenate DataFrames using Polars and Python. It is usefull for data analysis and data manipulation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Concatenate_DataFrames.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Concatenate_DataFrames.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "b0ec8cb4ccca4c7e92db03bd0282150b5301b49d4afd039cd3d6d134bc302247", "tool": "Polars", "notebook": "Create DataFrame", "action": "", "tags": ["#polars", "#dataframe", "#read", "#python", "#library", "#data", "#csv"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-06", "created_at": "2023-07-06", "description": "This notebook demonstrates how to create a DataFrame using `polars` library.\n\nAbout Polars:\n- `polars` is a Python library for data manipulation that is built on top of Rust's `Apache Arrow` and `DataFusion` projects.\n- It offers fast and efficient data processing and manipulation capabilities for large datasets, with a Pandas-like API and support for advanced data types.\n- `polars` is especially useful for data-intensive applications such as machine learning, data analysis, and data visualization, and can handle datasets that are too large to fit into memory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Create_DataFrame.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Create_DataFrame.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "5ad976a4ad2a8c89054f8c2676b823083a4ffa05d5d8803d3ad6164a6649f777", "tool": "Polars", "notebook": "Read CSV", "action": "", "tags": ["#polars", "#dataframe", "#read", "#python", "#library", "#data", "#csv"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2023-04-07", "description": "This notebook will demonstrate how to read a csv using the Polars library.\n\nAbout Polars:\n- `polars` is a Python library for data manipulation that is built on top of Rust's `Apache Arrow` and `DataFusion` projects.\n- It offers fast and efficient data processing and manipulation capabilities for large datasets, with a Pandas-like API and support for advanced data types.\n- `polars` is especially useful for data-intensive applications such as machine learning, data analysis, and data visualization, and can handle datasets that are too large to fit into memory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Read_CSV.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Read_CSV.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "3521a51627aded39438fb89161151234ff86772c86c9ffee7fd4cef55c3cac79", "tool": "Polars", "notebook": "Select columns", "action": "", "tags": ["#polars", "#dataframe", "#read", "#python", "#library", "#data", "#csv"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-06", "created_at": "2023-07-06", "description": "This notebook demonstrates how to select columns in a DataFrame using `polars` library.\n\nAbout Polars:\n- `polars` is a Python library for data manipulation that is built on top of Rust's `Apache Arrow` and `DataFusion` projects.\n- It offers fast and efficient data processing and manipulation capabilities for large datasets, with a Pandas-like API and support for advanced data types.\n- `polars` is especially useful for data-intensive applications such as machine learning, data analysis, and data visualization, and can handle datasets that are too large to fit into memory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Select_Columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Select_Columns.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "fa25e3ec1012dad1c63aeda4b86a6f93f308c4643b6260611d01662a65f294e7", "tool": "Polars", "notebook": "Select rows", "action": "", "tags": ["#polars", "#dataframe", "#read", "#python", "#library", "#data", "#csv"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-06", "created_at": "2023-07-06", "description": "This notebook demonstrates how to select rows in a DataFrame using `polars` library.\n\nAbout Polars:\n- `polars` is a Python library for data manipulation that is built on top of Rust's `Apache Arrow` and `DataFusion` projects.\n- It offers fast and efficient data processing and manipulation capabilities for large datasets, with a Pandas-like API and support for advanced data types.\n- `polars` is especially useful for data-intensive applications such as machine learning, data analysis, and data visualization, and can handle datasets that are too large to fit into memory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Select_Rows.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Select_Rows.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "7a9f09587076ee0c3192e964f346d57f656558be530916d518954ff4dcf37679", "tool": "Polars", "notebook": "Select both rows and columns", "action": "", "tags": ["#polars", "#dataframe", "#read", "#python", "#library", "#data", "#csv"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-06", "created_at": "2023-07-06", "description": "This notebook demonstrates how to select columns, rows, and both columns and rows at once in a DataFrame using `polars` library.\n\nAbout Polars:\n- `polars` is a Python library for data manipulation that is built on top of Rust's `Apache Arrow` and `DataFusion` projects.\n- It offers fast and efficient data processing and manipulation capabilities for large datasets, with a Pandas-like API and support for advanced data types.\n- `polars` is especially useful for data-intensive applications such as machine learning, data analysis, and data visualization, and can handle datasets that are too large to fit into memory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Polars/Polars_Select_Rows_and_Columns.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Polars/Polars_Select_Rows_and_Columns.ipynb", "imports": ["polars", "polars"], "image_url": ""}, {"objectID": "228a81ed357d309e1ec921bcacf182615172dd1fabda1a70ac76cc2403589444", "tool": "PostgresSQL", "notebook": "Get data from database", "action": "", "tags": ["#postgressql", "#database", "#operations", "#snippet", "#dataframe"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou/", "updated_at": "2023-04-12", "created_at": "2022-05-02", "description": "This notebook provides instructions on how to query a PostgreSQL database and retrieve data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PostgresSQL/PostgresSQL_Get_data_from_database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PostgresSQL/PostgresSQL_Get_data_from_database.ipynb", "imports": ["psycopg2", "psycopg2", "pandas", "naas"], "image_url": ""}, {"objectID": "d407f6c7c08a81f0c5871257274d21d6b1ca36d44fdb2483cc0caab78c998412", "tool": "PowerPoint", "notebook": "Add Slide With Image", "action": "", "tags": ["#powerpoint", "#slide", "#portrait", "#pptx", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-30", "description": "This notebook provides instructions on how to add an image to a PowerPoint slide.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Add_Slide_With_Image.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Add_Slide_With_Image.ipynb", "imports": ["pptx.Presentation", "pptx.Presentation", "pptx.util.Inches"], "image_url": ""}, {"objectID": "85d11fb04a9f5d15ba18c7cad27cc4241d0cbb163c4d27551bec621c5896932d", "tool": "PowerPoint", "notebook": "Add Slide With Textbox", "action": "", "tags": ["#powerpoint", "#slide", "#portrait", "#pptx", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-30", "description": "This notebook allows users to create a new slide in PowerPoint with a textbox.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Add_Slide_With_Textbox.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Add_Slide_With_Textbox.ipynb", "imports": ["pptx.Presentation", "pptx.Presentation", "pptx.util.Inches, Pt"], "image_url": ""}, {"objectID": "e3d8e2acd0d06ddfb9d30c2f126b22ec639ec52fb578e2bf890674239ab7e4b6", "tool": "PowerPoint", "notebook": "Add Slide With Title Subtitle", "action": "", "tags": ["#powerpoint", "#slide", "#portrait", "#pptx", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-30", "description": "This notebook allows users to quickly and easily create a new slide in PowerPoint with a title and subtitle.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Add_Slide_With_Title_Subtitle.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Add_Slide_With_Title_Subtitle.ipynb", "imports": ["pptx.Presentation", "pptx.Presentation", "pptx.util.Inches"], "image_url": ""}, {"objectID": "f8ca7d5fbaed2f83b5a5b90bfd54a5d9965f635427725abef04601fc7c340129", "tool": "PowerPoint", "notebook": "Add title + line in presentation", "action": "", "tags": ["#powerpoint", "#naas", "#python", "#python_pptx"], "author": "Ayoub Berdeddouch", "author_url": "https://www.linkedin.com/in/ayoub-berdeddouch", "updated_at": "2023-04-12", "created_at": "2022-11-01", "description": "This notebook Adds a title + Line to a presentation in PowerPoint", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Add_title_%2B_line_in_presentation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Add_title_%2B_line_in_presentation.ipynb", "imports": ["pptx.Presentation", "pptx.enum.shapes.MSO_CONNECTOR", "pptx.util.Inches"], "image_url": ""}, {"objectID": "4944a903bfe77005932df44840be3cc20f84adb51aa8fc7a18eb411e04aef75a", "tool": "PowerPoint", "notebook": "Create Presentation", "action": "", "tags": ["#powerpoint", "#naas", "#python", "#pythonpptx", "#asset", "#snippet", "#operations", "#slide", "#microsoft"], "author": "Ayoub Berdeddouch", "author_url": "https://www.linkedin.com/in/ayoub-berdeddouch", "updated_at": "2023-04-12", "created_at": "2022-10-23", "description": "This notebook creates a PowerPoint presentation with a cover page, 3 pages with graphs and text and a last page.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Create_Presentation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Create_Presentation.ipynb", "imports": ["pptx.Presentation", "pptx.enum.shapes.MSO_SHAPE", "pptx.dml.color.RGBColor", "pptx.util.Inches, Pt", "pptx.enum.dml.MSO_THEME_COLOR", "pptx.chart.data.CategoryChartData", "pptx.enum.chart.XL_CHART_TYPE", "pptx.chart.data.ChartData", "pptx.util.Inches", "numpy", "datetime", "requests", "plotly.graph_objects", "pandas", "naas"], "image_url": ""}, {"objectID": "87b9a5c96c8ceccefe39e7dbb996c586cdd15f07b0317200b63be92aeb8d3281", "tool": "PowerPoint", "notebook": "Set portrait format", "action": "", "tags": ["#powerpoint", "#slide", "#portrait", "#pptx", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-09-30", "description": "This notebook allows you to easily set the portrait format for your PowerPoint presentation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PowerPoint/PowerPoint_Set_portrait_format.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PowerPoint/PowerPoint_Set_portrait_format.ipynb", "imports": ["pptx.Presentation", "pptx.Presentation", "pptx.util.Inches"], "image_url": ""}, {"objectID": "6dc53ab8a25919a7cd0c364aec804a3e259bce5341b0ac2694bc44c4cc19ff65", "tool": "PyCaret", "notebook": "Automl classification", "action": "", "tags": ["#automl", "#pandas", "#snippet", "#classification", "#dataframe", "#visualize", "#pycaret", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-05-28", "description": "This notebook demonstrates how to use PyCaret to quickly and easily build and evaluate machine learning models for classification tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PyCaret/PyCaret_automl_classification.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PyCaret/PyCaret_automl_classification.ipynb", "imports": ["pandas", "pycaret.classification.setup, compare_models, evaluate_model, predict_model, finalize_model, \\", "pycaret.classification.setup, compare_models, evaluate_model, predict_model, finalize_model, \\"], "image_url": ""}, {"objectID": "7836b18a1acc436173deeed60d42ff7bd8ddf36559c8275931e2ec346a0b7087", "tool": "PyCaret", "notebook": "Automl regression", "action": "", "tags": ["#automl", "#pandas", "#snippet", "#regression", "#dataframe", "#visualize", "#pycaret", "#operations"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-05-28", "description": "This notebook demonstrates how to use PyCaret's automated machine learning capabilities to perform regression tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PyCaret/PyCaret_automl_regression.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PyCaret/PyCaret_automl_regression.ipynb", "imports": ["pandas", "pycaret.regression.setup, compare_models, evaluate_model, predict_model, finalize_model, \\", "pycaret.regression.setup, compare_models, evaluate_model, predict_model, finalize_model, \\"], "image_url": ""}, {"objectID": "47b1d63eba6e37dd5d1ed7fe4be46bb37f6914de53819f21fadae86a6f19acdf", "tool": "PyGWalker", "notebook": "Analyze Pandas dataframe", "action": "", "tags": ["#pandas", "#dataframe", "#tableau", "#pygwalker", "#analyze", "#jupyter"], "author": "Abraham Israel", "author_url": "https://www.linkedin.com/in/abraham-israel/", "updated_at": "2023-04-12", "created_at": "2023-03-07", "description": "This notebook will demonstrate how to analyze a Pandas dataframe in Jupyter using a Tableau-style interface.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PyGWalker/PyGWalker_Analyze_Pandas_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PyGWalker/PyGWalker_Analyze_Pandas_dataframe.ipynb", "imports": ["pandas", "numpy", "pygwalker", "pygwalker"], "image_url": ""}, {"objectID": "8da37e2aaf56e0b26e7ee696dc16f492d45a2e204454444b107880aac4b15824", "tool": "PyPI", "notebook": "- Get number of downloads any package", "action": "", "tags": ["#pypi", "#downloads", "#package", "#operations", "#analytics", "#plotly", "#html", "#csv", "#image", "#png"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-27", "description": "This notebook provides a way to retrieve the download count of any package from the Python Package Index (PyPI).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PyPI/PyPI_Get_number_of_downloads_any_package.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PyPI/PyPI_Get_number_of_downloads_any_package.ipynb", "imports": ["pypistats", "pypistats", "pprint.pprint", "datetime.datetime", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "5b61a4c4382b4f68bdf9dd662ae75f7e84c36a567a9eabf26257aa87cf5c4046", "tool": "PyPI", "notebook": "Get release dates from package", "action": "", "tags": ["#pypi", "#downloads", "#package", "#operations", "#analytics", "#plotly", "#html", "#csv", "#image", "#png"], "author": "Mardiat-Iman", "author_url": "https://www.linkedin.com/in/mardiat-iman-ibrahim-imam-726027262", "updated_at": "2023-07-27", "created_at": "2023-07-27", "description": "This notebook get the release dates a package from the Python Package Index (PyPI) and plot a Barchart and Scatter Plot to display the release by month. \n\nNB: We have noticed that sometimes not all versions are accessible via this endpoint in comparison with the website. Please let us know if you manage to find a solution to this issue, we would appreciate.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/PyPI/PyPI_Get_release_dates_from_package.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/PyPI/PyPI_Get_release_dates_from_package.ipynb", "imports": ["requests", "numpy", "matplotlib.pyplot", "matplotlib.dates", "dateutil.parser.parse"], "image_url": ""}, {"objectID": "f4efb27c8503f52f1198dec50fc0602cc6147fa541b8869da617593b6cf6e43c", "tool": "Python", "notebook": "Calculate the percentage of similarity between two strings", "action": "", "tags": ["#python", "#string", "#similarity", "#calculate", "#percentage", "#compare"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-28", "created_at": "2023-08-28", "description": "This notebook calculates the percentage of similarity between two strings and is usefull for organizations to compare two strings and measure their similarity.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Calculate_the_percentage_of_similarity_between_two_strings.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Calculate_the_percentage_of_similarity_between_two_strings.ipynb", "imports": ["difflib.SequenceMatcher"], "image_url": ""}, {"objectID": "1285d5b317f4b36ebfc42542b8f98c906a4c3ea71f825078f09766ea31bc076e", "tool": "Python", "notebook": "Check if string is number", "action": "", "tags": ["#python", "#string", "#number", "#check", "#isnumber", "#function"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook will check if a string is a number and how it is useful for organizations. It will help to identify if a string is a number or not.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Check_if_string_is_number.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Check_if_string_is_number.ipynb", "imports": ["string"], "image_url": ""}, {"objectID": "03bc3ba50473a4aff2cfca6b15c26f19dd51443a7e99da17d33864435520c19e", "tool": "Python", "notebook": "Clean your download folder", "action": "", "tags": ["#python", "#automation", "#clean_folder"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-04-12", "created_at": "2023-04-01", "description": "This notebook will go through your given folder and check each file last modification time, and if it's been more than 30 days it will move those file to new folder 'files_to_delete'", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Clean_your_download_folder.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Clean_your_download_folder.ipynb", "imports": ["os", "shutil", "datetime.datetime, timedelta"], "image_url": ""}, {"objectID": "6803ffcd1c5475d13f4ef26dd7761f41d317f9a20677f2e8e30352537c2c9cf5", "tool": "Python", "notebook": "Compress images", "action": "", "tags": ["#python", "#PIL", "#images", "#compress"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-05-23", "created_at": "2023-05-23", "description": "This notebook uses PIL library to compress the image.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Compress_images.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Compress_images.ipynb", "imports": ["PIL.Image", "PIL.Image", "os", "requests"], "image_url": ""}, {"objectID": "ccf490cb6569994548b9c95421373ae1e94bb10fa7fb61dadd3576a073277f1d", "tool": "Python", "notebook": "Consolidate Excel files", "action": "", "tags": ["#python", "#consolidate", "#files", "#productivity", "#snippet", "#operations", "#excel"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2021-10-07", "description": "The objective of this notebook is to consolidate multiple Excel files (.xlsx) into one.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Consolidate_Excel_files.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Consolidate_Excel_files.ipynb", "imports": ["os", "pandas"], "image_url": ""}, {"objectID": "d41e9d952be285475cb26b5226195474cd7ba62ace4f711fe492d5f79b7ba97c", "tool": "Python", "notebook": "Convert CSV to Excel", "action": "", "tags": ["#python", "#csv", "#excel", "#pandas", "#file"], "author": "Sophia Iroegbu", "author_url": "www.linkedin.com/in/sophia-iroegbu", "updated_at": "2023-04-12", "created_at": "2022-10-10", "description": "This notebook provides a step-by-step guide to converting CSV files to Excel spreadsheets using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_CSV_to_Excel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_CSV_to_Excel.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "5b5dee3ead8fd96908827f51ac99cb0b72b7dbfc37239147e2dfb6feba7426ef", "tool": "Python", "notebook": "Convert degrees-minutes-seconds to decimal degrees", "action": "", "tags": ["#python", "#geopy", "#snippet", "#navigation"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook shows how to convert degrees-minutes-seconds to decimal degrees. Converting coordinates from Degrees, Minutes, and Seconds (DMS) to decimal degrees can be useful for compatibility with modern systems that use decimal format. It also simplifies calculations and data processing, as working with decimal numbers is often easier and more straightforward than working with degrees, minutes, and seconds.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_DMS_to_decimal_degrees.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_DMS_to_decimal_degrees.ipynb", "imports": [], "image_url": ""}, {"objectID": "0069c1c7add214fdd2655b1fa2238a2f17d761feb5403f7dfeb95c27114911eb", "tool": "Python", "notebook": "Convert PNG Images To JPG", "action": "", "tags": ["#jpg", "#png", "#to", "#image", "#images", "#convert"], "author": "Ahmed Mousa", "author_url": "https://www.linkedin.com/in/akmousa/", "updated_at": "2023-04-12", "created_at": "2022-11-10", "description": "This notebook converts png images to jpg images.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_PNG_Images_To_JPG.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_PNG_Images_To_JPG.ipynb", "imports": ["PIL.Image"], "image_url": ""}, {"objectID": "ea5c6ad4046dea2b3a2e3f412203b3899b9f88cffa458917a9b828ee0b6dd11b", "tool": "Python", "notebook": "Convert URL to string", "action": "", "tags": ["#python", "#urllib", "#string", "#url", "#convert", "#library"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook will show how to convert a URL to a string using urllib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_URL_to_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_URL_to_string.ipynb", "imports": ["urllib.parse"], "image_url": ""}, {"objectID": "bb57377a72ad818450b8065fe617392e959e8c11b27e830a1548a57af32e054c", "tool": "Python", "notebook": "Convert audiofile from wav to mp3", "action": "", "tags": ["#python", "#audio", "#wavtomp3", "#pydub"], "author": "Mohit Singh", "author_url": "", "updated_at": "2023-04-12", "created_at": "2023-03-08", "description": "This notebook uses the Pydub library to convert audio file from wav to mp3.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_audiofile_from_wav_to_mp3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_audiofile_from_wav_to_mp3.ipynb", "imports": ["os", "pydub.AudioSegment", "pydub.AudioSegment", "requests"], "image_url": ""}, {"objectID": "efc49f04ec827f01ebc298a6468803093908ebcaa46a2f7fcd8353cf67289731", "tool": "Python", "notebook": "Convert coordinates to degrees-minutes-seconds", "action": "", "tags": ["#python", "#geopy", "#snippet", "#navigation"], "author": "Antonio Georgiev", "author_url": "www.linkedin.com/in/antonio-georgiev-b672a325b", "updated_at": "2023-07-28", "created_at": "2023-07-28", "description": "This notebook shows how to convert coordinates to to Degrees, Minutes, and Seconds (DMS). Converting coordinates to Degrees, Minutes, and Seconds (DMS) can be beneficial for compatibility with systems that use DMS as their standard format. It can also improve precision in fields like surveying or navigation, where accurate measurements are crucial.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_coordinates_to_DMS.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_coordinates_to_DMS.ipynb", "imports": [], "image_url": ""}, {"objectID": "1b0f742b14019f6471df8b63da4b92c06192acbe92d849987e62afafb2dac907", "tool": "Python", "notebook": "Convert currency", "action": "", "tags": ["#python", "#exchange", "#currency", "#converter", "#convert", "#snippet", "#operations"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-19", "created_at": "2023-06-19", "description": "This workbook shows you how to convert any currency into any other currency in real time using `forex_python` library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_currency.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_currency.ipynb", "imports": ["forex_python.converter.CurrencyRates", "forex_python.converter.CurrencyRates"], "image_url": ""}, {"objectID": "30b65ea2617db409e1fba9cc5ff0c4b258e5a8e58ebde18fe4ff5314a177810e", "tool": "Python", "notebook": "Convert length", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#length"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert length using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_length.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_length.ipynb", "imports": [], "image_url": ""}, {"objectID": "a16c1298d415f1c4c24ae79bf540d33cbde9150d81bae2d196bbbba37a742116", "tool": "Python", "notebook": "Convert speed", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#speed"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert speed using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_speed.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_speed.ipynb", "imports": [], "image_url": ""}, {"objectID": "c3b9f65c829ea7dd7c8fe689d18199671b582c28e65ca5ab0544da17e9566633", "tool": "Python", "notebook": "Convert string boolean to boolean", "action": "", "tags": ["#python", "#string", "#boolean", "#convert", "#type", "#data"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-07-25", "created_at": "2023-07-25", "description": "This notebook will show how to convert a string boolean to a boolean type in Python. It is usefull for data cleaning and data manipulation.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_string_boolean_to_boolean.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_string_boolean_to_boolean.ipynb", "imports": ["ast"], "image_url": ""}, {"objectID": "8dacf09e80d19c288d77ccdf43ba69339901ed23a093c040857e1e6abdc05eee", "tool": "Python", "notebook": "Convert string to URL", "action": "", "tags": ["#python", "#urllib", "#string", "#url", "#convert", "#library"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook will show how to convert a string to a URL using urllib.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_string_to_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_string_to_URL.ipynb", "imports": ["urllib.parse"], "image_url": ""}, {"objectID": "067b3975c0bfb9d91f586f52bc48f9b131588dccf939568abb539de93f96b308", "tool": "Python", "notebook": "Convert temperature", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#temperature"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert units temperature using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_temperature.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_temperature.ipynb", "imports": [], "image_url": ""}, {"objectID": "56b5020fb5de6bd618fd2b48c7fdf5e338135bbc4cb8b7a39b8a847fdabf45a3", "tool": "Python", "notebook": "Convert time", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#time"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert time using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_time.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_time.ipynb", "imports": [], "image_url": ""}, {"objectID": "03791db2779f73d9044c86f3b1f51a2f2c9b4343f9717fd1e2ccf0aa65da85c6", "tool": "Python", "notebook": "Convert time delta to months", "action": "", "tags": ["#python", "#datetime", "#timedelta", "#calculate", "#date", "#time"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-22", "created_at": "2023-05-22", "description": "This notebook convert the time delta between two dates to months.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_time_delta_to_months.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_time_delta_to_months.ipynb", "imports": ["datetime.datetime"], "image_url": ""}, {"objectID": "e124d5cbb19b3fbe5b868dcf46bb16fa5e5b8c2d1caf34e712fd11ce10360bf5", "tool": "Python", "notebook": "Convert units", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#length", "#temperature", "#weight", "#time", "#volume", "#speed"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-19", "created_at": "2023-06-19", "description": "This notebook shows you how to convert units (length, temperature, weight, time, volume, speed) using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_units.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_units.ipynb", "imports": [], "image_url": ""}, {"objectID": "7b235c7c8db12861213c775e7d7ae25d6d24f1ab8ef535cb438e651f2e7a2d47", "tool": "Python", "notebook": "Convert volume", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#volume"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert volume using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_volume.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_volume.ipynb", "imports": [], "image_url": ""}, {"objectID": "f5e386585bbd320a3d0dde509039baec9d255f0945b148fba09d94b400642d56", "tool": "Python", "notebook": "Convert weight", "action": "", "tags": ["#python", "#convert", "#units", "#snippet", "#operations", "#weight"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-21", "created_at": "2023-06-21", "description": "This notebook shows you how to convert weight using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Convert_weight.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Convert_weight.ipynb", "imports": [], "image_url": ""}, {"objectID": "8b78cb9c1482a8aa5d796c3cb0084b2af3a3e9efaeebeb65de5a5c82143af234", "tool": "Python", "notebook": "Copy files and subdir from directory to another directory", "action": "", "tags": ["#python", "#os", "#shutil", "#operations", "#snippet"], "author": "Parth Panchal", "author_url": "https://www.linkedin.com/in/parthpanchal8401/", "updated_at": "2023-04-12", "created_at": "2022-10-14", "description": "This notebook provides a Python script to copy files and subdirectories from one directory to another.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Copy_files_and_subdir_from_directory_to_another_directory.ipynb.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Copy_files_and_subdir_from_directory_to_another_directory.ipynb.ipynb", "imports": ["shutil", "os"], "image_url": ""}, {"objectID": "7a22581a89abec8e9064d61cbe041eb2714389315534606904bb777e73f3eb7b", "tool": "Python", "notebook": "Create Email Combination with Firstname Lastname Domain address", "action": "", "tags": ["#python", "#email", "#combination", "#firstname", "#lastname", "#domain", "#sales", "#prospect"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-27", "description": "This notebook will create a list of emails combination with firstname, lastname and domain address. This notebook can be used to find and test an email address for a prospect.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Create_Email_Combination_with_Firstname_Lastname_Domain_address.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Create_Email_Combination_with_Firstname_Lastname_Domain_address.ipynb", "imports": [], "image_url": ""}, {"objectID": "287f76fafc85efc85412756d89bbbcfe44730e5f2bb38149ac0374522f23c2dd", "tool": "Python", "notebook": "Create Strong Random Password", "action": "", "tags": ["#python", "#password", "#random", "#snippet", "#operations"], "author": "Sunny", "author_url": "https://www.linkedin.com/in/sunny-chugh-ab1630177/", "updated_at": "2023-04-12", "created_at": "2022-11-30", "description": "The objective of this notebook is to Create Strong random password.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Create_Strong_Random_Password.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Create_Strong_Random_Password.ipynb", "imports": ["random", "string"], "image_url": ""}, {"objectID": "dc2e29332347a26e140e365029573d514acb1dae172eb15ce21ad5c557bba2c6", "tool": "Python", "notebook": "Create dataframe from lists", "action": "", "tags": ["#python", "#list", "#dataframe", "#snippet", "#pandas", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to use Python to create a dataframe from lists.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Create_dataframe_from_lists.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Create_dataframe_from_lists.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "d7d863424921d5fede902600607bd28d9bf4753d1c27af768c5b35cc1d1abe0c", "tool": "Python", "notebook": "Create dict from lists", "action": "", "tags": ["#python", "#list", "#dict", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides instructions on how to create a dictionary from two lists in Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Create_dict_from_lists.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Create_dict_from_lists.ipynb", "imports": [], "image_url": ""}, {"objectID": "03afcf02c7e061c5c2deb5f4d6cd7467b149399644cb1bba64ea2e36dd15f196", "tool": "Python", "notebook": "Delete entire directory tree", "action": "", "tags": ["#python", "#shutil", "#delete", "#folder", "#file", "#directory"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-04-26", "created_at": "2023-04-26", "description": "This notebook will show how to delete an entire directory tree using the shutil library. \n\nShutil module in Python provides many functions of high-level operations on files and collections of files. It comes under Python\u2019s standard utility modules. This module helps in automating the process of copying and removal of files and directories. \n\n`shutil.rmtree()` is used to delete an entire directory tree, path must point to a directory (but not a symbolic link to a directory).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Delete_entire_directory_tree.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Delete_entire_directory_tree.ipynb", "imports": ["shutil"], "image_url": ""}, {"objectID": "7a281dea954ab667015391ddacef8e3c6f808fa79c747bb70d288124ffbdd5cb", "tool": "Python", "notebook": "Download Image from URL", "action": "", "tags": ["#python", "#image", "#url", "#naas", "#snippet"], "author": "Abraham Israel", "author_url": "https://www.linkedin.com/in/abraham-israel/", "updated_at": "2023-07-03", "created_at": "2022-10-09", "description": "This notebook demonstrates how to download an image from a URL using Python and `wget` library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Download_Image_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Download_Image_from_URL.ipynb", "imports": ["wget", "wget", "IPython.display.Image"], "image_url": ""}, {"objectID": "872420f12cee8df45fe4b26b0fd0b0626f804e3babb46767478343b72b8a9577", "tool": "Python", "notebook": "Download PDF from URL", "action": "", "tags": ["#python", "#pdf", "#snippet", "#url", "#naas", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-04-29", "description": "This notebook provides a step-by-step guide to downloading a PDF file from a URL using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Download_PDF_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Download_PDF_from_URL.ipynb", "imports": ["urllib"], "image_url": ""}, {"objectID": "957c6b7099115e2ae404fdeea269f27e570a97ae941a603faad6a55502ce016f", "tool": "Python", "notebook": "Download ZIP from URL", "action": "", "tags": ["#python", "#urllib", "#download", "#zip", "#url", "#request"], "author": "Hamid Mukhtar", "author_url": "https://www.linkedin.com/in/mukhtar-hamid/", "updated_at": "2023-05-04", "created_at": "2023-04-11", "description": "This notebook will show how to download a ZIP file from a URL using urllib.request.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Download_ZIP_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Download_ZIP_from_URL.ipynb", "imports": ["os", "shutil", "urllib"], "image_url": ""}, {"objectID": "4c668b1964bb6e1a96dfe7a4ae9cfd6e4a9054a13f2852badfef2a5f5cc31077", "tool": "Python", "notebook": "Download audio file from URL", "action": "", "tags": ["#python", "#download", "#snippet", "#url", "#naas", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-07-23", "created_at": "2023-07-23", "description": "This notebook demonstrates how to download audio file from an URL using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Download_audio_file_from_URL.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Download_audio_file_from_URL.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "aed246dedce0dfc3440f08d081ff16e62e1dda1fd1cc0b6c5f39b88ea8617e89", "tool": "Python", "notebook": "Explore Dataset with Pivot Table", "action": "", "tags": ["#python", "#dataset", "#pivottable", "#dataexploration"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2023-01-30", "description": "This notebook allows you to interactively explore and analyze a dataset using a pivot table. It uses the `pivottablejs` library to generate a dynamic pivot table in your web browser, giving you the ability to sort, filter, and aggregate data in real-time. This template provides a simple and intuitive way to explore and gain insights from your dataset, making it a valuable tool for data analysis and visualization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Explore_Dataset_with_Pivot_Table.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Explore_Dataset_with_Pivot_Table.ipynb", "imports": ["pandas", "pivottablejs.pivot_ui", "pivottablejs.pivot_ui"], "image_url": ""}, {"objectID": "4d33b51aeb8bff0d6e56610f53de035ed263c78d3f2399eaee3990e4ccac4b85", "tool": "Python", "notebook": "Extract characters from string", "action": "", "tags": ["#python", "#extract", "#string", "#character"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-13", "created_at": "2023-06-08", "description": "This notebook will show how to extract characters from a string.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Extract_characters_from_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Extract_characters_from_string.ipynb", "imports": [], "image_url": ""}, {"objectID": "f0ed397656db4d35042f2e3dba5ca56a23ab02a7d4a4642cccc077086eaf0e1f", "tool": "Python", "notebook": "Find Phone Number in string", "action": "", "tags": ["#python", "#string", "#number", "#naas", "#operations", "#snippet"], "author": "Anas Tazir", "author_url": "https://github.com/anastazir", "updated_at": "2023-04-12", "created_at": "2022-10-06", "description": "This notebook provides a Python script to identify and extract phone numbers from a given string.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Find_Phone_Number_in_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Find_Phone_Number_in_string.ipynb", "imports": [], "image_url": ""}, {"objectID": "c53dc95597572e013944cf90ff5480eabd8f4deb4a7d116fcb2ef26ad5e76181", "tool": "Python", "notebook": "Find differences between strings", "action": "", "tags": ["#python", "#strings", "#differences", "#compare", "#find", "#string"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-14", "created_at": "2023-06-14", "description": "This notebook will compare two strings and find the differences between them. It is useful for users to quickly identify the differences between two strings.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Find_differences_between_strings.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Find_differences_between_strings.ipynb", "imports": [], "image_url": ""}, {"objectID": "c481bc8d4efd4aff05e1577eb197f2cfeed1834b5fd496a8438a190c5684c9f8", "tool": "Python", "notebook": "Flatten nested dict", "action": "", "tags": ["#python", "#dict", "#flatten", "#nested", "#data", "#structure"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will show how to flatten a nested dict in Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Flatten_nested_dict.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Flatten_nested_dict.ipynb", "imports": [], "image_url": ""}, {"objectID": "333b5d2d5a8adf1385cca957efd4e1193793c91593fdb4ba7eae7593fe88d64f", "tool": "Python", "notebook": "Get Word Definition and Translation", "action": "", "tags": ["#python", "#dictionary", "#project", "#word", "#snippet"], "author": "Sriniketh Jayasendil", "author_url": "https://twitter.com/srini047/", "updated_at": "2023-04-12", "created_at": "2022-10-18", "description": "This notebook get world definition and translation from English using PyDictionary.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_Word_Definition_and_Translation.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_Word_Definition_and_Translation.ipynb", "imports": ["PyDictionary.PyDictionary", "PyDictionary.PyDictionary"], "image_url": ""}, {"objectID": "712b3b28a79e451c9bcce99b1cfd032a25416ce695e3c59f9f455df31523b8da", "tool": "Python", "notebook": "Get all files from directory", "action": "", "tags": ["#python", "#naas", "#glob", "#pprint", "#snippet"], "author": "Ayoub Berdeddouch", "author_url": "https://www.linkedin.com/ayoub-berdeddouch", "updated_at": "2023-04-12", "created_at": "2022-10-18", "description": "This notebook gives you the ability to get all files from a directory even in a sub-directory.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_all_files_from_directory.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_all_files_from_directory.ipynb", "imports": ["glob", "os.path"], "image_url": ""}, {"objectID": "99b7889c02066945ea9978b756ab4b00c081c15b2f18dc3f7161b8a4f08923d8", "tool": "Python", "notebook": "Get coordinates from address", "action": "", "tags": ["#python", "#snippet", "#naas", "#geocoder"], "author": "Suhas B", "author_url": "https://www.linkedin.com/in/suhasbrao/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook get coordinates from a given address.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_coordinates_from_address.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_coordinates_from_address.ipynb", "imports": ["geocoder", "geocoder"], "image_url": ""}, {"objectID": "785972e87c0df9d4eae498b1c5c285f8fb9f85218c9745ddd20f3a04002b5659", "tool": "Python", "notebook": "Get emojis from text", "action": "", "tags": ["#python", "#text", "#emoji", "#nlp", "#string", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-23", "created_at": "2023-08-23", "description": "This notebook will show how to get emojis from text using `emoji` and `regex` libraries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_emojis_from_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_emojis_from_text.ipynb", "imports": ["emoji", "emoji", "regex"], "image_url": ""}, {"objectID": "8a57a4125fe02a9041a6723a3e80eea843fe2a5efb705b899c2558c8bbd5248e", "tool": "Python", "notebook": "Get last file modified from directy", "action": "", "tags": ["#python", "#os", "#library", "#file", "#modified", "#directory"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-23", "description": "This notebook will show how to get the last file modified from a directory using the os library.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_last_file_modified_from_directy.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_last_file_modified_from_directy.ipynb", "imports": ["os"], "image_url": ""}, {"objectID": "ebc58d505f37c456cff8fedcc2252596d0f3957a268f00d45856b1231f12e98e", "tool": "Python", "notebook": "Get next occurrences of a cron job", "action": "", "tags": ["#python", "#cron", "#croniter", "#job", "#occurrences", "#scheduling"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-09", "created_at": "2023-05-09", "description": "This notebook will show how to get the next x occurrences of your cron job using croniter. It is usefull for organizations to schedule tasks and jobs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_next_occurrences_of_a_cron_job.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_next_occurrences_of_a_cron_job.ipynb", "imports": ["croniter", "croniter", "pytz", "datetime.datetime"], "image_url": ""}, {"objectID": "273a29ff310403095ebba2c30813413cdbea48f497eb114a7224762e8ae1ebf3", "tool": "Python", "notebook": "Get random number", "action": "", "tags": ["#python", "#number", "#generation", "#random", "#snippet", "#operation"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-08", "created_at": "2023-06-07", "description": "This notebook demonstrates how to get random numbers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_random_number.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_random_number.ipynb", "imports": ["random"], "image_url": ""}, {"objectID": "528d537bbac178bf8781873b2a2aad8e0496c9e1536508e3585d6ad24f41addc", "tool": "Python", "notebook": "Get a random word", "action": "", "tags": ["#python", "#word", "#random", "#snippet"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-19", "created_at": "2023-06-14", "description": "This notebook show how to get a random word.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Get_random_word.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Get_random_word.ipynb", "imports": ["random", "nltk.corpus.wordnet", "nltk.corpus.wordnet", "nltk"], "image_url": ""}, {"objectID": "381a06edafb0d844bae219bab0e7cd6772d3ed58bbb597161a0ffecce70fff53", "tool": "Python", "notebook": "List specific files from directory and subdirectories", "action": "", "tags": ["#python", "#glob", "#os", "#files", "#directory", "#subdirectories"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-31", "created_at": "2023-05-31", "description": "This notebook list all specific files from a directory and its subdirectories using glob and os libraries. It is usefull to quickly list all files from a directory and its subdirectories.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_List_specific_files_from_directory_and_subdirectories.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_List_specific_files_from_directory_and_subdirectories.ipynb", "imports": ["glob", "os"], "image_url": ""}, {"objectID": "34facbf13a7e56bfaa689c8351e1f7980a5b0ac0c6818da5b29d7930907d14fd", "tool": "Python", "notebook": "Locate address on map", "action": "", "tags": ["#python", "#geocoding", "#city", "#coordinates", "#location", "#api"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will show how to get coordinates from an address using Python and display it on a map.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Locate_address_on_map.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Locate_address_on_map.ipynb", "imports": ["geocoder", "geocoder", "pandas", "plotly.express"], "image_url": ""}, {"objectID": "f6bac2f96a6ae10b5e54f83f2ed151f5c4094bee0516f3ee795de50c02c95791", "tool": "Python", "notebook": "Locate city on map", "action": "", "tags": ["#python", "#geocoding", "#city", "#coordinates", "#location", "#api"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook will show how to get coordinates from a city name using Python and display it on a map.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Locate_city_on_map.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Locate_city_on_map.ipynb", "imports": ["geocoder", "geocoder", "pandas", "plotly.express"], "image_url": ""}, {"objectID": "d55e369e1ac2a640e4019f281f7944654c06cb9f2b0c27c0f1f2f129dd5fa099", "tool": "Python", "notebook": "Locate coordinates", "action": "", "tags": ["#python", "#snippet", "#naas", "#geocoder"], "author": "Suhas B", "author_url": "https://www.linkedin.com/in/suhasbrao/", "updated_at": "2023-04-12", "created_at": "2023-03-24", "description": "This notebook provides a way to find the geographic coordinates of a given location using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Locate_coordinates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Locate_coordinates.ipynb", "imports": ["geocoder", "geocoder"], "image_url": ""}, {"objectID": "0d30d21161d2fb93660e3177f2620431276c202a1814b1913273755b86468e8a", "tool": "Python", "notebook": "Looping Over Dataframe", "action": "", "tags": ["#python", "#pandas", "#python", "#loops", "#dataframes", "#forloop", "#loop", "#snippet", "#operations"], "author": "Oketunji Oludolapo", "author_url": "https://www.linkedin.com/in/oludolapo-oketunji/", "updated_at": "2023-06-06", "created_at": "2021-10-08", "description": "This notebook provides an overview of how to use loops to iterate over a dataframe in Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Looping_Over_Dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Looping_Over_Dataframe.ipynb", "imports": ["pandas", "numpy"], "image_url": ""}, {"objectID": "b3250febe49c96eaa6b828a7d7db8ea79a7be078466bf984f7e3d0495291d190", "tool": "Python", "notebook": "Manage code error with try except", "action": "", "tags": ["#python", "#error", "#try", "#exception", "#snippet"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-16", "created_at": "2023-06-15", "description": "This notebook will demonstrate how to manage code error using try except. \nThe `try` block lets you test a block of code for errors.\nThe `except` block lets you handle the error. You can specify the type of exception to manage error.\nThe `else` block lets you execute code when there is no error.\nThe `finally` block lets you execute code, regardless of the result of the try- and except blocks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Manage_exception_with_try_except.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Manage_exception_with_try_except.ipynb", "imports": [], "image_url": ""}, {"objectID": "0ab9494e481d7f7c2fdead13ca4b8a0d8c8caca6cc43f1c1386eeaa60915720b", "tool": "Python", "notebook": "Organize Directories based on file types", "action": "", "tags": ["#organize", "#files", "#directories"], "author": "Ahmed Mousa", "author_url": "https://www.linkedin.com/in/akmousa/", "updated_at": "2023-04-12", "created_at": "2022-11-11", "description": "This notebook organizes your files based on their extensions to directories for data scientists", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Organize_Directories_based_on_file_types.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Organize_Directories_based_on_file_types.ipynb", "imports": ["shutil.move", "os.path", "os", "glob", "pathlib"], "image_url": ""}, {"objectID": "6b201a517cee73c048da83f5eeea5a372c37d868c68b1ba958a7eb3723778014", "tool": "Python", "notebook": "Pseudonym generator", "action": "", "tags": ["#python", "#pseudonym", "#generation", "#random", "#snippet", "#operation"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-19", "created_at": "2023-06-15", "description": "This notebook demonstrates how to get random pseudonym.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Pseudonym_generator.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Pseudonym_generator.ipynb", "imports": ["random"], "image_url": ""}, {"objectID": "764a61ccadd589be64a9953b0c2f0ae854335e74fb7dd944ed5585051a031eb8", "tool": "Python", "notebook": "Read pickle file", "action": "", "tags": ["#python", "#pickle", "#file", "#load", "#data", "#io"], "author": "Kaushal Krishna", "author_url": "https://www.linkedin.com/in/kaushal-krishna-a48959153/", "updated_at": "2023-04-12", "created_at": "2023-03-13", "description": "This notebook loads a dictionary from pickle object. Loading a dictionary using pickle is a quick and easy process. With just a few lines of code, you can store your dictionary data from a pickle file. \n\nPickle can cause critical security vulnerabilities in code, you should never unpickle data you don\u2019t trust. If you must accept data from an untrusted client, you should use the safer JSON format. And, if you transfer pickled data between trusted applications but need extra measures to prevent tampering, you should generate an HMAC signature you can verify before unpickling.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Read_pickle_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Read_pickle_file.ipynb", "imports": ["pickle"], "image_url": ""}, {"objectID": "0d78a6b4a629c2de8f39bc5862abe5d91077ed048c9ae5b3df5277f419395f72", "tool": "Python", "notebook": "Remove all spaces on string", "action": "", "tags": ["#python", "#remove", "#string", "#space"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-13", "created_at": "2023-06-13", "description": "This notebook shows how to remove all spaces from a string using two different methods", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Remove_all_spaces_on_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Remove_all_spaces_on_string.ipynb", "imports": [], "image_url": ""}, {"objectID": "cfcf72d570d6c8d8d5cb799af70b6e84175428ca194c3838cbaad7876b61aae1", "tool": "Python", "notebook": "Remove duplicates from a list", "action": "", "tags": ["#python", "#list", "#remove", "#duplicates", "#function", "#data"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-28", "created_at": "2023-08-28", "description": "This notebook explains how to remove duplicates from a list in Python. It is usefull for data cleaning and data wrangling.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Remove_duplicates_from_a_list.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Remove_duplicates_from_a_list.ipynb", "imports": [], "image_url": ""}, {"objectID": "2420ecf7c6601531c93fcf5bd3fd74ae7584c3b666889d872cecdd186ac28502", "tool": "Python", "notebook": "Save dict to pickle", "action": "", "tags": ["#python", "#pickle", "#file", "#save", "#data", "#io"], "author": "Kaushal Krishna", "author_url": "https://www.linkedin.com/in/kaushal-krishna-a48959153/", "updated_at": "2023-04-12", "created_at": "2023-03-13", "description": "This notebook saves a dictionary to pickle object. Saving a dictionary using pickle is a quick and easy process. With just a few lines of code, you can store your dictionary data in a binary format that can be easily loaded later on.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Save_dict_to_pickle.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Save_dict_to_pickle.ipynb", "imports": ["pickle"], "image_url": ""}, {"objectID": "cd0eb2047f4ba6ff6d26c2a2842f93e989014f5a4902b69592fd075bbb6859e4", "tool": "Python", "notebook": "Split string", "action": "", "tags": ["#python", "#file", "#string", "#url", "#split", "#snippet", "#operations"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-09", "created_at": "2023-06-08", "description": "This notebook shows you how to split a string object. The `split()` function in Python is useful for dividing a string into smaller parts based on a specified delimiter. It enables efficient string parsing, data cleaning, user input processing, and tokenization in natural language processing tasks.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Split_string.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Split_string.ipynb", "imports": [], "image_url": ""}, {"objectID": "51927e37f1c930d38501a5524f66df6a3305327b1f73da29f93de18680b7b723", "tool": "Python", "notebook": "Transform String to Secure Hash Algorithm", "action": "", "tags": ["#python", "#security", "#hash", "#algorithm", "#encryption", "#sha"], "author": "Firstname LastName", "author_url": "https://www.linkedin.com/in/xxxxxx/", "updated_at": "2023-06-19", "created_at": "2023-06-19", "description": "This notebook will demonstrate how to create a secure hash algorithm using Python. It is useful for organizations to ensure data security and integrity.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Transform_string_to_Secure_Hash_Algorithm.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Transform_string_to_Secure_Hash_Algorithm.ipynb", "imports": ["hashlib", "hashlib"], "image_url": ""}, {"objectID": "6de9c1a35eb23d9d9f9c7f42401106d9b96ac0cfc31c95f41ee0fa4190b8ed10", "tool": "Python", "notebook": "Validate email and phone numbers", "action": "", "tags": ["#python", "#twilio", "#project", "#call", "#mobile", "#snippet"], "author": "Sriniketh Jayasendil", "author_url": "https://twitter.com/srini047/", "updated_at": "2023-06-05", "created_at": "2023-06-05", "description": "This notebook validates a given email address and phone number using `re` and `phonenumbers` modules.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Python/Python_Validate_email_and_phone_numbers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Python/Python_Validate_email_and_phone_numbers.ipynb", "imports": ["re", "phonenumbers", "phonenumbers"], "image_url": ""}, {"objectID": "2df55afca82f21837a817a57c842dcf4460d0908883b76b3c64576ef8f09f864", "tool": "Pyvis", "notebook": "Create a network visualization", "action": "", "tags": ["#python", "#naas", "#scheduler", "#network", "#snippet", "#analytics"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2022-07-27", "description": "With this notebook, you can create a network graph to visualize the relations between different elements.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Pyvis/Pyvis_Create_a_network_visualization.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Pyvis/Pyvis_Create_a_network_visualization.ipynb", "imports": ["naas", "pyvis.network.Network"], "image_url": ""}, {"objectID": "a7d100e0889cb14f5c824f377c6a44885ee52aa18f9155282c1d08bd2c642f26", "tool": "Qonto", "notebook": "Get cash position trend", "action": "", "tags": ["#qonto", "#bank", "#statement", "#naas_drivers", "#plotly", "#linechart", "#finance", "#analytics", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "This notebook provides an overview of cash position trends for Qonto customers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_cash_position_trend.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_cash_position_trend.ipynb", "imports": ["naas_drivers.qonto", "datetime.datetime", "pandas", "plotly.graph_objects"], "image_url": ""}, {"objectID": "31964e4e6eb09f073ef7878131675b687729a27f0a488f0186e6666b735b861e", "tool": "Qonto", "notebook": "Get organizations", "action": "", "tags": ["#qonto", "#bank", "#organizations", "#positions", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "Qonto is a financial service that helps organizations manage their finances and get organized.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_organizations.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_organizations.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "ea9e48f2660d5e99bf7c98f34152cb079f7643c88a1cb3bbb689828118d28d35", "tool": "Qonto", "notebook": "Get positions", "action": "", "tags": ["#qonto", "#bank", "#organizations", "#positions", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-01-26", "description": "This notebook provides an overview of the positions available through Qonto, a digital banking service.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_positions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_positions.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "6a9ad826ce7186c78e78078a3ee167f0a0226478c26805fe708b78eed6659048", "tool": "Qonto", "notebook": "Get statement", "action": "", "tags": ["#qonto", "#bank", "#statement", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "This notebook provides a convenient way to access and view your Qonto account statements.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_statement.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_statement.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "ae25587a760343b76cd21871e8fb5a9348e957b7e89fd66c66edeaa5683a1bcc", "tool": "Qonto", "notebook": "Get statement barline", "action": "", "tags": ["#qonto", "#bank", "#statement", "#plotly", "#barline", "#naas_drivers", "#finance", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-11-05", "description": "This notebook provides a convenient way to generate barlines for Qonto statements.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_statement_barline.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_statement_barline.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "e34d7a0d1f542aed1377cf95b45f7b2ae126679533186edb3529908fe0b406c8", "tool": "Qonto", "notebook": "Get statement ranking by category", "action": "", "tags": ["#qonto", "#bank", "#statement", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "This notebook provides a way to organize and analyze financial statements by category to gain insights into spending patterns.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_statement_ranking_by_category.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_statement_ranking_by_category.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "f64cd3ab2aa93155bc8e1bf38148fb31ec7d96744518fe4426086a63de69c306", "tool": "Qonto", "notebook": "Get statement summary by operation type", "action": "", "tags": ["#qonto", "#bank", "#statement", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "This notebook provides a summary of financial operations by type for Qonto users.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_statement_summary_by_operation_type.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_statement_summary_by_operation_type.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "b79366dec95c9ac8fd048926ce03d2ce291bfc116f06d4c12182d386496c48bd", "tool": "Qonto", "notebook": "Get transactions", "action": "", "tags": ["#qonto", "#bank", "#transactions", "#naas_drivers", "#finance", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-02-16", "description": "Qonto's notebook allows you to easily access and manage your transactions.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Get_transactions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Get_transactions.ipynb", "imports": ["naas_drivers.qonto"], "image_url": ""}, {"objectID": "9cc3c79640025122d4d08f417b90e3c33382632218f192b7f91b09e0e07d7a36", "tool": "Qonto", "notebook": "Releve de compte augmente", "action": "", "tags": ["#qonto", "#bank", "#statement", "#naas_drivers", "#notification", "#emailbuilder", "#asset", "#scheduler", "#naas", "#finance", "#automation", "#analytics", "#plotly", "#email", "#html", "#image", "#excel"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-07-21", "description": "Recevez un relev\u00e9 de compte augment\u00e9 par email gratuitement, chaque semaine, gr\u00e2ce \u00e0 un template Naas.ai (moteur de donn\u00e9es opensource, 100 cr\u00e9dits offert par mois). \n

\n-Dur\u00e9e de l'installation = 5 minutes
\n-Support d'installation = Guide vid\u00e9o
\n-Niveau = Facile
", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Qonto/Qonto_Releve_de_compte_augmente.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Qonto/Qonto_Releve_de_compte_augmente.ipynb", "imports": ["naas_drivers.qonto", "datetime.datetime, timedelta", "pandas", "naas", "naas"], "image_url": ""}, {"objectID": "b011d4cb48a9cb6019a9bf3d65607a661c3b457d783fd0a31f524e0d36d500a0", "tool": "Quandl", "notebook": "Get data from API", "action": "", "tags": ["#quandl", "#marketdata", "#opendata", "#finance", "#snippet", "#matplotlib"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a guide to retrieving data from the Quandl API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Quandl/Quandl_Get_data_from_API.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Quandl/Quandl_Get_data_from_API.ipynb", "imports": ["quandl", "matplotlib.pyplot"], "image_url": ""}, {"objectID": "5fc16e4d7e6415f3d4c6c3adb959707425d1e22a89f4c9ed83dce4819a6524be", "tool": "Quandl", "notebook": "Get data from CSV", "action": "", "tags": ["#quandl", "#marketdata", "#opendata", "#finance", "#snippet", "#csv"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-02-28", "description": "This notebook provides a guide to retrieving data from CSV files using the Quandl API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Quandl/Quandl_Get_data_from_CSV.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Quandl/Quandl_Get_data_from_CSV.ipynb", "imports": ["matplotlib.pyplot", "pandas", "os"], "image_url": ""}, {"objectID": "8531d6684ed740ec2ff6fd79b946c490932a6fb0b5f8929ace7f53c543152096", "tool": "Reddit", "notebook": "Get Hot Posts From Subreddit", "action": "", "tags": ["#reddit", "#subreddit", "#data", "#hottopics", "#rss", "#information", "#opendata", "#snippet", "#dataframe"], "author": "Yaswanthkumar GOTHIREDDY", "author_url": "https://www.linkedin.com/in/yaswanthkumargothireddy/", "updated_at": "2023-04-12", "created_at": "2021-08-16", "description": "This notebook allows users to retrieve the hottest posts from a specified subreddit on Reddit.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Reddit/Reddit_Get_Hot_Posts_From_Subreddit.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Reddit/Reddit_Get_Hot_Posts_From_Subreddit.ipynb", "imports": ["praw", "pandas", "numpy", "datetime.datetime"], "image_url": ""}, {"objectID": "8812c328726e145037006c5dcb182640230ec58dcb57aec562289e838e3ae409", "tool": "Redshift", "notebook": "Connect with SQL Magic and IAM Credentials", "action": "", "tags": ["#redshift", "#database", "#snippet", "#operations", "#naas", "#jupyternotebooks"], "author": "Caleb Keller", "author_url": "https://www.linkedin.com/in/calebmkeller/", "updated_at": "2023-04-12", "created_at": "2021-07-16", "description": "## Input\n\n- ipython-sql\n- boto3\n- psycopg2\n- sqlalchemy-redshift\n\nIf you're running in NaaS, you can execute the below to install the necessary libraries.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Redshift/Redshift_Connect_with_SQL_Magic_and_IAM_Credentials.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Redshift/Redshift_Connect_with_SQL_Magic_and_IAM_Credentials.ipynb", "imports": ["boto3", "psycopg2", "getpass", "pandas", "urllib.parse"], "image_url": ""}, {"objectID": "4f03512608dfc108d56e8bd6f0396f48d71e76adca829f5753f7ed8172a2f2de", "tool": "RegEx", "notebook": "Check email validity", "action": "", "tags": ["#regex", "#python", "#email", "#validity", "#check", "#string"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook will demonstrate how to check the validity of an email address using `re` module. \nThe `re.search()` function in Python's re module allows you to search for a specified pattern within a string. It returns a match object if the pattern is found, enabling you to extract relevant information from the string based on the given pattern.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/RegEx/RegEx_Check_email_validity.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/RegEx/RegEx_Check_email_validity.ipynb", "imports": ["re"], "image_url": ""}, {"objectID": "685a1f40f7aa4a1232db34e0359c257af7cfb943e0ababc3ce2c39cb4d53a733", "tool": "RegEx", "notebook": "Match pattern", "action": "", "tags": ["#regex", "#python", "#snippet", "#operations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook demonstrates how to match a pattern in a string using `re.search()` and `re.match()`. The main difference between `re.search()` and `re.match()` lies in how they apply pattern matching to the input string. `re.search()` scans the entire input string and returns the first occurrence of a pattern match, regardless of its position within the string. On the other hand, `re.match()` only checks for a pattern match at the beginning of the string.\n\nTo start, we recommand you to test your regular expression using this website: https://regex101.com/", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/RegEx/RegEx_Match_pattern.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/RegEx/RegEx_Match_pattern.ipynb", "imports": ["re"], "image_url": ""}, {"objectID": "8f7a2b09ec80741fdd6479ff42823dd333560ec26a5dad2ef45593c41062ba48", "tool": "RegEx", "notebook": "Remove HTML tags from text", "action": "", "tags": ["#regex", "#python", "#html", "#text", "#remove", "#tags", "#string"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-08-25", "created_at": "2023-08-25", "description": "This notebook shows how to remove HTML tags from a text using Python. It is usefull for organizations that need to clean text from HTML tags before using it.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/RegEx/RegEx_Remove_HTML_tags_from_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/RegEx/RegEx_Remove_HTML_tags_from_text.ipynb", "imports": ["re"], "image_url": ""}, {"objectID": "c1fb82c7c15421cc52e119f4c0989d93fff90d185ae48e67c528a81197f697ce", "tool": "RegEx", "notebook": "Replace value in text in a specific paragraph", "action": "", "tags": ["#regex", "#re", "#python", "#string", "#replace", "#text", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-06", "created_at": "2023-06-06", "description": "This notebook will show how to replace a value in a specific paragraph of a text using `re` module. The `re.sub()` function enables you to perform pattern-based string substitutions. It allows you to replace occurrences of a pattern in a given string with a specified replacement.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/RegEx/RegEx_Replace_value_in_text_in_a_specific_paragraph.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/RegEx/RegEx_Replace_value_in_text_in_a_specific_paragraph.ipynb", "imports": ["re"], "image_url": ""}, {"objectID": "305c5c190163ec3d354712a27c233a097b14c1492cd412900d9283b6cacc4424", "tool": "Remoteok", "notebook": "Get jobs from categories", "action": "", "tags": ["#remoteok", "#jobs", "#csv", "#snippet", "#opendata", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-03", "description": "Remoteok is a job search platform that allows users to find jobs from a variety of categories.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remoteok/Remoteok_Get_jobs_from_categories.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remoteok/Remoteok_Get_jobs_from_categories.ipynb", "imports": ["pandas", "requests", "datetime.datetime", "time"], "image_url": ""}, {"objectID": "d49a83032e1012afe8025a8ee46e5eca93ea3f5212272486e2ea692bd2783590", "tool": "Remoteok", "notebook": "Post daily jobs on slack", "action": "", "tags": ["#remoteok", "#jobs", "#slack", "#gsheet", "#naas_drivers", "#automation", "#opendata", "#text"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-03", "description": "This notebook allows you to post daily jobs from Remoteok to your Slack workspace.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remoteok/Remoteok_Post_daily_jobs_on_slack.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remoteok/Remoteok_Post_daily_jobs_on_slack.ipynb", "imports": ["pandas", "requests", "datetime.datetime", "time", "naas_drivers.gsheet, slack", "naas"], "image_url": ""}, {"objectID": "2e0a5121d38b84cc390290272eea893ea63d79e5ce7993a046e6c6f332824dfc", "tool": "Remotive", "notebook": "Get categories from job", "action": "", "tags": ["#remotive", "#categories", "#snippet", "#opendata", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-02-14", "description": "This notebook provides a way to categorize jobs posted on Remotive.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remotive/Remotive_Get_categories_from_job.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remotive/Remotive_Get_categories_from_job.ipynb", "imports": ["pandas", "requests"], "image_url": ""}, {"objectID": "e141af26ebf6859a4e26fdf19cbbef08826a4a49ba12d240412d69b89f8b322b", "tool": "Remotive", "notebook": "Get jobs from categories", "action": "", "tags": ["#remotive", "#jobs", "#csv", "#snippet", "#opendata", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-02-14", "description": "This notebook provides a comprehensive list of remote job opportunities from a variety of categories.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remotive/Remotive_Get_jobs_from_categories.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remotive/Remotive_Get_jobs_from_categories.ipynb", "imports": ["pandas", "requests", "time", "datetime.datetime"], "image_url": ""}, {"objectID": "521ba7b3ee67b30d454150ddda5168f097b9f305cc6b56c02297e603aade0ba9", "tool": "Remotive", "notebook": "Post daily jobs on slack", "action": "", "tags": ["#remotive", "#jobs", "#slack", "#gsheet", "#naas_drivers", "#automation", "#opendata", "#text"], "author": "Sanjeet Attili", "author_url": "https://www.linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-02-09", "description": "Remotive is a Slack app that allows users to post and find remote job opportunities on a daily basis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remotive/Remotive_Post_daily_jobs_on_slack.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remotive/Remotive_Post_daily_jobs_on_slack.ipynb", "imports": ["pandas", "bs4.BeautifulSoup", "requests", "datetime.datetime", "time", "naas_drivers.gsheet, slack", "naas"], "image_url": ""}, {"objectID": "0bae0fd45a541ae9aa454e8fce4a5df9f94d001e54ac616de251c2cf19566aeb", "tool": "Remotive", "notebook": "Send jobs to gsheet", "action": "", "tags": ["#remotive", "#jobs", "#gsheet", "#naas_drivers", "#automation", "#opendata", "#googlesheets"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-02-14", "description": "This notebook allows users to quickly and easily send jobs to a Google Sheet.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Remotive/Remotive_Send_jobs_to_gsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Remotive/Remotive_Send_jobs_to_gsheet.ipynb", "imports": ["pandas", "requests", "datetime.datetime", "time", "naas_drivers.gsheet", "naas"], "image_url": ""}, {"objectID": "c760989aeb646043394a467ce2c6b687a3066f01ab69f8e63a21755361bd5fe0", "tool": "Request", "notebook": "Basic HTTP GET", "action": "", "tags": ["#request", "#http", "#get", "#library", "#python", "#api"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-14", "created_at": "2023-06-09", "description": "This notebook provides a template for making a basic HTTP GET request using the requests library. It covers importing the library, making the request, handling the response, and displaying the retrieved data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Request/Request_Basic_HTTP_GET_Request.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Request/Request_Basic_HTTP_GET_Request.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "e4657f273b8f1a16243f2cf42b54bf6280fd4415f91496be69bae05c845828cc", "tool": "Request", "notebook": "Handling Errors and Exceptions", "action": "", "tags": ["#request", "#error", "#exception", "#handling", "#python", "#library"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-26", "created_at": "2023-06-09", "description": "This notebook template explores how to handle errors and exceptions when using the requests library. It provides examples of error handling techniques, including proper status code checking, handling timeouts, and dealing with connection errors.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Request/Request_Handling_Errors_and_Exceptions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Request/Request_Handling_Errors_and_Exceptions.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "9678f6e9d554c476ab1edd5e4046bdb3c55626b16b11a91767b3ef45250215d2", "tool": "Request", "notebook": "Sending POST s with Data", "action": "", "tags": ["#requests", "#post", "#data", "#python", "#library", "#api"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-16", "created_at": "2023-06-09", "description": "This notebook template demonstrates how to use the requests library to send a POST request with data. It includes importing the library, preparing the data, making the request, handling the response, and verifying the successful submission.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Request/Request_Sending_POST_Requests_with_Data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Request/Request_Sending_POST_Requests_with_Data.ipynb", "imports": ["requests"], "image_url": ""}, {"objectID": "1ec91cf3ea4e7bc9c5e5fe8f000bfcab76e74a221d3820500f41cb5744282f1d", "tool": "SAP-HANA", "notebook": "Query data", "action": "", "tags": ["#sap-hana", "#sap", "#saphana", "#database", "#snippet", "#operations", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides an introduction to querying data in SAP HANA.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SAP-HANA/SAP-HANA_Query_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SAP-HANA/SAP-HANA_Query_data.ipynb", "imports": ["sap_hana_connector"], "image_url": ""}, {"objectID": "bc8693ec5df8d3d2c7d05271ed8f68e0aeefdcb1ae5c3fcefcf4246df9614dcd", "tool": "SEON", "notebook": "Get email info", "action": "", "tags": ["#seon", "#email", "#enrichment", "#api", "#tool", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-23", "description": "This notebook will demonstrate how to use SEON's standalone email enrichment tool to learn about the approximate minimum age of an email address, its provider, and any connected online profiles and save it into a json file.\n\n*Good to know:*\n- You can use the Fraud API if you want to use the Email API together with any of our Phone API, IP API, and Device Fingerprinting.\n- All SEON API requests are case-sensitive. Please follow the formatting below to avoid errors.\n- Email API requests are limited to 120/minute during your SEON free trial.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SEON/SEON_Get_email_info.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SEON/SEON_Get_email_info.ipynb", "imports": ["requests", "naas", "pprint.pprint", "json"], "image_url": ""}, {"objectID": "dfc7aa18b61ba877af2ccc28a176b6ec5c7ae90df276085a78e8a01d116ec615", "tool": "SQLite", "notebook": "Create Database file", "action": "", "tags": ["#SQLite", "#database", "#databasemanagement", "#filebaseddb", "#dbcreation", "#dbsetup", "#SQLiteDB", "#localstorage", "#datastore", "#SQLitedatabase", "#embeddedDB", "#PythonDB", "#sqllite3", "#DBfile"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook creates a new SQLite database file using the sqlite3 module in Python. Here's an example of how you can create a new SQLite database file called \"mydatabase.db\"", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SQLite/SQLite_Create_Database_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SQLite/SQLite_Create_Database_file.ipynb", "imports": ["sqlite3"], "image_url": ""}, {"objectID": "1bc66c95ce6020ea5e543316f2bf03a0cf0e7d41f12680f81371452e3454320d", "tool": "SQLite", "notebook": "Create Table in Database", "action": "", "tags": ["#SQLite", "#database", "#databasemanagement", "#filebaseddb", "#dbcreation", "#dbsetup", "#SQLiteDB", "#localstorage", "#datastore", "#SQLitedatabase", "#embeddedDB", "#PythonDB", "#sqllite3", "#DBfile"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook creates a table called \"employees\" in a SQLite database. Please note that the new table created will erase the old one if a table already exist in the database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SQLite/SQLite_Create_Table_in_Database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SQLite/SQLite_Create_Table_in_Database.ipynb", "imports": ["sqlite3"], "image_url": ""}, {"objectID": "d9989623aa996ed0e28f3ea73630f21a11e50cc3087b3de6271505d6c59bb986", "tool": "SQLite", "notebook": "Insert data in Table", "action": "", "tags": ["#SQLite", "#database", "#databasemanagement", "#filebaseddb", "#dbcreation", "#dbsetup", "#SQLiteDB", "#localstorage", "#datastore", "#SQLitedatabase", "#embeddedDB", "#PythonDB", "#sqllite3", "#DBfile"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook insert the values into a table in a SQLite database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SQLite/SQLite_Insert_data_in_Table.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SQLite/SQLite_Insert_data_in_Table.ipynb", "imports": ["sqlite3"], "image_url": ""}, {"objectID": "7190661ad83396721f507d763dc721bf6a56ccba205c65a622153be05d637503", "tool": "SQLite", "notebook": "List Tables in Database", "action": "", "tags": ["#SQLite", "#database", "#databasemanagement", "#filebaseddb", "#dbcreation", "#dbsetup", "#SQLiteDB", "#localstorage", "#datastore", "#SQLitedatabase", "#embeddedDB", "#PythonDB", "#sqllite3", "#DBfile"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook lists tables within a SQLite database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SQLite/SQLite_List_Tables_in_Database.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SQLite/SQLite_List_Tables_in_Database.ipynb", "imports": ["sqlite3"], "image_url": ""}, {"objectID": "00e01d8540447a9f7dbc8a19ee47f55e785be0d85e821c4ce6f8912fba9b6d33", "tool": "SQLite", "notebook": "Read data in Table", "action": "", "tags": ["#SQLite", "#database", "#databasemanagement", "#filebaseddb", "#dbcreation", "#dbsetup", "#SQLiteDB", "#localstorage", "#datastore", "#SQLitedatabase", "#embeddedDB", "#PythonDB", "#sqllite3", "#DBfile"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-01-12", "description": "This notebook reads data from a table called \"employees\" in a SQLite database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SQLite/SQLite_Read_data_in_Table.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SQLite/SQLite_Read_data_in_Table.ipynb", "imports": ["sqlite3"], "image_url": ""}, {"objectID": "b2640eef0eb25e93c3717902c701273fe4f8689ec7805ec9865aa5dede072f65", "tool": "SWIFT", "notebook": "Create MT940 XML file", "action": "", "tags": ["#swift", "#mt940", "#xml", "#file", "#create", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-17", "description": "This notebook will show how to create an MT940 XML file using Python.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SWIFT/SWIFT_Create_MT940_XML_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SWIFT/SWIFT_Create_MT940_XML_file.ipynb", "imports": ["xml.etree.ElementTree"], "image_url": ""}, {"objectID": "d7e34a46dfdab62d55033522183e338b4bfd89523400494c9c14a7880471b1cb", "tool": "SendGrid", "notebook": "Get all messages", "action": "", "tags": ["#sendgrid", "#activity", "#snippet", "#operations", "#dataframe"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-04-04", "description": "This notebook provides a comprehensive overview of all messages sent through SendGrid.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SendGrid/SendGrid_Get_all_messages.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SendGrid/SendGrid_Get_all_messages.ipynb", "imports": ["naas", "requests", "urllib", "pandas"], "image_url": ""}, {"objectID": "49126dfdadde535c9004cb89b3c0e4c1fea355ea72a5e9f019fc99086ba4befc", "tool": "SendGrid", "notebook": "Send message", "action": "", "tags": ["#sendgrid", "#message", "#snippet", "#operations"], "author": "Sanjeet Attili", "author_url": "https://linkedin.com/in/sanjeet-attili-760bab190/", "updated_at": "2023-04-12", "created_at": "2022-03-08", "description": "This notebook allows you to send messages using SendGrid's email delivery service.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SendGrid/SendGrid_Send_message.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SendGrid/SendGrid_Send_message.ipynb", "imports": ["requests", "sendgrid.SendGridAPIClient", "sendgrid.helpers.mail.*"], "image_url": ""}, {"objectID": "3644b28c400b814d09ab9a29811b9ce0d5c88db8b6ea7288146b12530d88e1ad", "tool": "Sendinblue", "notebook": "Get no of emails opened", "action": "", "tags": ["#sendinblue", "#emails", "#campaign", "#opened", "#emailcampaigns", "#marketing", "#operations", "#snippet"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-07-09", "description": "This notebook provides a way to track the number of emails opened using Sendinblue.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Sendinblue/Sendinblue_Get_no_of_emails_opened.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Sendinblue/Sendinblue_Get_no_of_emails_opened.ipynb", "imports": ["requests", "json", "naas"], "image_url": ""}, {"objectID": "7dcc2250cb71fd6d7df3b877dc5168e6ee68e03beb17aeed32fb057a113f9740", "tool": "Sendinblue", "notebook": "Get no of emails sent", "action": "", "tags": ["#sendinblue", "#emails", "#campaign", "#sent", "#emailcampaigns", "#marketing", "#operations", "#snippet"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-07-09", "description": "This notebook provides a way to track the number of emails sent through Sendinblue.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Sendinblue/Sendinblue_Get_no_of_emails_sent.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Sendinblue/Sendinblue_Get_no_of_emails_sent.ipynb", "imports": ["requests", "json", "naas"], "image_url": ""}, {"objectID": "d44b552d043fa74c9a00ca9ed43835a9acd1016434330820159f1818411b73e4", "tool": "Sendinblue", "notebook": "Get no of spam reports", "action": "", "tags": ["#sendinblue", "#emails", "#campaign", "#spam", "#emailcampaigns", "#marketing", "#operations", "#snippet"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-07-09", "description": "This notebook provides a way to track the number of spam reports received through Sendinblue.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Sendinblue/Sendinblue_Get_no_of_spam_reports.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Sendinblue/Sendinblue_Get_no_of_spam_reports.ipynb", "imports": ["requests", "json", "naas"], "image_url": ""}, {"objectID": "dd7e259333a94870bff986f6e4f3d3e1875f6fd02fbe6c6fccacd81d7fbc1336", "tool": "Sendinblue", "notebook": "Get no of undelivered emails", "action": "", "tags": ["#emails", "#campaign", "#undelivered", "#emailcampaigns", "#marketing", "#sendinblue", "#operations", "#snippet"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-06-30", "description": "This notebook provides a count of emails that were not successfully delivered using Sendinblue.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Sendinblue/Sendinblue_Get_no_of_undelivered_emails.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Sendinblue/Sendinblue_Get_no_of_undelivered_emails.ipynb", "imports": ["requests", "json", "naas"], "image_url": ""}, {"objectID": "e14418219d04e28461426bee2d1dd57778c3265b9e36b8696268ad8ed0b5f0bc", "tool": "SharePoint", "notebook": "Get file", "action": "", "tags": ["#sharepoint", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-07-13", "description": "This notebook provides a guide to retrieving files from a SharePoint server.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SharePoint/SharePoint_Get_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SharePoint/SharePoint_Get_file.ipynb", "imports": ["naas_drivers.sharepoint", "naas"], "image_url": ""}, {"objectID": "ea00d49b6e6488a3327b37ffc55ae0498cbd875f1a50654e4298105e11fd0af2", "tool": "SharePoint", "notebook": "List folder", "action": "", "tags": ["#sharepoint", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-07-13", "description": "This notebook provides a guide to managing and organizing files in a SharePoint List folder.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SharePoint/SharePoint_List_folder.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SharePoint/SharePoint_List_folder.ipynb", "imports": ["naas_drivers.sharepoint", "naas"], "image_url": ""}, {"objectID": "00f1ebf2b83dcf76e8e3264850f5e04de346e4722e102bc8a95aa553a44255fc", "tool": "SharePoint", "notebook": "Upload file", "action": "", "tags": ["#sharepoint", "#productivity", "#naas_drivers", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-07-13", "description": "This notebook provides instructions on how to upload a file to a SharePoint site.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/SharePoint/SharePoint_Upload_file.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/SharePoint/SharePoint_Upload_file.ipynb", "imports": ["naas_drivers.sharepoint", "naas"], "image_url": ""}, {"objectID": "310727059ea08d1992077ac57cb0ca54196257738cb92d852bbb2bc3af7a7251", "tool": "Shutterstock", "notebook": "Search for images", "action": "", "tags": ["#shutterstock", "#images", "#search", "#api", "#reference", "#library"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-20", "created_at": "2023-02-27", "description": "This notebook will demonstrate how to use the Shutterstock API to search for images.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Shutterstock/Shutterstock_Search_for_images.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Shutterstock/Shutterstock_Search_for_images.ipynb", "imports": ["json", "naas", "requests", "PIL.Image", "io", "matplotlib.pyplot", "pydash"], "image_url": ""}, {"objectID": "69edbf0f3bece275b66ceff5c8dc5510c1db14429f958e7dc109afbf15f02bc2", "tool": "Slack", "notebook": "Add new user to Google Sheets", "action": "", "tags": ["#slack", "#googlesheets", "#operations", "#automation"], "author": "Sanjeet Attili", "author_url": "https://docs.naas.ai/templates/google-sheets", "updated_at": "2023-04-12", "created_at": "2022-04-25", "description": "## Input", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Slack/Slack_Add_new_user_to_Google_Sheets.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Slack/Slack_Add_new_user_to_Google_Sheets.ipynb", "imports": ["naas_drivers.gsheet", "naas", "pandas", "slack_sdk.WebClient", "datetime.datetime"], "image_url": ""}, {"objectID": "5f730f307f840b3988958c46d7d837ac5877d7294ba2e4e8c77db87521611989", "tool": "Slack", "notebook": "Follow number of users in workspace", "action": "", "tags": ["#slack", "#plotly", "#html", "#image", "#csv", "#marketing", "#automation", "#analytics"], "author": "Sanjeet Attili", "author_url": "https://github.com/slackapi/python-slack-sdk", "updated_at": "2023-04-12", "created_at": "2022-04-25", "description": "## Input", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Slack/Slack_Follow_number_of_users_in_workspace.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Slack/Slack_Follow_number_of_users_in_workspace.ipynb", "imports": ["naas", "pandas", "plotly.graph_objects", "slack_sdk.WebClient", "datetime.datetime"], "image_url": ""}, {"objectID": "8c14aab53bd8c6fe6689201ba16d90346db4f37cb888763e61eb7a3c65c38eda", "tool": "Slack", "notebook": "Send blocks to channel", "action": "", "tags": ["#slack", "#message", "#send", "#operations", "#snippet", "#block"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-06-22", "created_at": "2023-06-19", "description": "This notebook allows you to quickly and easily send blocks through Slack. Blocks are visual components that can be stacked and arranged to create app layouts. Block Kit can make your app's communication clearer while also giving you consistent opportunity to interact with and assist users.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Slack/Slack_Send_blocks_to_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Slack/Slack_Send_blocks_to_channel.ipynb", "imports": ["naas_drivers.slack", "naas"], "image_url": ""}, {"objectID": "0531f44f6ac83d8e06902f52b1460d35fb57a29f6afb4091f1a276d3244a91af", "tool": "Slack", "notebook": "Send message", "action": "", "tags": ["#slack", "#message", "#send", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-22", "created_at": "2023-06-22", "description": "This notebook allows you to quickly and easily send text messages through Slack.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Slack/Slack_Send_message_to_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Slack/Slack_Send_message_to_channel.ipynb", "imports": ["naas_drivers.slack", "naas"], "image_url": ""}, {"objectID": "15defdfba3040a35be89b5bf41b6e7de4dd4317de5bff7d85d5541e1ae4487a4", "tool": "Snowflake", "notebook": "Basics and data querying", "action": "", "tags": ["#snowflake", "#data", "#warehouse", "#naas_drivers", "#snippet"], "author": "Mateusz Polakowski", "author_url": "https://www.linkedin.com/in/polakowski/", "updated_at": "2023-04-12", "created_at": "2022-08-06", "description": "This notebook provides an introduction to the basics of Snowflake and how to query data within it.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Snowflake/Snowflake_Basics_and_data_querying.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Snowflake/Snowflake_Basics_and_data_querying.ipynb", "imports": ["os", "naas_drivers.snowflake", "snowflake.connector.errors.ProgrammingError"], "image_url": ""}, {"objectID": "e34aa1f49930e96ed9f8f3a829011f511890ffdde810c43f4f06637a66d85b9a", "tool": "Snowflake", "notebook": "Ingest csv data from local stage", "action": "", "tags": ["#snowflake", "#data", "#warehouse", "#naas_drivers", "#snippet"], "author": "Mateusz Polakowski", "author_url": "https://www.linkedin.com/in/polakowski/", "updated_at": "2023-04-12", "created_at": "2022-08-06", "description": "This notebook demonstrates how to ingest CSV data from a local stage into Snowflake.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Snowflake/Snowflake_Ingest_csv_data_from_local_stage.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Snowflake/Snowflake_Ingest_csv_data_from_local_stage.ipynb", "imports": ["os", "naas_drivers.snowflake", "snowflake.connector.errors.ProgrammingError"], "image_url": ""}, {"objectID": "e272e6e7fcca9fb2482ff3f91eab93a951c03c36e6bf7ba1fd83d6928b88c88c", "tool": "Snowflake", "notebook": "Ingest data from AWS external stages", "action": "", "tags": ["#snowflake", "#data", "#warehouse", "#naas_drivers", "#snippet"], "author": "Mateusz Polakowski", "author_url": "https://www.linkedin.com/in/polakowski/", "updated_at": "2023-04-12", "created_at": "2022-08-06", "description": "This notebook demonstrates how to ingest data from AWS external stages into Snowflake.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Snowflake/Snowflake_Ingest_data_from_AWS_external_stages.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Snowflake/Snowflake_Ingest_data_from_AWS_external_stages.ipynb", "imports": ["os", "naas_drivers.snowflake", "snowflake.connector.errors.ProgrammingError", "pandas"], "image_url": ""}, {"objectID": "0dfb1e2bec528e076f9a7e599747f0b8ff34b464253c902a17b7f737791862f9", "tool": "Snowflake", "notebook": "Ingest json data from local stage", "action": "", "tags": ["#snowflake", "#data", "#warehouse", "#naas_drivers", "#snippet"], "author": "Mateusz Polakowski", "author_url": "https://www.linkedin.com/in/polakowski/", "updated_at": "2023-04-12", "created_at": "2022-08-06", "description": "This notebook demonstrates how to ingest JSON data from a local stage into Snowflake.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Snowflake/Snowflake_Ingest_json_data_from_local_stage.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Snowflake/Snowflake_Ingest_json_data_from_local_stage.ipynb", "imports": ["os", "naas_drivers.snowflake", "snowflake.connector.errors.ProgrammingError"], "image_url": ""}, {"objectID": "996435d28247d8e9c175da10ebc3f3a3c3a7709f6ab658a453069f27629f80aa", "tool": "Societe.com", "notebook": "Get company details", "action": "", "tags": ["#societe.com", "#companies", "#opendata", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides detailed information about companies registered on Societe.com.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Societe.com/Societe.com_Get_company_details.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Societe.com/Societe.com_Get_company_details.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "44d6284d9798272ec8d8b57d4a4cc811e758e0612d0d87c9fca6bf49c2b79c75", "tool": "Societe.com", "notebook": "Get verif.com", "action": "", "tags": ["#companies", "#opendata", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides access to Societe.com's verification services through Verif.com.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Societe.com/Societe.com_Get_verif.com.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Societe.com/Societe.com_Get_verif.com.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "460cb50b6264b395c250e70db47ad5aa39b2bfcc2b406dc25e5adbce004a87dc", "tool": "Spotify", "notebook": "Create Radar Chart to analyze Playlist", "action": "", "tags": ["#spotify", "#python", "#spotipy", "#analytics", "#operations", "#image"], "author": "Akshaya Parthasarathy", "author_url": "https://github.com/iaks23", "updated_at": "2023-04-12", "created_at": "2021-10-12", "description": "This notebook provides a step-by-step guide to creating a Radar Chart to analyze a Spotify Playlist.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Spotify/Spotify_Create_Radar_Chart_to_analyze_Playlist.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Spotify/Spotify_Create_Radar_Chart_to_analyze_Playlist.ipynb", "imports": ["json", "spotipy", "pandas", "spotipy.oauth2.SpotifyClientCredentials", "sklearn.preprocessing.MinMaxScaler", "matplotlib.pyplot", "math.pi"], "image_url": ""}, {"objectID": "dca116db84f70425c4800366b46cc450713e1b39960edc929e38deed8702789b", "tool": "Stabilty AI", "notebook": "Generate Image from text", "action": "", "tags": ["#stabilityai", "#png", "#prompt", "#generate", "#file", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-27", "description": "This notebook will demonstrate how to execute a basic image generation call via Stability AI API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stabilty%20AI/Stabilty_AI_Generate_Image_from_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stabilty%20AI/Stabilty_AI_Generate_Image_from_text.ipynb", "imports": ["os", "io", "warnings", "PIL.Image", "stability_sdk.client", "stability_sdk.client", "stability_sdk.interfaces.gooseai.generation.generation_pb2", "naas"], "image_url": ""}, {"objectID": "832c6caba950d6fab4bf84f56f9ec0661ca43ffc478e0f39bf5ba999022a6e17", "tool": "Stable Diffusion", "notebook": "Generate image from text", "action": "", "tags": ["#stable-diffusion", "#image-generation", "#text-to-image", "#ai", "#machine-learning", "#deep-learning"], "author": "Oussama El Bahaoui", "author_url": "https://www.linkedin.com/in/oelbahaoui/", "updated_at": "2023-06-19", "created_at": "2023-05-12", "description": "This notebook generate image from text using Stable Diffusion.\n\nIt requires a more powerful machine than the free tier we provide. You have two options to proceed:\n\n1. **Using Google Colab:** If you have a Google account, you can open this notebook in Google Colab(link is above), which provides free access to more powerful computational resources to run this notebook. To do this, click the \u201cOpen in Colab\u201d button located at the end of this paragraph. Please note that you may need to sign in with your Google account or create one if you don\u2019t have it. \"Open\n\n2. **Contacting Us for Machine Upgrade:** If you prefer to run this notebook on your own machine, you can contact us to upgrade your machine. Our team will assist you in setting up the necessary environment. Please reach out to [Jeremy Ravenel](mailto:jeremy@naas.ai) for further assistance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stable%20Diffusion/Stable_Diffusion_Generate_image_from_text.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stable%20Diffusion/Stable_Diffusion_Generate_image_from_text.ipynb", "imports": ["diffusers.DiffusionPipeline, DPMSolverMultistepScheduler", "PIL.Image", "matplotlib.pyplot", "torch"], "image_url": ""}, {"objectID": "966d01eed050cc4cb01fe7a63b108c7981a5c194867ac50e215e489fe9ef04c0", "tool": "Streamlit", "notebook": "Create prediction app", "action": "", "tags": ["#streamlit", "#app", "#ml", "#ai", "#operations", "#plotly"], "author": "Gagan Bhatia", "author_url": "https://github.com/gagan3012", "updated_at": "2023-04-12", "created_at": "2021-09-01", "description": "This notebook provides a step-by-step guide to creating a Streamlit app that can make predictions based on user input.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Streamlit/Streamlit_Create_prediction_app.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Streamlit/Streamlit_Create_prediction_app.ipynb", "imports": ["naas_drivers.streamlit", "naas_drivers.streamlit, plotly, yahoofinance, prediction", "streamlit"], "image_url": ""}, {"objectID": "ea7c3e26461ab96b7177bdb5a53a4091ee6e0c1d59010899a52e7fdb96b41797", "tool": "Stripe", "notebook": "Create a customer", "action": "", "tags": ["#stripe", "#payment", "#customer", "#api", "#python", "#create", "#crud"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-18", "created_at": "2023-04-30", "description": "This notebook will show how to create a customer using the Stripe API. It is usefull for organizations that need to manage customer payments.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Create_a_customer.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Create_a_customer.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "80d3f6a6c98fb33c54b4e6eb95c5741adf5c5a89f6ca6c85ec149c2d1789a907", "tool": "Stripe", "notebook": "Delete a customer", "action": "", "tags": ["#stripe", "#payment", "#customer", "#api", "#python", "#delete", "#crud"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-18", "created_at": "2023-05-18", "description": "This notebook will show how to delete a customer using the Stripe API. It is usefull for organizations that need to manage customer payments.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Delete_a_customer.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Delete_a_customer.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "2e1162c3667428d176ee2dc9ae136c309599c272948339c3783e0960761b749d", "tool": "Stripe", "notebook": "Get balances", "action": "", "tags": ["#stripe", "#balances", "#snippet", "#operations", "#dataframe"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides a way to view and manage Stripe account balances.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Get_balances.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Get_balances.ipynb", "imports": ["stripe", "stripe", "pandas"], "image_url": ""}, {"objectID": "e75c117c1f5c9fdbef31f27e2df13e2a6e0ff9690f98452eaa7f16e7b41ec6e7", "tool": "Stripe", "notebook": "Get charges", "action": "", "tags": ["#stripe", "#charges", "#snippet", "#operations", "#dataframe"], "author": "Martin Donadieu", "author_url": "https://www.linkedin.com/in/martindonadieu/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides an overview of Stripe charges and their associated data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Get_charges.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Get_charges.ipynb", "imports": ["stripe", "stripe", "pandas"], "image_url": ""}, {"objectID": "3bc32324991101e1a88858f766923d627fe005351a5a1424287302bf586dca76", "tool": "Stripe", "notebook": "List all customers", "action": "", "tags": ["#stripe", "#api", "#customers", "#list", "#python", "#reference"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel", "updated_at": "2023-05-18", "created_at": "2023-04-26", "description": "This notebook will list all customers from Stripe and explain how to use the Stripe API to do so. It is usefull for organizations that need to manage their customers.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_List_all_customers.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_List_all_customers.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "d28a5138a2cc901dc326745b136655e50ecd70b823da5cfeb35fa472d429af86", "tool": "Stripe", "notebook": "Retrieve a customer", "action": "", "tags": ["#stripe", "#payment", "#customer", "#api", "#python", "#retrieve", "#crud"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-18", "created_at": "2023-05-18", "description": "This notebook will show how to retrieve a customer using the Stripe API. It is usefull for organizations that need to manage customer payments.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Retrieve_a_customer.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Retrieve_a_customer.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "b812b9cab5dd404fcfa8a097f203dc0ddcfacd3728e8c14ed1205b11b0c2e92d", "tool": "Stripe", "notebook": "Update a customer", "action": "", "tags": ["#stripe", "#payment", "#customer", "#api", "#python", "#update", "#crud"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-05-18", "created_at": "2023-05-18", "description": "This notebook will show how to update a customer using the Stripe API. It is usefull for organizations that need to manage customer payments.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Stripe/Stripe_Update_a_customer.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Stripe/Stripe_Update_a_customer.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "07fa9fa6090c516e8d7233c9c4aceb4dafdcbbe96c685eda8ace2314d11df2df", "tool": "Supabase", "notebook": "Email Auth", "action": "", "tags": ["#supabase", "#auth", "#email", "#signin", "#signout", "#verification"], "author": "Sriniketh Jayasendil", "author_url": "http://linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-02-15", "description": "This notebook will utilize the Supabase DB and Authentication (with email verification) to Login users.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Supabase/Supabase_Email_Auth.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Supabase/Supabase_Email_Auth.ipynb", "imports": ["naas", "json", "supabase.create_client", "supabase.create_client"], "image_url": ""}, {"objectID": "9aacc71819205eb5f78d216ff9a089344dc6e6d906707f7c9281232f86dde6aa", "tool": "Telegram", "notebook": "Create crypto sentiment bot", "action": "", "tags": ["#telegram", "#sentiment", "#bot", "#naas_drivers", "#ai", "#investors"], "author": "Yaswanthkumar GOTHIREDDY", "author_url": "https://www.linkedin.com/in/yaswanthkumargothireddy/", "updated_at": "2023-04-12", "created_at": "2021-07-09", "description": "This notebook provides instructions on how to create a Telegram bot that tracks and analyzes sentiment around cryptocurrencies.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Telegram/Telegram_Create_crypto_sentiment_bot.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Telegram/Telegram_Create_crypto_sentiment_bot.ipynb", "imports": ["logging", "telegram.ext.*", "numpy", "naas_drivers.newsapi", "naas_drivers.sentiment", "datetime.datetime, timedelta"], "image_url": ""}, {"objectID": "87ed6f3653975a17927f01bcbe3f0385fb02c53b0860ded81236b9083dc9f890", "tool": "Text", "notebook": "Reformat Without Spaces", "action": "", "tags": ["#text", "#reformat", "#snippet", "#operations", "#spaces"], "author": "Minura Punchihewa", "author_url": "https://www.linkedin.com/in/minurapunchihewa/", "updated_at": "2023-04-12", "created_at": "2022-10-10", "description": "This notebook reformats text by removing all spaces.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Text/Text_Reformat_Text_Without_Spaces.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Text/Text_Reformat_Text_Without_Spaces.ipynb", "imports": ["wordninja", "wordninja", "twotransactionswhichcameearlier,andfordecadesthisstymiedthedevelopmentofdecentralized digitalcurrency.Satoshi'sblockchainwasthefirstcredibledecentralizedsolution.Andnow,attentionis rapidlystartingtoshifttowardthissecondpartofBitcoin'stechnology,andhowtheblockchainconceptcanbe used for more than just money. Commonlycitedapplicationsincludeusingon-blockchaindigitalassetstorepresentcustomcurrenciesand financialinstruments(\"coloredcoins\"),theownershipofanunderlyingphysicaldevice(\"smartproperty\"), non-fungibleassetssuchasdomainnames(\"Namecoin\")aswellasmoreadvancedapplicationssuchas decentralizedexchange,financialderivatives,peer-to-peergamblingandon-blockchainidentityand reputationsystems.Another.antareaofinquiryis\"smartcontracts\"-systemswhichautomatically movedigitalassetsaccordingtoarbitrarypre-specifiedrules.Forexample,onemighthaveatreasurycontract oftheform\"AcanwithdrawuptoXcurrencyunitsperday,BcanwithdrawuptoYperday,AandBtogether canwithdrawanything,andAcanshutoffB'sabilitytowithdraw\".Thelogicalextensionofthisis decentralizedautonomousorganizations(DAOs)-long-termsmartcontractsthatcontaintheassetsand encodethebylawsofanentireorganization.WhatEthereumintendstoprovideisablockchainwithabuilt-in fullyfledgedTuring-completeprogramminglanguagethatcanbeusedtocreate\"contracts\"thatcanbeused toencodearbitrarystatetransitionfunctions,allowinguserstocreateanyofthesystemsdescribedabove,as well"], "image_url": ""}, {"objectID": "c547876f0d475350ad796940faaba28ebd0b65165eddb1123ebfb19116a70d35", "tool": "Thinkific", "notebook": "Get users", "action": "", "tags": ["#thinkific", "#education", "#naas_drivers", "#operations", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides a guide to acquiring and engaging users for the Thinkific platform.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Thinkific/Thinkific_Get_users.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Thinkific/Thinkific_Get_users.ipynb", "imports": ["naas_drivers.thinkific"], "image_url": ""}, {"objectID": "5b7aab31600212c5c3c1ebe3bde329691ef5e075e26bfad83e30b96a27406539", "tool": "Thinkific", "notebook": "Send users", "action": "", "tags": ["#thinkific", "#education", "#naas_drivers", "#operations", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook allows you to send users automated emails from Thinkific.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Thinkific/Thinkific_Send_users.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Thinkific/Thinkific_Send_users.ipynb", "imports": ["naas_drivers.thinkific"], "image_url": ""}, {"objectID": "6e6ff26e13b5d362629eda7e97f100403c4263682ce83cd402f3e0fc0352fb3b", "tool": "TikTok", "notebook": "Get user stats", "action": "", "tags": ["#tiktok", "#user", "#stats", "#snippet", "#content"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-04-12", "description": "This notebook provides an analysis of user statistics on the popular social media platform, TikTok.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/TikTok/TikTok_Get_user_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/TikTok/TikTok_Get_user_stats.ipynb", "imports": ["TikTokAPI.TikTokAPI", "TikTokAPI.TikTokAPI", "nest_asyncio", "pandas"], "image_url": ""}, {"objectID": "35f614b16e2f264d1d38670c7ca5c0fe010e4c1cd828f2812e8a58faaeaee557", "tool": "TikTok", "notebook": "Get videos stats", "action": "", "tags": ["#tiktok", "#videos", "#stats", "#snippet", "#content"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-04-12", "description": "This notebook provides an analysis of video statistics on the popular social media platform, TikTok.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/TikTok/TikTok_Get_videos_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/TikTok/TikTok_Get_videos_stats.ipynb", "imports": ["TikTokAPI.TikTokAPI", "TikTokAPI.TikTokAPI", "nest_asyncio", "pandas"], "image_url": ""}, {"objectID": "bda97c0086e67e89ca713c307c134464ce0269066c8eb0398f343df74d61d809", "tool": "Trello", "notebook": "Create Card", "action": "", "tags": ["#trello", "#api", "#card", "#create", "#board", "#list"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-14", "created_at": "2023-07-14", "description": "This notebook would show you how to create a new card on a Trello board using the API. You could specify the board and list that you want the card to be created in, as well as its name, description, and any other relevant details, you can also create several cards.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Trello/Trello_Create_Card.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Trello/Trello_Create_Card.ipynb", "imports": ["requests", "naas", "ant\"},"], "image_url": ""}, {"objectID": "171b2e70749cf7235cefd7b019c057afa2196c1cdfdb0127320915d7609c3fc6", "tool": "Trello", "notebook": "Get Cards on a Board", "action": "", "tags": ["#trello", "#api", "#rest", "#cards", "#board", "#get"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-14", "created_at": "2023-07-14", "description": "This notebook get all cards from a board.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Trello/Trello_Get_Cards_on_a_Board.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Trello/Trello_Get_Cards_on_a_Board.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "e0c37b0b9b71eef4ba954737ebcf7889a1961540390e8d61dc9665188cdb9cc1", "tool": "Trello", "notebook": "Get Lists on a Board", "action": "", "tags": ["#trello", "#project", "#retrieve", "#snippet", "#operations", "#lists", "#board"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-14", "created_at": "2023-07-14", "description": "This notebook shows how to get the Lists on a Board.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Trello/Trello_Get_Lists_on_a_Board.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Trello/Trello_Get_Lists_on_a_Board.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "236ba6113e6987e489a54a8297398d0e66d2b9ee47911ef73dc0ad23a15df7c1", "tool": "Trello", "notebook": "Get board data", "action": "", "tags": ["#trello", "#project", "#board", "#snippet", "#operations", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides a way to access and analyze data from Trello boards.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Trello/Trello_Get_board_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Trello/Trello_Get_board_data.ipynb", "imports": ["trello_connector"], "image_url": ""}, {"objectID": "8bf5205524ae16d62ec58b8c3d98d25bf423d3cb87975758f7e440f537e38440", "tool": "Trello", "notebook": "List Boards", "action": "", "tags": ["#trello", "#api", "#boards", "#list", "#python", "#rest"], "author": "Benjamin Filly", "author_url": "https://www.linkedin.com/in/benjamin-filly-05427727a/", "updated_at": "2023-07-11", "created_at": "2023-07-11", "description": "This notebook would allow you to retrieve a list of all the boards that you have access to in Trello. You could then use this information to perform further actions on the boards, such as listing the cards or updating their details.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Trello/Trello_List_Boards.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Trello/Trello_List_Boards.ipynb", "imports": ["requests", "naas"], "image_url": ""}, {"objectID": "2eddf7c217470a6be61c299b0cd813d63d1c4f4786016a3b897ffcf20e36f628", "tool": "Twilio", "notebook": "Add SMS to Google Sheets spreadsheet", "action": "", "tags": ["#twilio", "#google", "#sheets", "#googlesheets", "#send"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-03-14", "description": "This notebook allows you to log all the messages sent through your Twilio Account into a Google Sheets document. Each new message will be added as a new row, along with the date, time, message ID, and message content. It's a convenient way to keep track of your Twilio activity and make sure you never miss an important message.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twilio/Twilio_Add_SMS_to_Google_Sheets_spreadsheet.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twilio/Twilio_Add_SMS_to_Google_Sheets_spreadsheet.ipynb", "imports": ["datetime.datetime", "naas", "gspread", "gspread", "oauth2client.service_account.ServiceAccountCredentials", "oauth2client.service_account.ServiceAccountCredentials", "twilio.rest.Client", "twilio.rest.Client"], "image_url": ""}, {"objectID": "84f71a020625f18300825bd684ac0985e2fc5b45f88839cfd9c176d5271a0f8a", "tool": "Twilio", "notebook": "Make Call", "action": "", "tags": ["#twilio", "#project", "#call", "#mobile"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2022-10-05", "description": "This notebook allows us to make a phone call to a verified twilio number. It also has different parameters to customize the output of the voice call.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twilio/Twilio_Make_Call.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twilio/Twilio_Make_Call.ipynb", "imports": ["time", "naas", "twilio.rest.Client", "twilio.rest.Client"], "image_url": ""}, {"objectID": "cf796abab887f0c032b38c2ac5c95b86f4245e69d66aea9a8d7b7e5cc5dac186", "tool": "Twilio", "notebook": "Send SMS", "action": "", "tags": ["#twilio", "#project", "#send", "#sms", "#snippet", "#operations", "#dataframe"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows you to send SMS messages using the Twilio API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twilio/Twilio_Send_SMS.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twilio/Twilio_Send_SMS.ipynb", "imports": ["twilio.rest.Client", "twilio.rest.Client"], "image_url": ""}, {"objectID": "9a33bfd7731b24971b0629ffb86419d5e7e45605566c208ce2e82a5e93b81b10", "tool": "Twilio", "notebook": "Send SMS messages for Google Calendar Events", "action": "", "tags": ["#googlecalendar", "#twilio", "#notification", "#event"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil", "updated_at": "2023-06-20", "created_at": "2023-03-17", "description": "This notebook sends an SMS notification for upcoming the next event you're attending in your Google Calendar.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twilio/Twilio_Send_SMS_Google_Calendar_Events.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twilio/Twilio_Send_SMS_Google_Calendar_Events.ipynb", "imports": ["naas", "datetime.datetime", "pytz", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "apiclient.discovery.build", "google_auth_oauthlib.flow.InstalledAppFlow", "twilio.rest.Client", "twilio.rest.Client", "pickle"], "image_url": ""}, {"objectID": "b83bc56ec2d52348e7769a349a95cffeda2100c29daae44ab84d3b54744bedfa", "tool": "Twitter", "notebook": "Add member to list", "action": "", "tags": ["#twitter", "#tweepy", "#pandas", "#twitterautomation", "#twitterlistmembers", "#snippet"], "author": "Kaushal Krishna", "author_url": "https://www.linkedin.com/in/kaushal-krishna-a48959153", "updated_at": "2023-04-12", "created_at": "2023-01-13", "description": "This notebook adds a member to the list of a particular user.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Add_member_to_list.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Add_member_to_list.ipynb", "imports": ["tweepy", "pandas", "naas"], "image_url": ""}, {"objectID": "ac4829f37f52f9554372ffdc6920da0099d83854bdd4d6e8e18efcc86af6fa37", "tool": "Twitter", "notebook": "Get followers list", "action": "", "tags": ["#twitter", "#api", "#followers", "#list", "#get", "#developer"], "author": "Sriniketh Jayasendil", "author_url": "https://www.linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-05-23", "created_at": "2023-05-17", "description": "This notebook will demonstrate how to get a list of followers from Twitter using the API. This feature is only available on paid plan.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_followers_list.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_followers_list.ipynb", "imports": ["naas", "tweepy", "tweepy.Stream", "json", "pandas"], "image_url": ""}, {"objectID": "871bb71e3870638a5e7cbe6c68554487b055d3eadc0653cc0d229d556e7d6438", "tool": "Twitter", "notebook": "Get members of list", "action": "", "tags": ["#twitter", "#tweepy", "#pandas", "#twitterautomation", "#twitterlistmembers", "#snippet"], "author": "Kaushal Krishna", "author_url": "https://www.linkedin.com/in/kaushal-krishna-a48959153", "updated_at": "2023-04-12", "created_at": "2023-01-11", "description": "This notebook gets the members of a list of a particular user. Private list members will only be shown if the authenticated user owns the specified list. It can be used to enable people to curate and organize new Lists based on the membership information", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_members_of%20list.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_members_of%20list.ipynb", "imports": ["tweepy", "pandas", "naas"], "image_url": ""}, {"objectID": "2cfc5fc37a64737391240ba4c7ccac0fbee076d183decdeeec6480f97ec8ec20", "tool": "Twitter", "notebook": "Get posts stats", "action": "", "tags": ["#twitter", "#post", "#comments", "#naas_drivers", "#snippet", "#content"], "author": "Alok Chilka", "author_url": "https://www.linkedin.com/in/calok64/", "updated_at": "2023-04-12", "created_at": "2022-04-12", "description": "This notebook provides an analysis of Twitter posts, including statistics on user engagement and post performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_posts_stats.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_posts_stats.ipynb", "imports": ["naas_drivers.linkedin, hubspot", "pandas", "numpy", "naas", "datetime.datetime, timedelta", "requests", "json", "tweepy"], "image_url": ""}, {"objectID": "d50dc5991bf4fe05f69298b0b37857587e63f47d21cab0b07fbf0c4f6d4bf0b7", "tool": "Twitter", "notebook": "Get tweets from search", "action": "", "tags": ["#twitter", "#ifttt", "#naas_drivers", "#snippet", "#content", "#dataframe"], "author": "Dineshkumar Sundaram", "author_url": "https://github.com/dineshh912", "updated_at": "2023-04-12", "created_at": "2021-09-29", "description": "This notebook allows users to search and retrieve tweets from Twitter.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_tweets_from_search.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_tweets_from_search.ipynb", "imports": ["tweepy", "pandas"], "image_url": ""}, {"objectID": "4414785952831aae6f4b0f2ac5664a5fe233cf83950b1b06ed30e869c59efbfb", "tool": "Twitter", "notebook": "Get tweets stats from profile", "action": "", "tags": ["#twitter", "#tweets", "#scrap", "#snippet", "#content", "#dataframe"], "author": "Tannia Dubon", "author_url": "https://www.linkedin.com/in/tanniadubon/", "updated_at": "2023-04-12", "created_at": "2021-12-27", "description": "This notebook allows users to retrieve and analyze statistics from a Twitter profile.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_tweets_stats_from_profile.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_tweets_stats_from_profile.ipynb", "imports": ["os", "re", "pandas"], "image_url": ""}, {"objectID": "ebea8c3910c8f62394c5ff6901940b5e54a520d9531e84a90d22b61c23a8be00", "tool": "Twitter", "notebook": "Get user data", "action": "", "tags": ["#twitter", "#ifttt", "#naas_drivers", "#snippet", "#content", "#dataframe"], "author": "Dineshkumar Sundaram", "author_url": "https://github.com/dineshh912", "updated_at": "2023-04-12", "created_at": "2021-09-29", "description": "This notebook provides a way to access and analyze data from Twitter users.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Get_user_data.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Get_user_data.ipynb", "imports": ["tweepy", "pandas"], "image_url": ""}, {"objectID": "dfd78b97b964be28292a8cf054deb633939e1af86deb1831414ef29b59722f8f", "tool": "Twitter", "notebook": "Post text and image", "action": "", "tags": ["#twitter", "#ifttt", "#naas_drivers", "#snippet", "#content"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook allows users to post text and images to their Twitter account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Post_text_and_image.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Post_text_and_image.ipynb", "imports": ["naas", "naas_drivers"], "image_url": ""}, {"objectID": "d3bc43603e97ccc16cae1bc8045699ce7340ce42c481cd1502c91450da209673", "tool": "Twitter", "notebook": "Remove member from list", "action": "", "tags": ["#twitter", "#tweepy", "#pandas", "#twitterautomation", "#twitterlistmembers", "#snippet"], "author": "Kaushal Krishna", "author_url": "https://www.linkedin.com/in/kaushal-krishna-a48959153", "updated_at": "2023-04-12", "created_at": "2023-01-20", "description": "This notebook removes a single member from member list.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Remove_member_from_list.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Remove_member_from_list.ipynb", "imports": ["tweepy", "pandas", "naas"], "image_url": ""}, {"objectID": "f613ea52f869a50913e79cc1bf1af68d3f31d6ca2f3cd5af1c1d77cdaa48ba50", "tool": "Twitter", "notebook": "Schedule posts", "action": "", "tags": ["#twitter", "#automation", "#ifttt", "#naas_drivers", "#gsheet", "#content"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook allows you to plan and schedule posts to your Twitter account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Schedule_posts.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Schedule_posts.ipynb", "imports": ["datetime.datetime", "naas_drivers", "naas"], "image_url": ""}, {"objectID": "49bb50d18a5fbfeb26b133b99b0f52e247e3ff104935fe78c1b7aad18334c7ff", "tool": "Twitter", "notebook": "Send posts stats to Notion", "action": "", "tags": ["#twitter", "#post", "#comments", "#naas_drivers", "#snippet", "#content", "#notion"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maixmejublou", "updated_at": "2023-04-12", "created_at": "2022-06-09", "description": "This notebook allows you to track and analyze your Twitter posts and send the stats to Notion for further analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Twitter/Twitter_Send_posts_stats_to_Notion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Twitter/Twitter_Send_posts_stats_to_Notion.ipynb", "imports": ["naas", "naas_drivers.notion", "re", "regex", "numpy.inf", "emoji", "emoji", "tweepy", "pandas", "json", "typing.List", "datetime", "pydash"], "image_url": ""}, {"objectID": "a02d4dd206c67190a9b400df37c1a99e3f8213b2108561f054f3d2707589f920", "tool": "Typeform", "notebook": "Log New Entries In Notion Databases", "action": "", "tags": ["#typeform", "#notion", "#operations", "#automation"], "author": "Sanjeet Attili", "author_url": "https://billowy-lemming-95e.notion.site/f8e44ff261564c76b3bb80e6edb171a9?v=1d2a506563fe4082b71e78695185962e, which has all the questions asked in the typeform as column names and their responses as entries.\n\nThis output database consists of only 5 responses collected over the sample typeform.", "updated_at": "2023-04-12", "created_at": "2022-03-31", "description": "## Input", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Typeform/Typeform_Log_New_Typeform_Entries_In_Notion_Databases.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Typeform/Typeform_Log_New_Typeform_Entries_In_Notion_Databases.ipynb", "imports": ["naas_drivers.notion", "typeform.Typeform", "naas, pandas", "requests", "datetime.datetime", "pydash"], "image_url": ""}, {"objectID": "34d7d038a426cecb7dc11a0dbedab7b790e8494adc94264826f3259f8979e919", "tool": "US Bureau of Labor Statistics", "notebook": "Follow CPI", "action": "", "tags": ["#inflation", "#us", "#BLS", "#naas", "#scheduler", "#asset", "#snippet", "#automation", "#ai", "#analytics"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/j%C3%A9r%C3%A9my-ravenel-8a396910/", "updated_at": "2023-04-12", "created_at": "2022-07-16", "description": "This notebook provides an analysis of the US Bureau of Labor Statistics Consumer Price Index (CPI) over time.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/US%20Bureau%20of%20Labor%20Statistics/US_Bureau_of_Labor_Statistics_Follow_CPI.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/US%20Bureau%20of%20Labor%20Statistics/US_Bureau_of_Labor_Statistics_Follow_CPI.ipynb", "imports": ["pandas", "cpi", "seaborn", "matplotlib.pyplot", "naas", "naas_drivers.plotly"], "image_url": ""}, {"objectID": "a83d4ed0c1d03a2da02745a16b4d98f9d5cc99d5c0130126ecd8d4f24961496f", "tool": "Vizzu", "notebook": "Create Animated Bar Chart", "action": "", "tags": ["#vizzu", "#animation", "#bar-chart", "#data-visualization", "#data-science", "#python"], "author": "Alexandre Petit", "author_url": "https://www.linkedin.com/in/alexandre-petit-24a87a219/", "updated_at": "2023-04-25", "created_at": "2023-04-18", "description": "This notebook would allow you to create an animated bar chart. It will show the oil production evolution by country year after year.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Animated_Bar_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Animated_Bar_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style, DisplayTarget", "ipyvizzu.Chart, Data, Config, Style, DisplayTarget"], "image_url": ""}, {"objectID": "6a458ee798291f3b3f7887e81b2068fe7be5b41fb8db37d7dcffcef94f1bb500", "tool": "Vizzu", "notebook": "Create Animated Pie Chart", "action": "", "tags": ["#vizzu", "#animation", "#piechart", "#data", "#visualization", "#python"], "author": "Alexandre Petit", "author_url": "https://www.linkedin.com/in/alexandre-petit-24a87a219/", "updated_at": "2023-05-10", "created_at": "2023-04-25", "description": "This notebook will show how to create an animated pie chart with Vizzu. An animated pie chart can be useful for visualizing changes or transitions in categorical data over time.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Animated_Pie_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Animated_Pie_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style, DisplayTarget", "ipyvizzu.Chart, Data, Config, Style, DisplayTarget"], "image_url": ""}, {"objectID": "830f9c8e609c3df8a57c70b327d9eb459a1082c8a588947645d08c7b6b1b6868", "tool": "Vizzu", "notebook": "Create Column Chart", "action": "", "tags": ["#vizzu", "#analytics", "#dataviz", "#chart", "#graph", "#columnchart"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-27", "description": "This notebook template on Vizzu is designed to help users create visually appealing column charts. Vizzu is a powerful data visualization tool that allows users to easily create interactive and engaging charts and graphs.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Column_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Column_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style", "ipyvizzu.Chart, Data, Config, Style"], "image_url": ""}, {"objectID": "34436bb48b9455e15c60d687a2bb79c6e277c4a938966a5d87c5be2467bb22b2", "tool": "Vizzu", "notebook": "Create Grouped Column Chart", "action": "", "tags": ["#analytics", "#dataviz", "#chart", "#graph", "#groupedbarchart"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-27", "description": "This notebook template on Vizzu is designed to help users create visually appealing grouped column charts. Vizzu is a powerful data visualization tool that allows users to easily create interactive and engaging charts and graphs", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Grouped_Column_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Grouped_Column_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style", "ipyvizzu.Chart, Data, Config, Style"], "image_url": ""}, {"objectID": "9f4adb5f22c3959ac5b2c8004c963c98ea745b2d837e59960fc685f3844ca005", "tool": "Vizzu", "notebook": "Create Line Chart", "action": "", "tags": ["#analytics", "#dataviz", "#chart", "#graph", "#waterfallChart"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-03", "description": "This notebook template on Vizzu is designed to help users create visually appealing line charts. Vizzu is a powerful data visualization tool that allows users to easily create interactive and engaging charts and graphs", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Line_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Line_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style", "ipyvizzu.Chart, Data, Config, Style"], "image_url": ""}, {"objectID": "cc379f1a45e8d669d37d8156179c77eb989a3aad869dae103093651aedb99c62", "tool": "Vizzu", "notebook": "Create Stacked Column Chart", "action": "", "tags": ["#analytics", "#dataviz", "#chart", "#graph", "#stackedbarchart"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-03-27", "description": "This notebook template on Vizzu is designed to help users create visually appealing stacked column charts. Vizzu is a powerful data visualization tool that allows users to easily create interactive and engaging charts and graphs", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Stacked_Column_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Stacked_Column_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style", "ipyvizzu.Chart, Data, Config, Style"], "image_url": ""}, {"objectID": "c7522a696b863bf686badace2757c296a18d213491ddc905ae5edd1c2c547da6", "tool": "Vizzu", "notebook": "Create Waterfall Chart", "action": "", "tags": ["#analytics", "#dataviz", "#chart", "#graph", "#waterfallChart"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-03", "description": "This notebook template on Vizzu is designed to help users create visually appealing waterfall charts. Vizzu is a powerful data visualization tool that allows users to easily create interactive and engaging charts and graphs", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Vizzu/Vizzu_Create_Waterfall_Chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Vizzu/Vizzu_Create_Waterfall_Chart.ipynb", "imports": ["naas", "pandas", "ipyvizzu.Chart, Data, Config, Style", "ipyvizzu.Chart, Data, Config, Style"], "image_url": ""}, {"objectID": "78e0951d9b24d4a7bccd167a4af767b31a9916c4adbbdba076453909d87a7484", "tool": "WAQI", "notebook": "Display AQI on worldmap", "action": "", "tags": ["#waqi", "#airquality", "#api", "#data", "#city", "#stations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook displays AQI on worldmap.
\n\nAir Quality Index Scale:\n- 0 - 50: Good - Air quality is considered satisfactory, and air pollution poses little or no risk\n- 51 - 100: Moderate - Air quality is acceptable; however, for some pollutants there may be a moderate health concern for a very small number of people who are unusually sensitive to air pollution.\n- 101-150: Unhealthy for Sensitive Groups - Members of sensitive groups may experience health effects. The general public is not likely to be affected.\n- 151-200: Unhealthy - Everyone may begin to experience health effects; members of sensitive groups may experience more serious health effects.\n- 201-300: Very Unhealthy - Health warnings of emergency conditions. The entire population is more likely to be affected.\n- 300+: Hazardous - Health alert: everyone may experience more serious health effects.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WAQI/WAQI_Display_AQI_on_worldmap.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WAQI/WAQI_Display_AQI_on_worldmap.ipynb", "imports": ["requests", "naas", "pandas", "plotly.express"], "image_url": ""}, {"objectID": "1b1d23da1ea44c9fb55dfe63eddcbee38236d37467a51606381cfd20353906f4", "tool": "WAQI", "notebook": "Get daily air quality data by coordinates", "action": "", "tags": ["#waqi", "#airquality", "#api", "#data", "#city", "#python"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will demonstrate how to use the WAQI API to get daily air quality data for a city.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WAQI/WAQI_Get_daily_air_quality_data_by_coordinates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WAQI/WAQI_Get_daily_air_quality_data_by_coordinates.ipynb", "imports": ["requests", "naas", "pydash", "pprint.pprint"], "image_url": ""}, {"objectID": "71f15185e22b83a858312830275117c8f7e91e307ceb5b7d28a70d0629d73c63", "tool": "WAQI", "notebook": "Get daily air quality data for a city", "action": "", "tags": ["#waqi", "#airquality", "#api", "#data", "#city", "#python"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will demonstrate how to use the WAQI API to get daily air quality data for a city.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WAQI/WAQI_Get_daily_air_quality_data_for_a_city.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WAQI/WAQI_Get_daily_air_quality_data_for_a_city.ipynb", "imports": ["requests", "naas", "pydash", "pprint.pprint"], "image_url": ""}, {"objectID": "17d2397824593cc21b5d523eadcb2da7822e926c5cc0a4109deae7542ff97df7", "tool": "WAQI", "notebook": "Get stations by coordinates", "action": "", "tags": ["#waqi", "#airquality", "#api", "#data", "#city", "#stations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will demonstrate how to get stations within a given lat/lng bounds.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WAQI/WAQI_Get_stations_by_coordinates.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WAQI/WAQI_Get_stations_by_coordinates.ipynb", "imports": ["requests", "naas", "pandas", "plotly.express"], "image_url": ""}, {"objectID": "3d0747d79e0168df75adfc3ed3b500e5308bda1d114f932c5972004833cef961", "tool": "WAQI", "notebook": "Search station by name", "action": "", "tags": ["#waqi", "#airquality", "#api", "#data", "#city", "#python", "#stations"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-04-04", "description": "This notebook will demonstrate how to search stations by name using AQI API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WAQI/WAQI_Search_station_by_name.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WAQI/WAQI_Search_station_by_name.ipynb", "imports": ["requests", "naas", "pandas"], "image_url": ""}, {"objectID": "7c5471bb20ca17ba8b8ca70d01df4a2b65aa88a1e0c7810949b9ae13d5735662", "tool": "WSR", "notebook": "WHI Create indicator", "action": "", "tags": ["#wsr", "#whi", "#indicators", "#opendata", "#worldsituationroom", "#analytics", "#dataframe", "#image"], "author": "Peter Turner", "author_url": "https://www.linkedin.com/in/peter-turner-0839aa116/", "updated_at": "2023-04-12", "created_at": "2022-03-10", "description": "This notebook creates an indicator to measure the performance of the WSR-WHI portfolio.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WSR/WHI_Create_indicator.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WSR/WHI_Create_indicator.ipynb", "imports": ["pandas", "PIL.Image, ImageDraw, ImageFont", "datetime.date"], "image_url": ""}, {"objectID": "cc4d4bf571af50f16896b07354de0083ff3fb16b3b12963460441fda9ea72ffe", "tool": "WSR", "notebook": "Get daily Covid19 active cases trend JHU", "action": "", "tags": ["#wsr", "#covid", "#active-cases", "#plotly", "#opendata", "#snippet"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-20", "description": "This notebook provides a daily trend of Covid19 active cases from the Johns Hopkins University (JHU) dataset.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WSR/WSR_Get_daily_Covid19_active_cases_trend_JHU.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WSR/WSR_Get_daily_Covid19_active_cases_trend_JHU.ipynb", "imports": ["pandas", "datetime.datetime", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "aab90eca5a5dad874fdf39c39fe60d29d579c385566f7156bea44d68c7d6f84b", "tool": "WSR", "notebook": "Get daily Covid19 active cases worldmap JHU", "action": "", "tags": ["#wsr", "#covid", "#active-cases", "#analytics", "#plotly", "#automation", "#naas", "#opendata", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-07", "description": "This notebook provides a daily world map of active Covid-19 cases based on data from the Johns Hopkins University.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WSR/WSR_Get_daily_Covid19_active_cases_worldmap_JHU.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WSR/WSR_Get_daily_Covid19_active_cases_worldmap_JHU.ipynb", "imports": ["pandas", "datetime.datetime", "dataprep.clean.clean_country", "dataprep.clean.clean_country", "plotly.graph_objects", "naas"], "image_url": ""}, {"objectID": "20d2d1915c03323426f0cc05b016a752a34555d15cd4f08ab70992b5c1b93ec4", "tool": "WhatsApp", "notebook": "Create heatmap of activities", "action": "", "tags": ["#whatsapp", "#naas_drivers", "#naas", "#visualisation", "#chatminers", "#heatmap"], "author": "Hamid Mukhtar", "author_url": "https://www.linkedin.com/in/mukhtar-hamid/", "updated_at": "2023-05-31", "created_at": "2023-05-31", "description": "This notebook creates a heatmap of your chat activities.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WhatsApp/WhatsApp_Create_heatmap_of_activities.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WhatsApp/WhatsApp_Create_heatmap_of_activities.ipynb", "imports": ["chatminer", "chatminer.chatparsers.WhatsAppParser", "chatminer.visualizations", "matplotlib.pyplot"], "image_url": ""}, {"objectID": "ec40932392f591f65891e1b562c477459f79dd9c603a6fec6aeb8a299504ba47", "tool": "WhatsApp", "notebook": "Transform chat txt to dataframe", "action": "", "tags": ["#python", "#pandas", "#regex", "#whatsapp", "#chats"], "author": "Mohit Singh", "author_url": "https://www.linkedin.com/in/mohwits/", "updated_at": "2023-05-31", "created_at": "2023-05-31", "description": "This notebook transforms your WhatsApp chat export from txt to a dataframe.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WhatsApp/WhatsApp_Transform_chat_txt_to_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WhatsApp/WhatsApp_Transform_chat_txt_to_dataframe.ipynb", "imports": ["re", "pandas"], "image_url": ""}, {"objectID": "cbe5b94b80eae61d57207cec803c67f81a0575afcaed7275c80fc9d075f96727", "tool": "Wikipedia", "notebook": "List largest cities in the world", "action": "", "tags": ["#wikipedia", "#list", "#cities", "#largest", "#world", "#data"], "author": "Florent Ravenel", "author_url": "http://linkedin.com/in/florent-ravenel", "updated_at": "2023-04-12", "created_at": "2023-03-29", "description": "This notebook will show how to extract the list of the largest cities in the world using pandas.read_html() on Wikipedia.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Wikipedia/Wikipedia_List_largest_cities_in_the_world.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Wikipedia/Wikipedia_List_largest_cities_in_the_world.ipynb", "imports": ["pandas"], "image_url": ""}, {"objectID": "4db4cd15f329e1e7b0c097969fed6832b0cb73eb417217b92a97760ed9346872", "tool": "WindsorAI", "notebook": "Create Dash app to query AP", "action": "", "tags": ["#tool", "#naas_drivers", "#naas", "#dash", "#marketing", "#automation", "#ai", "#analytics"], "author": "Elia Dabbas", "author_url": "https://www.linkedin.com/in/eliasdabbas/", "updated_at": "2023-04-12", "created_at": "2022-11-07", "description": "This notebook enable anyone with a [Windsor.ai](https://windsor.ai/) account to visualy query the API with a Dash app.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WindsorAI/WindsorAI_Create_Dash_app_to_query_AP.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WindsorAI/WindsorAI_Create_Dash_app_to_query_AP.ipynb", "imports": ["json", "os", "requests", "pandas", "plotly.express", "dash.Dash, html, dcc, Input, Output, State, callback", "dash.dash_table.DataTable", "dash.exceptions.PreventUpdate", "jupyter_dash.JupyterDash", "dash_bootstrap_components", "dash_bootstrap_templates.load_figure_template"], "image_url": ""}, {"objectID": "193771e0df5a14495539f0f8a08b45fd29dedf23a589f38b21a52cda9ef2c528", "tool": "WorldBank", "notebook": "GDP contributors", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides an analysis of the countries and sectors that contribute the most to the World Bank's Gross Domestic Product (GDP).", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_GDP_contributors.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_GDP_contributors.ipynb", "imports": ["pandas", "pandas_datareader.wb", "plotly.graph_objects"], "image_url": ""}, {"objectID": "24fff5750f4dca229fa7019f91ec0b2298e646b23ee6db1ee2cbafc7ee510970", "tool": "WorldBank", "notebook": "GDP per capita and growth", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-04-14", "description": "This notebook provides an analysis of GDP per capita and growth data from the World Bank.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_GDP_per_capita_and_growth.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_GDP_per_capita_and_growth.ipynb", "imports": ["pandas", "numpy", "plotly.graph_objects", "pandas_datareader.wb", "naas_drivers.plotly"], "image_url": ""}, {"objectID": "56e6d83b1d5575e03cc57cf51cadc47b507a8be1e7159034e124b79ed8d3484d", "tool": "WorldBank", "notebook": "GDP per country and evolution", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "Objective : allows to visualize the distribution of GDP per capita and the GDP growth in the world. Click on the country on the map or select it to see the details info\n\nData :\nGDP PER CAPITA (CURRENT US$)\nGDP GROWTH (ANNUAL %)\n\nby countries, agregated by region\n\nSources:\n\nWorld Bank national accounts data,\nOECD National Accounts data files.\n\n\nProduction : Team Denver 2020/04/20 (MyDigitalSchool)", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_GDP_per_country_and_evolution.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_GDP_per_country_and_evolution.ipynb", "imports": ["pandas", "numpy", "plotly.graph_objects", "pandas_datareader.wb"], "image_url": ""}, {"objectID": "5bcd4bf5d4a562d15a90cc3079592749caa8cee07e3fc286953f7852b80f2daf", "tool": "WorldBank", "notebook": "Gini index", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides an analysis of the Gini index, a measure of income inequality, from the World Bank.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_Gini_index.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_Gini_index.ipynb", "imports": ["pandas", "pandas_datareader.wb", "plotly.graph_objects", "plotly.express"], "image_url": ""}, {"objectID": "9eff7cf860c115ac4cd5b982a41c4d7b8702252d797d1a3b2f40c5a45d1f01ab", "tool": "WorldBank", "notebook": "Most populated countries", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly", "#matplotlib"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "**Notebook d'exemple pour classer les pays les plus peupl\u00e9s**", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_Most_populated_countries.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_Most_populated_countries.ipynb", "imports": ["pandas", "matplotlib.pyplot", "requests", "io", "numpy", "plotly.graph_objects", "plotly.express", "pydrive.auth.GoogleAuth", "pydrive.drive.GoogleDrive", "google.colab.auth", "oauth2client.client.GoogleCredentials", "pandas.DataFrame", "plotly.graph_objects"], "image_url": ""}, {"objectID": "8b8c44156453589069394ba1341397036c04752815f24e4b25755a89994eefd5", "tool": "WorldBank", "notebook": "Richest countries top10", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides a comparison of the top 10 wealthiest countries in the world according to the World Bank.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_Richest_countries_top10.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_Richest_countries_top10.ipynb", "imports": ["pandas", "pandas_datareader.wb", "plotly.graph_objects"], "image_url": ""}, {"objectID": "a21ffefc3ea5fbec9b0555ed60b73a5fc6e516ff98c5bb53dcf085114f512c6b", "tool": "WorldBank", "notebook": "World employment by sector", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "**Objective**\n\nThis graph compares the world distribution of employment by sector with the country distribution. Select the country to visualize which sector is dominant.\n\nData\nby countries, by region\n\nSource\nInternational Labour Organization, ILOSTAT database.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_World_employment_by_sector.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_World_employment_by_sector.ipynb", "imports": ["math", "pandas", "datetime.datetime", "plotly.offline.iplot, plot, download_plotlyjs, init_notebook_mode", "plotly.graph_objects", "plotly.subplots.make_subplots"], "image_url": ""}, {"objectID": "115506753040f989d986e2a3e2f5e36b8bbe12f26be33950b4f3fd46d6334ab7", "tool": "WorldBank", "notebook": "World population and density", "action": "", "tags": ["#worldbank", "#opendata", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook provides an analysis of the world population and population density data from the World Bank.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/WorldBank/WorldBank_World_population_and_density.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/WorldBank/WorldBank_World_population_and_density.ipynb", "imports": ["pandas", "numpy", "plotly.express"], "image_url": ""}, {"objectID": "0483468fa84c29572e8b9a896e59fad9278a3d1b600646b604c19328fde51ea1", "tool": "Worldometer", "notebook": "World population evolution and projections", "action": "", "tags": ["#worldometer", "#opendata", "#population", "#snippet", "#plotly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-05-05", "description": "This notebook provides an overview of the current and projected population of the world, as tracked by Worldometer.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Worldometer/Worldometer_World_population_evolution_and_projections.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Worldometer/Worldometer_World_population_evolution_and_projections.ipynb", "imports": ["pandas", "plotly.express", "bs4.BeautifulSoup", "requests"], "image_url": ""}, {"objectID": "d53fcc695712505d6f768a768aaafc0bd1e79a5046278e1248620ddf40433a96", "tool": "XGBoost", "notebook": "Binary classification example with hyper-parameters optimization", "action": "", "tags": ["#xgboost", "#snippet", "#classification", "#tabular", "#cross-validation", "#optimization", "#modeling"], "author": "Oussama El Bahaoui", "author_url": "https://www.linkedin.com/in/oelbahaoui/", "updated_at": "2023-04-12", "created_at": "2022-11-02", "description": "This notebook provides an example of using XGBoost to perform binary classification with hyper-parameter optimization.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/XGBoost/XGBoost_Binary_classification_example_with_hyper-parameters_optimization.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/XGBoost/XGBoost_Binary_classification_example_with_hyper-parameters_optimization.ipynb", "imports": ["pandas", "sklearn.datasets.load_breast_cancer", "sklearn.model_selection.train_test_split", "sklearn.model_selection.GridSearchCV", "sklearn.metrics.accuracy_score", "xgboost.XGBClassifier", "xgboost.Booster, DMatrix"], "image_url": ""}, {"objectID": "495b6a709d9e2db6eca221adee7ec474d35a3b288156890ae1de6f6ee4a07f92", "tool": "XML", "notebook": "Transform sitemap to dataframe", "action": "", "tags": ["#xml", "#file", "#tool", "#operations", "#automation", "#dataframe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook demonstrates how to convert an XML sitemap into a dataframe for further analysis.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/XML/XML_Transform_sitemap_to_dataframe.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/XML/XML_Transform_sitemap_to_dataframe.ipynb", "imports": ["naas", "json", "xmltodict", "xmltodict", "pandas", "requests"], "image_url": ""}, {"objectID": "a898dc1a3589c789666fbcc6e4c8c13fbabeba4972e66345fa8ce99f66167ca4", "tool": "YahooFinance", "notebook": "Candlestick chart", "action": "", "tags": ["#yahoofinance", "#trading", "#yfin", "#investors", "#snippet", "#plotly"], "author": "Carlo Occhiena", "author_url": "https://www.linkedin.com/in/carloocchiena/", "updated_at": "2023-04-12", "created_at": "2022-02-15", "description": "This notebook provides a visual representation of stock market data using a candlestick chart from YahooFinance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Candlestick_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Candlestick_chart.ipynb", "imports": ["datetime", "pandas_datareader", "mplfinance", "mplfinance", "yfinance", "yfinance"], "image_url": ""}, {"objectID": "137e04149304fa44a56b90ffdd1ae4135bed5ecf9d7a1af519b6a9719dbda2e7", "tool": "YahooFinance", "notebook": "Chat about ANSYS trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#anss"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for ANSYS. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_ANSYS_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_ANSYS_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "67d1435531a07c950b1034eedb278afd390cb91499210c3a5b6e372bd0909c05", "tool": "YahooFinance", "notebook": "Chat about ASML Holding N.V. New York Registry Shares trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#asml"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for ASML Holding N.V. New York Registry Shares. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_ASML_Holding_N.V._New_York_Registry_Shares_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_ASML_Holding_N.V._New_York_Registry_Shares_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "cfeee65d70f77082037e63eed71c1df927d6f474625dd21705735107f8caedf2", "tool": "YahooFinance", "notebook": "Chat about Adobe trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#adbe"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Adobe. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Adobe_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Adobe_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "c12297fc39de90f732fdf6e8727dcee50d20309abd34aa0c5567b7e6ec0dbfd9", "tool": "YahooFinance", "notebook": "Chat about Advanced Micro Devices trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#amd"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Advanced Micro Devices. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Advanced_Micro_Devices_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Advanced_Micro_Devices_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "9b97c945f2437407a47bd3c57b695332090e77259b683d56ba77ae2829779bbf", "tool": "YahooFinance", "notebook": "Chat about Airbnb trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#abnb"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Airbnb. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Airbnb_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Airbnb_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a3ac6eeaac07c948b7136fc66fcd8d8b5b6ff19d8526bd4971d534ed7db8540b", "tool": "YahooFinance", "notebook": "Chat about Align Technology trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#algn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Align Technology. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Align_Technology_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Align_Technology_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "8712b081e23f2ec72cc749b6e163ff2a8ea02a58e4d2604f3480fe3760325d16", "tool": "YahooFinance", "notebook": "Chat about Alphabet trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#googl"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Alphabet. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Alphabet_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Alphabet_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "7442a91c5c92f0b2977cc8c63ebb89e6fc14b1eeffb74c140ae9019e41b949a8", "tool": "YahooFinance", "notebook": "Chat about Amazon trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#amzn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Amazon. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Amazon_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Amazon_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a35c22807ebe68c9343d8e68f3c9cdb5aae52f18c14e8768b8a7c32f63693aaa", "tool": "YahooFinance", "notebook": "Chat about American Electric Power Company trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#aep"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for American Electric Power Company. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_American_Electric_Power_Company_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_American_Electric_Power_Company_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "33b5fb710b3ab35effbacf6ca747ef7544f8018bbe23f9263d94e862d3ed9fdb", "tool": "YahooFinance", "notebook": "Chat about Amgen trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#amgn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Amgen. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Amgen_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Amgen_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "c0003ed1cef81656178f14fe01f3d4900e8b27b7ff09e5690b0f7df7c1013e43", "tool": "YahooFinance", "notebook": "Chat about Analog Devices trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#adi"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Analog Devices. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Analog_Devices_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Analog_Devices_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "55878e0bb39db7f7ec9d91383696db9cae1303a071708a3b69641496abe040f1", "tool": "YahooFinance", "notebook": "Chat about Applied Materials trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#amat"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Applied Materials. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Applied_Materials_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Applied_Materials_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "1d619046c14806a9c672847841c7e578a8c6d552c21bb23c2d1f02ca1233c9a4", "tool": "YahooFinance", "notebook": "Chat about AstraZeneca PLC American Depositary Shares trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#azn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for AstraZeneca PLC American Depositary Shares. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_AstraZeneca_PLC_American_Depositary_Shares_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_AstraZeneca_PLC_American_Depositary_Shares_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "4577fe5e924ca13d2708663e159f55caa969839e3ee60eb9f7128cdc84d94e3b", "tool": "YahooFinance", "notebook": "Chat about Atlassian Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#team"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Atlassian Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Atlassian_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Atlassian_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b77e6bea8afd054998edd60a9575cb7f4eb4f1892dc32bcf15c86bc383f7c314", "tool": "YahooFinance", "notebook": "Chat about Automatic Data Processing trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#adp"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Automatic Data Processing. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Automatic_Data_Processing_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Automatic_Data_Processing_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "1a78f98e507fb0f7d58e432604b0356801c72c976637ac9cf24bca82e55f48dd", "tool": "YahooFinance", "notebook": "Chat about Baker Hughes Company trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#bkr"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Baker Hughes Company. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Baker_Hughes_Company_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Baker_Hughes_Company_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "3fcc9d0b81420c95293ee3b9256bc3ba3d0c7d19f17cb2885585cc51038899ad", "tool": "YahooFinance", "notebook": "Chat about Biogen trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#biib"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Biogen. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Biogen_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Biogen_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b93ca207cc0d90cfb0098f8736b098162e23b2f9b3445b31a2edfc7a1aeadfa7", "tool": "YahooFinance", "notebook": "Chat about Broadcom trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#avgo"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Broadcom. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Broadcom_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Broadcom_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "6a5cd431c38902652eea214a15e9d794ffa74c375597df08d3fe7fe83d1ab47c", "tool": "YahooFinance", "notebook": "Chat about CSX Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#csx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for CSX Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_CSX_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_CSX_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "cab83cd9dbe7c71e0d929f902dfd749a72ebf0f7733d67e3870d6315a5fda09a", "tool": "YahooFinance", "notebook": "Chat about Cadence Design Systems trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#cdns"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Cadence Design Systems. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Cadence_Design_Systems_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Cadence_Design_Systems_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "d0b0c75e64a292c26ebcd750fa514e2ca247f8ecc5350f8c1370fc3daa05b808", "tool": "YahooFinance", "notebook": "Chat about Charter Communications New trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#chtr"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Charter Communications New. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Charter_Communications_New_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Charter_Communications_New_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "547f340cd1b93652c1ae40ebeae5f37ca1e461754823a20e5a771dbcce6ec85a", "tool": "YahooFinance", "notebook": "Chat about Cintas Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ctas"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Cintas Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Cintas_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Cintas_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "015bf4ca3350b1404278b0368261ca1222c6f592a41d066483c208706da73c64", "tool": "YahooFinance", "notebook": "Chat about Cisco Systems (DE) trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#csco"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Cisco Systems (DE). It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Cisco_Systems_%28DE%29_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Cisco_Systems_%28DE%29_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "107f4e5cb73f2c5b81c0e6475274751c6af6f14b19736f50dc276b4e51cc7d2e", "tool": "YahooFinance", "notebook": "Chat about CoStar Group trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#csgp"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for CoStar Group. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_CoStar_Group_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_CoStar_Group_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "ee99b1abd31b3fb8645c9dd8c138630b196fe4cd5721e597134a9219b5a05f88", "tool": "YahooFinance", "notebook": "Chat about Cognizant Technology Solutions Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ctsh"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Cognizant Technology Solutions Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Cognizant_Technology_Solutions_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Cognizant_Technology_Solutions_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "4a8a978bd1b54f6657ba1cd830060cd2b64787da8bc33617ade439ec0ff50112", "tool": "YahooFinance", "notebook": "Chat about Constellation Energy Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ceg"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Constellation Energy Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Constellation_Energy_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Constellation_Energy_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "447347f9c3f121c37c46d4eee677c043e5b682e3212f4dd4c0abc6a464110bf1", "tool": "YahooFinance", "notebook": "Chat about Copart (DE) trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#cprt"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Copart (DE). It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Copart_%28DE%29_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Copart_%28DE%29_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "fc8ebcb14dd4ef18e5225f97ae2a1fa5b6021c64df8c2e450f487db862366257", "tool": "YahooFinance", "notebook": "Chat about CrowdStrike Holdings trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#crwd"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for CrowdStrike Holdings. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_CrowdStrike_Holdings_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_CrowdStrike_Holdings_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "537b6a1495f7e34472a43bf762c6bae8b2784bcb86fc40238dd3da25c59f964c", "tool": "YahooFinance", "notebook": "Chat about Datadog trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ddog"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Datadog. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Datadog_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Datadog_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b6da0211691a90b7e285172167a44ede266655142d0efa21ee9c9e871684ea93", "tool": "YahooFinance", "notebook": "Chat about DexCom trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#dxcm"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for DexCom. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_DexCom_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_DexCom_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "e3b5fa5803456f044eac92f1f1eed584af84ec4ce15355711d6d9c32f175fc35", "tool": "YahooFinance", "notebook": "Chat about Diamondback Energy trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#fang"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Diamondback Energy. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Diamondback_Energy_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Diamondback_Energy_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "5513bf7405619286d7dd94cccd73c8e6f44fdf574e91647762f69f8d736b6103", "tool": "YahooFinance", "notebook": "Chat about Dollar Tree trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#dltr"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Dollar Tree. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Dollar_Tree_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Dollar_Tree_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "6f7f4725c55c953578a694de1fc755a069d8478bef875a0dc856a22934822b86", "tool": "YahooFinance", "notebook": "Chat about Electronic Arts trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ea"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Electronic Arts. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Electronic_Arts_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Electronic_Arts_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "c2ae19b4da5e590936adac028d3258d60b0a56eb878ca1d2fab0e09e54b5e3fd", "tool": "YahooFinance", "notebook": "Chat about Enphase Energy trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#enph"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Enphase Energy. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Enphase_Energy_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Enphase_Energy_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "240e62189bbb4510c941cfdcb981c9366c325b1beba64baaedfbb33df2969973", "tool": "YahooFinance", "notebook": "Chat about Exelon Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#exc"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Exelon Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Exelon_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Exelon_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "617b1c431c962cac8e3fff2f258b5469b3f4b6df9bb62899184a2c03c24cf214", "tool": "YahooFinance", "notebook": "Chat about Fastenal Company trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#fast"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Fastenal Company. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Fastenal_Company_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Fastenal_Company_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "4a6593ba0b7f8eeb0f0a018c55312c84a89be3285e76943fba8045f0b5200570", "tool": "YahooFinance", "notebook": "Chat about Fortinet trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ftnt"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Fortinet. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Fortinet_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Fortinet_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "46292fcce418d5dd9164b2fa10154c0e2f365ff0b50c8af907004542c80aedae", "tool": "YahooFinance", "notebook": "Chat about GE HealthCare Technologies trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#gehc"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for GE HealthCare Technologies. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_GE_HealthCare_Technologies_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_GE_HealthCare_Technologies_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "91c0ff92b60058940c7d6c509c1d9b0a08a1245bedf1018c5549ac86928d3392", "tool": "YahooFinance", "notebook": "Chat about Gilead Sciences trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#gild"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Gilead Sciences. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Gilead_Sciences_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Gilead_Sciences_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "0ab6db5174984a9d7d455d4709cc22cf491ec3ac8ad201bad080c5a0c190437e", "tool": "YahooFinance", "notebook": "Chat about GlobalFoundries Ordinary Shares trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#gfs"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for GlobalFoundries Ordinary Shares. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_GlobalFoundries_Ordinary_Shares_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_GlobalFoundries_Ordinary_Shares_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "4e2a2a01fabebad50d09483245e48b74977a610c36bd1737c8ebf0cfe3016f10", "tool": "YahooFinance", "notebook": "Chat about Honeywell International trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#hon"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Honeywell International. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Honeywell_International_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Honeywell_International_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "3d986c84f0125077ef63562648c5f4b83a93aa424559e05883d371f5582d5767", "tool": "YahooFinance", "notebook": "Chat about IDEXX Laboratories trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#idxx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for IDEXX Laboratories. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_IDEXX_Laboratories_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_IDEXX_Laboratories_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "3c17e25d613ad4c36f8ae297180d6857ad6601312c2941b4a8b74b06a3d70631", "tool": "YahooFinance", "notebook": "Chat about Illumina trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ilmn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Illumina. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Illumina_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Illumina_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b7a075b26170dba007791236caf121e8c4e70c660084d1852578db48498fba7b", "tool": "YahooFinance", "notebook": "Chat about Intel Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#intc"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Intel Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Intel_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Intel_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "8b67945087a2b87f28842129eb46b8819fc9949e69e758d96bd547a0712451bc", "tool": "YahooFinance", "notebook": "Chat about Intuit trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#intu"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Intuit. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Intuit_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Intuit_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "78063fe941e4aea1611b8edd59b8a5ef255534393fe50db58cba98b41ffe1799", "tool": "YahooFinance", "notebook": "Chat about JD.com American Depositary Shares trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#jd"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for JD.com American Depositary Shares. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_JD.com_American_Depositary_Shares_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_JD.com_American_Depositary_Shares_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "427bf682c422773d5ddd3918b64407ffd63f01c7ba288f70c1ac2963fa1f6e3c", "tool": "YahooFinance", "notebook": "Chat about KLA Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#klac"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for KLA Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_KLA_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_KLA_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a6bb9402e581a9b68a9590912e9233e8617d5e2b606e5c54857913b05f18934f", "tool": "YahooFinance", "notebook": "Chat about Keurig Dr Pepper trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#kdp"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Keurig Dr Pepper. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Keurig_Dr_Pepper_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Keurig_Dr_Pepper_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "7bdec616e0ad2a31ebffe3c74ea0278440d1bf2523a386b70e3e514b92e3793f", "tool": "YahooFinance", "notebook": "Chat about Lam Research Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#lrcx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Lam Research Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Lam_Research_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Lam_Research_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "c6ac96f819ac4f14ca7f93b40dfbb45dad2d0614ded16c12308de632edcfbfcf", "tool": "YahooFinance", "notebook": "Chat about Lucid Group trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#lcid"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Lucid Group. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Lucid_Group_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Lucid_Group_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "fcf41f4a1b7ae82f6e54a212027dd016471068a77094ce6ef1de9f9d82d45aca", "tool": "YahooFinance", "notebook": "Chat about Marriott International trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#mar"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Marriott International. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Marriott_International_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Marriott_International_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "263aba353d8f9357f95f43cdd0621cbb0cf45065685f52c79a679752a802a9ed", "tool": "YahooFinance", "notebook": "Chat about Marvell Technology trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#mrvl"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Marvell Technology. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Marvell_Technology_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Marvell_Technology_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "d8aeecd630bf684bfcd05bd4d00f20681cc70d3917f8532a2a1ec77161e5ba36", "tool": "YahooFinance", "notebook": "Chat about MercadoLibre trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#meli"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for MercadoLibre. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_MercadoLibre_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_MercadoLibre_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "1e3a1cef24e84c08dc8c83d087ba42e49610950d64e03788f5e52fcf00b9d750", "tool": "YahooFinance", "notebook": "Chat about Meta Platforms trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#meta"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Meta Platforms. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Meta_Platforms_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Meta_Platforms_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "cd5d64bded282ffa3d3842046291d82484ba8abf4f1faa1e9fd267d03e575053", "tool": "YahooFinance", "notebook": "Chat about Micron Technology trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#mu"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Micron Technology. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Micron_Technology_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Micron_Technology_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "74eab3bae5e86278e3ca13ca4f33990898eba59ce3f3d1c6d85f4190d2cf3aa1", "tool": "YahooFinance", "notebook": "Chat about Mondelez International trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#mdlz"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Mondelez International. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Mondelez_International_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Mondelez_International_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "6ba5fa95466a49f883d852b9ece1ab347a700093238041fedb9eba78acc74aaa", "tool": "YahooFinance", "notebook": "Chat about NVIDIA Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#nvda"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for NVIDIA Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_NVIDIA_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_NVIDIA_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "9bba3c154699bf08e2e262522536f7297e6312f8773fae23415f3ca24e258cdc", "tool": "YahooFinance", "notebook": "Chat about NXP Semiconductors N.V. trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#nxpi"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for NXP Semiconductors N.V.. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_NXP_Semiconductors_N.V._trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_NXP_Semiconductors_N.V._trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "960f588a34b9a35496a661f75eba990bf1a9552dba7741b7605728e7e02907f1", "tool": "YahooFinance", "notebook": "Chat about Netflix trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#nflx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Netflix. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Netflix_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Netflix_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "7a4daaf71c3c1e492adf8f18b2c4e9c72975bf50ba2f395e397ef8365b15ce8a", "tool": "YahooFinance", "notebook": "Chat about O'Reilly Automotive trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#orly"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for O'Reilly Automotive. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_O%27Reilly_Automotive_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_O%27Reilly_Automotive_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "aaf6ff6f640bc6b47ebf6e7d6c9b499df33dd54e2bc50bd891f3ea11dc8542a8", "tool": "YahooFinance", "notebook": "Chat about ON Semiconductor Corporation trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#on"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for ON Semiconductor Corporation. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_ON_Semiconductor_Corporation_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_ON_Semiconductor_Corporation_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "4eaaea6f5d3f24a61f54aa9d899bb3c61f73dea314a0bf2512f17fabbdaf3b3b", "tool": "YahooFinance", "notebook": "Chat about Old Dominion Freight Line trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#odfl"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Old Dominion Freight Line. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Old_Dominion_Freight_Line_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Old_Dominion_Freight_Line_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "b529dfa0c4badc909054307b3bc1f408eb06e6a04938f3d5498c5a8927e625d7", "tool": "YahooFinance", "notebook": "Chat about PDD Holdings American Depositary Shares trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#pdd"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for PDD Holdings American Depositary Shares. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_PDD_Holdings_American_Depositary_Shares_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_PDD_Holdings_American_Depositary_Shares_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "d2c9c91e8a399468f54f50783010ca1185cd87f31e353e7db89193a18702d20a", "tool": "YahooFinance", "notebook": "Chat about PayPal Holdings trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#pypl"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for PayPal Holdings. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_PayPal_Holdings_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_PayPal_Holdings_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "365c9341c4966218f330392186eb8fa0df14620e5e616b5402a626ea3fe8579c", "tool": "YahooFinance", "notebook": "Chat about Paychex trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#payx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Paychex. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Paychex_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Paychex_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "8821c967642c554155c4f8220840fd09a1c4ca43ef383be66a4b570d77b0b124", "tool": "YahooFinance", "notebook": "Chat about PepsiCo trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#pep"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for PepsiCo. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_PepsiCo_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_PepsiCo_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "9b1b3a5e86f9ac6a53af523f9e98dffe43ec646e4ba26fae584537255dd62334", "tool": "YahooFinance", "notebook": "Chat about QUALCOMM Incorporated trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#qcom"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for QUALCOMM Incorporated. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_QUALCOMM_Incorporated_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_QUALCOMM_Incorporated_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "fd1533db5680f347b4787081c34eb457fca5e7ced055c22a3876898eb7019108", "tool": "YahooFinance", "notebook": "Chat about Regeneron Pharmaceuticals trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#regn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Regeneron Pharmaceuticals. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Regeneron_Pharmaceuticals_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Regeneron_Pharmaceuticals_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a6467944df278b9d1b03ebbbe2aa332af03886cc927c4b977beefa807b2aada7", "tool": "YahooFinance", "notebook": "Chat about Ross Stores trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#rost"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Ross Stores. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Ross_Stores_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Ross_Stores_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "cfb36fc2149e1808cea1666e3545d905d39e158e314cf2cf0a6a93d089304130", "tool": "YahooFinance", "notebook": "Chat about Seagen trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#sgen"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Seagen. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Seagen_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Seagen_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "3ace2f2927d6767ded820491c2a354a4364e73a157b133d01171faa9b4bdbbd9", "tool": "YahooFinance", "notebook": "Chat about Sirius XM Holdings trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#siri"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Sirius XM Holdings. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Sirius_XM_Holdings_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Sirius_XM_Holdings_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "dac33469fa100d5f211ec46b0303f509510391b5bc3baebd678f94d5ddb8131e", "tool": "YahooFinance", "notebook": "Chat about Synopsys trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#snps"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Synopsys. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Synopsys_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Synopsys_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "ede9456621f68bbd2bf4205ac34222d0a931b1c0579d8e09565428d7fd51b51a", "tool": "YahooFinance", "notebook": "Chat about T-Mobile US trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#tmus"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for T-Mobile US. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_T-Mobile_US_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_T-Mobile_US_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a59201976348cd448a95b933eb1985c9141876cb20a1782ed0481a7acd9b9564", "tool": "YahooFinance", "notebook": "Chat about Tesla trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#tsla"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Tesla. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Tesla_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Tesla_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "436b31f6e6c4f53bfc314880c479f177cf4ca0f705f1dd7ea930400c45ab3f12", "tool": "YahooFinance", "notebook": "Chat about Texas Instruments Incorporated trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#txn"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Texas Instruments Incorporated. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Texas_Instruments_Incorporated_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Texas_Instruments_Incorporated_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "52e5316fa76780f3764a5c6393c5ff4ac14224c0d465c9e75f51cc259c08c48d", "tool": "YahooFinance", "notebook": "Chat about The Trade Desk trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ttd"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for The Trade Desk. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_The_Trade_Desk_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_The_Trade_Desk_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "0d71238f0ddbffa48c968731586e26ef61c2f9a49832fd5b3a5f930a1185c3b4", "tool": "YahooFinance", "notebook": "Chat about Verisk Analytics trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#vrsk"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Verisk Analytics. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Verisk_Analytics_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Verisk_Analytics_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "a3437a7718690ff3e7fd995e8e5a1d451ecbd6f16dcfe51a214815c79324ba3b", "tool": "YahooFinance", "notebook": "Chat about Vertex Pharmaceuticals Incorporated trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#vrtx"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Vertex Pharmaceuticals Incorporated. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Vertex_Pharmaceuticals_Incorporated_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Vertex_Pharmaceuticals_Incorporated_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "ed1e147cb80c7cd2ad38b3640802addcfc9560be6029ae08188f3ba3b9ad47af", "tool": "YahooFinance", "notebook": "Chat about Walgreens Boots Alliance trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#wba"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Walgreens Boots Alliance. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Walgreens_Boots_Alliance_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Walgreens_Boots_Alliance_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "aacd9e914528ab2164bee48b3414c8549fb3898dd43b7bd485f086e284d4699e", "tool": "YahooFinance", "notebook": "Chat about Workday trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#wday"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Workday. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Workday_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Workday_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "dc78883dcf77261a79ea66d921472333e6d319110f1582e4112a0a853bd46582", "tool": "YahooFinance", "notebook": "Chat about Xcel Energy trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#xel"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Xcel Energy. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Xcel_Energy_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Xcel_Energy_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "9cb8ec1ce5db1edbfb0e638cea3e930afaf3a0051229aa266a444c43744ea32a", "tool": "YahooFinance", "notebook": "Chat about Zoom Video Communications trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#zm"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Zoom Video Communications. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Zoom_Video_Communications_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Zoom_Video_Communications_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "fb5e9cc3776ee111f5437f1bc60512d03ee2a518bf77fae1f52b787b237b416b", "tool": "YahooFinance", "notebook": "Chat about Zscaler trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#zs"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for Zscaler. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_Zscaler_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_Zscaler_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "79ecd741c9e6b35b4dc307ebe6698fe774c8378c7cb4062e93613ec6c021f4d0", "tool": "YahooFinance", "notebook": "Chat about eBay trends and predictions", "action": "", "tags": ["#yahoo", "#finance", "#ai", "#chat", "#plugin", "#python", "#ebay"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/jeremyravenel/", "updated_at": "2023-08-31", "created_at": "2023-08-31", "description": "This notebook will generate an Naas Chat plugin for YahooFinance for eBay. It uses Python to access the YahooFinance API, NewsAPI, create one big table with actual, predictions, news, and sentiment and output a plugin that can be used to answer questions about the stock performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Chat_about_eBay_trends_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Chat_about_eBay_trends_and_predictions.ipynb", "imports": ["os", "os.path", "naas", "pandas", "naas_drivers.prediction, yahoofinance, plotly, newsapi", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML", "nltk", "nltk", "nltk.sentiment.vader.SentimentIntensityAnalyzer", "json", "tiktoken", "tiktoken"], "image_url": ""}, {"objectID": "dbcda358b6ff27edb6f4b4b3a38e00714efe3a2137bf3e9210e0d24d0b8629d5", "tool": "YahooFinance", "notebook": "Cryptocurrencies heatmap correlation graph", "action": "", "tags": ["#yahoofinance", "#cryptocurrency", "#eth", "#btc", "#heatmap", "#finance", "#trading", "#investors", "#snippet", "#matplotlib"], "author": "Carlo Occhiena", "author_url": "https://www.linkedin.com/in/carloocchiena/", "updated_at": "2023-04-12", "created_at": "2022-02-15", "description": "This notebook provides a graphical representation of the correlation between different cryptocurrencies using a heatmap from YahooFinance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Cryptocurrencies_heatmap_correlation_graph.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Cryptocurrencies_heatmap_correlation_graph.ipynb", "imports": ["datetime", "matplotlib.pyplot", "seaborn", "seaborn", "yfinance", "yfinance"], "image_url": ""}, {"objectID": "7c08faa1a4fa6c75084204d90c6879159bb412b0ce01e9b97d266d2ecacbac6a", "tool": "YahooFinance", "notebook": "Display chart from ticker", "action": "", "tags": ["#yahoofinance", "#trading", "#plotly", "#naas_drivers", "#investors", "#snippet", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-11-22", "description": "This notebook provides a graphical representation of stock market data from a given ticker symbol using the YahooFinance API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Display_chart_from_ticker.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Display_chart_from_ticker.ipynb", "imports": ["naas_drivers.yahoofinance, plotly"], "image_url": ""}, {"objectID": "1f6fb2f8e71d845ac2e577bfd652de2c88017889251c387d91c687840505a839", "tool": "YahooFinance", "notebook": "Find the stock with closest performance using KNN", "action": "", "tags": ["#tool", "#naas_drivers", "#naas", "#scheduler", "#asset", "#snippet", "#automation", "#ai", "#analytics", "#yahoo", "#clustering", "#stocks"], "author": "Abhinav Lakhani", "author_url": "https://www.linkedin.com/in/abhinav-lakhani/", "updated_at": "2023-04-12", "created_at": "2022-06-23", "description": "This notebook uses KNN to find the stock with the most similar performance to a given stock from YahooFinance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Find_the_stock_with_closest_performance_using_KNN.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Find_the_stock_with_closest_performance_using_KNN.ipynb", "imports": ["naas_drivers.yahoofinance", "naas", "pylab.plot, show", "numpy.vstack, array", "numpy.random.rand", "numpy", "scipy.cluster.vq.kmeans, vq", "pandas", "math.sqrt", "sklearn.cluster.KMeans", "matplotlib.pyplot"], "image_url": ""}, {"objectID": "e4faa959f82ec8398c2290f27c0a1297a4d02d32981e982ced4d1aa2fa89efc7", "tool": "YahooFinance", "notebook": "Get Brent Crude Oil trend and predictions", "action": "", "tags": ["#commodities", "#energy", "#petrol", "#oil", "#yahoofinance", "#trading", "#markdown", "#prediction", "#plotly", "#naas_drivers", "#notification", "#naas", "#investors", "#automation", "#analytics", "#ai", "#html", "#image"], "author": "Ayoub Berdeddouch", "author_url": "https://www.linkedin.com/in/ayoub-berdeddouch/", "updated_at": "2023-04-12", "created_at": "2022-11-03", "description": "This notebook provides an analysis of the current trend and predictions for Brent Crude Oil prices using data from YahooFinance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Get_Brent_Crude_Oil_trend_and_predictions.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Get_Brent_Crude_Oil_trend_and_predictions.ipynb", "imports": ["naas", "naas_drivers.prediction, yahoofinance, plotly", "plotly.graph_objects", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML"], "image_url": ""}, {"objectID": "9452ee3b76b3da57b58787412419b2f1bb939f7830d1114e8e84a9ea739da137", "tool": "YahooFinance", "notebook": "Get Stock Update", "action": "", "tags": ["#yahoofinance", "#usdinr", "#plotly", "#investors", "#analytics", "#automation"], "author": "Megha Gupta", "author_url": "https://github.com/megha2907", "updated_at": "2023-04-12", "created_at": "2022-01-27", "description": "This notebook provides a convenient way to access up-to-date stock information from Yahoo Finance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Get_Stock_Update.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Get_Stock_Update.ipynb", "imports": ["naas", "naas_drivers.yahoofinance, plotly", "markdown2", "IPython.display.Markdown", "naas"], "image_url": ""}, {"objectID": "5296f754c8c0b510e03f2bff45b3f988f676c51e6e82fe4b042cb712b99ae73c", "tool": "YahooFinance", "notebook": "Get USDEUR data and chart", "action": "", "tags": ["#yahoofinance", "#trading", "#plotly", "#naas_drivers", "#investors", "#analytics"], "author": "Carlo Occhiena", "author_url": "https://www.linkedin.com/in/carloocchiena/", "updated_at": "2023-04-12", "created_at": "2022-02-08", "description": "This notebook provides a way to access and visualize the current exchange rate between the US Dollar and the Euro.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Get_USDEUR_data_and_chart.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Get_USDEUR_data_and_chart.ipynb", "imports": ["naas_drivers.yahoofinance, plotly"], "image_url": ""}, {"objectID": "c56ffadc687c98b7845b537fb4fffb768d7e122a3fee299688159595acda7bf3", "tool": "YahooFinance", "notebook": "Get data from ticker", "action": "", "tags": ["#yahoofinance", "#trading", "#naas_drivers", "#investors", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-06-14", "created_at": "2021-11-22", "description": "This notebook provides a way to access financial data from a given ticker symbol using the YahooFinance API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Get_data_from_ticker.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Get_data_from_ticker.ipynb", "imports": ["naas_drivers.yahoofinance"], "image_url": ""}, {"objectID": "705946d5a30b03afbb6b0aa8cafddce513528727663b25c55d30c2870407c02c", "tool": "YahooFinance", "notebook": "Send daily prediction to Email", "action": "", "tags": ["#yahoofinance", "#trading", "#markdown", "#prediction", "#plotly", "#slack", "#naas_drivers", "#notification", "#naas", "#investors", "#automation", "#analytics", "#email", "#html", "#image"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-12-02", "description": "This notebook sends daily predictions from YahooFinance to an email address.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Email.ipynb", "imports": ["naas", "naas_drivers.prediction, yahoofinance, plotly", "markdown2", "datetime.datetime", "IPython.core.display.display, HTML"], "image_url": ""}, {"objectID": "ec092922ecd04f252b65058b599ac56f50a0cc7abccc6cb2b8942b9a3fba465b", "tool": "YahooFinance", "notebook": "Send daily prediction to Notion", "action": "", "tags": ["#yahoofinance", "#trading", "#markdown", "#prediction", "#plotly", "#slack", "#naas_drivers", "#scheduler", "#notification", "#asset", "#webhook", "#dependency", "#naas", "#investors", "#automation", "#analytics", "#html", "#image", "#notion"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2022-05-06", "description": "This notebook sends daily stock market predictions from YahooFinance to Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Notion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Notion.ipynb", "imports": ["naas", "naas_drivers.prediction, yahoofinance, plotly, notion", "datetime.datetime", "naas_drivers.tools.notion.Link, BlockEmbed", "pytz"], "image_url": ""}, {"objectID": "e56f3194ca88ec903b95cb38754d2c16cce3da81e9a7583bd206ff177083020c", "tool": "YahooFinance", "notebook": "Send daily prediction to Slack", "action": "", "tags": ["#yahoofinance", "#trading", "#markdown", "#prediction", "#plotly", "#slack", "#naas_drivers", "#scheduler", "#naas", "#investors", "#automation", "#analytics"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2021-09-16", "description": "This notebook sends daily stock market predictions from YahooFinance to Slack.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Slack.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YahooFinance/YahooFinance_Send_daily_prediction_to_Slack.ipynb", "imports": ["naas", "naas_drivers.prediction, yahoofinance, plotly, slack", "markdown2", "datetime.datetime", "naas"], "image_url": ""}, {"objectID": "2ded78b09046383b0f26f14bae6ea2b48834e06dc5f192d334ad9a604a24ac2f", "tool": "YouTube", "notebook": "Download video", "action": "", "tags": ["#youtube", "#download", "#video", "#content", "#snippet", "#naas"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-06-03", "created_at": "2022-03-18", "description": "This notebook allows users to download videos from YouTube.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Download_video.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Download_video.ipynb", "imports": ["pytube.YouTube", "pytube.YouTube"], "image_url": ""}, {"objectID": "da5c2903e57893dad62f8502805f51e26481cd2488d6c8dbd122e2db4b23f38e", "tool": "YouTube", "notebook": "Extract and summarize transcript", "action": "", "tags": ["#youtube", "#transcript", "#video", "#summarize", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a method to extract and summarize the transcript of a YouTube video.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Extract_and_summarize_transcript.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Extract_and_summarize_transcript.ipynb", "imports": ["youtube_transcript_api.YouTubeTranscriptApi", "naas_drivers.huggingface"], "image_url": ""}, {"objectID": "dee84b001ccaccc3f883887549c5cd1c875c53528fac1004ffc8fbdcf0fb6c03", "tool": "YouTube", "notebook": "Extract transcript from video", "action": "", "tags": ["#youtube", "#transcript", "#video", "#naas_drivers", "#content", "#snippet", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a guide to extracting transcripts from YouTube videos.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Extract_transcript_from_video.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Extract_transcript_from_video.ipynb", "imports": ["pandas", "naas_drivers.youtube"], "image_url": ""}, {"objectID": "429ba3a376300f201bef648d8098ded0e3912f0d2c893732c709dea771746cca", "tool": "YouTube", "notebook": "Get statistics from channel", "action": "", "tags": ["#youtube", "#channel", "#statistics", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a way to access and analyze data from a YouTube channel to gain insights into its performance.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Get_statistics_from_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Get_statistics_from_channel.ipynb", "imports": ["naas", "naas_drivers.youtube"], "image_url": ""}, {"objectID": "0aa4588cbaaf7815d2de3c8fcec9b1bb0641760a255998dc86a3c5e8e4c9739f", "tool": "YouTube", "notebook": "Get statistics from video", "action": "", "tags": ["#youtube", "#video", "#statistics", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a way to get detailed statistics from YouTube videos.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Get_statistics_from_video.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Get_statistics_from_video.ipynb", "imports": ["naas", "naas_drivers.youtube"], "image_url": ""}, {"objectID": "8776b7a1311600362f191c19e9610009af2567a3a84141c76365b95eadef593d", "tool": "YouTube", "notebook": "Get uploads from channel", "action": "", "tags": ["#youtube", "#channel", "#videos", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook allows you to retrieve all the videos uploaded to a specific YouTube channel.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Get_uploads_from_channel.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Get_uploads_from_channel.ipynb", "imports": ["naas", "naas_drivers.youtube"], "image_url": ""}, {"objectID": "6d4cc03eb6e8b18900cb63af0ab5a97cd17be85547cff41eb2a6e32d95a78b8f", "tool": "YouTube", "notebook": "Send track to Spotify", "action": "", "tags": ["#youtube", "#spotify", "#snippet"], "author": "Josef", "author_url": "https://www.linkedin.com/in/joseftrchalik/", "updated_at": "2023-04-12", "created_at": "2022-06-03", "description": "This notebook allows users to easily send tracks from YouTube to their Spotify account.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Send_track_to_Spotify.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Send_track_to_Spotify.ipynb", "imports": ["spotipy", "spotipy", "spotipy.util", "spotipy.oauth2.SpotifyClientCredentials", "spotipy.SpotifyOAuth", "youtube_dl", "youtube_dl", "google_auth_oauthlib.flow", "google_auth_oauthlib.flow", "googleapiclient.discovery", "googleapiclient.errors", "googleapiclient.discovery", "googleapiclient.errors", "requests, json, os, re, time", "urllib.parse.parse_qs, urlparse", "subprocess.Popen, PIPE", "signal.SIGTERM, SIGKILL", "ant information"], "image_url": ""}, {"objectID": "fd09a21e12b5b8e8d4792169756d6cedf4d8dcc08c7c317062acdadd85f545a8", "tool": "YouTube", "notebook": "Send video stats to Notion", "action": "", "tags": ["#youtube", "#video", "#statistics", "#naas_drivers", "#content", "#snippet", "#dataframe"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2022-06-07", "description": "This notebook allows you to easily track and analyze your YouTube video performance by automatically sending video stats to Notion.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Send_video_stats_to_Notion.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Send_video_stats_to_Notion.ipynb", "imports": ["naas", "naas_drivers.youtube, notion", "pandas", "pydash", "re", "regex", "emoji", "emoji"], "image_url": ""}, {"objectID": "b451c356f8536123376b8e3ed3e9841ff3ad49a0ad1eb9577952270b63e6e15b", "tool": "YouTube", "notebook": "Summarize video", "action": "", "tags": ["#youtube", "#transcript", "#video", "#npl", "#naas_drivers", "#content", "#snippet", "#text"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/ACoAABCNSioBW3YZHc2lBHVG0E_TXYWitQkmwog/", "updated_at": "2023-04-12", "created_at": "2022-03-18", "description": "This notebook provides a summary of a YouTube video, allowing users to quickly understand the content of the video.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/YouTube/YouTube_Summarize_video.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/YouTube/YouTube_Summarize_video.ipynb", "imports": ["naas_drivers.youtube"], "image_url": ""}, {"objectID": "e62887290cc7a4c0b82ec67c82df44f9f6236be9992da26426b64649630170c0", "tool": "ZIP", "notebook": "Extract files", "action": "", "tags": ["#zip", "#extract", "#file", "#operations", "#snippet", "#naas"], "author": "Maxime Jublou", "author_url": "https://www.linkedin.com/in/maximejublou", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook allows users to extract files from a ZIP archive.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/ZIP/ZIP_Extract_files.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/ZIP/ZIP_Extract_files.ipynb", "imports": ["zipfile", "os", "pprint.pprint"], "image_url": ""}, {"objectID": "86607d1e05a7be9ceac61f0f3b044a650e57614b93b448afc38002e40ae92ade", "tool": "Zapier", "notebook": "Trigger workflow", "action": "", "tags": ["#zapier", "#nocode", "#operations", "#snippet"], "author": "Jeremy Ravenel", "author_url": "https://www.linkedin.com/in/ACoAAAJHE7sB5OxuKHuzguZ9L6lfDHqw--cdnJg/", "updated_at": "2023-04-12", "created_at": "2021-03-01", "description": "This notebook allows you to create automated workflows that are triggered by specific events.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/Zapier/Zapier_Trigger_workflow.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/Zapier/Zapier_Trigger_workflow.ipynb", "imports": ["naas_drivers"], "image_url": ""}, {"objectID": "1a4862f36ffb7a7c2766294894d690900fe245a354ba9b805fde9d40460f92c9", "tool": "ZeroBounce", "notebook": "Validate Single Email", "action": "", "tags": ["#zerobounce", "#email", "#validation", "#java", "#sdk", "#setup"], "author": "Florent Ravenel", "author_url": "https://www.linkedin.com/in/florent-ravenel/", "updated_at": "2023-04-12", "created_at": "2023-02-27", "description": "This notebook will demonstrate how to validate a single email address using ZeroBounce API.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/ZeroBounce/ZeroBounce_Validate_Single_Email.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/ZeroBounce/ZeroBounce_Validate_Single_Email.ipynb", "imports": ["requests", "naas", "pprint.pprint"], "image_url": ""}, {"objectID": "9393d951ab135f69cd1aadae8c73b1974891c6586136f3e62aa631501ed53fab", "tool": "gTTS", "notebook": "Save Text to Speech to MP3", "action": "", "tags": ["#gTTS", "#texttospeech", "#mp3", "#python", "#library", "#audio"], "author": "Sriniketh Jayasendil", "author_url": "http://linkedin.com/in/sriniketh-jayasendil/", "updated_at": "2023-04-12", "created_at": "2023-03-02", "description": "This notebook will demonstrate how to use the gTTS library to save text to speech as an MP3 file.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/gTTS/gTTS_Save_Text_to_Speech_to_MP3.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/gTTS/gTTS_Save_Text_to_Speech_to_MP3.ipynb", "imports": ["gtts.gTTS", "gtts.gTTS"], "image_url": ""}, {"objectID": "b296fdda5aa3884bc9a78e50364dd2532992013a7fb54012c2d9751aa4a5b15f", "tool": "spaCy", "notebook": "SpaCy Build a sentiment analysis model using Twitter", "action": "", "tags": ["#twitter", "#spaCy", "#data", "#nlp", "#sentiment", "#classification"], "author": "Tannia Dubon", "author_url": "https://www.linkedin.com/in/tanniadubon/", "updated_at": "2023-04-12", "created_at": "2022-05-12", "description": "This notebook demonstrates how to use spaCy to build a sentiment analysis model using Twitter data.", "open_in_lab": "https://app.naas.ai/user-redirect/naas/downloader?url=https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/spaCy/SpaCy_Build_a_sentiment_analysis_model_using_Twitter.ipynb", "open_in_chat": "", "notebook_url": "https://github.com/jupyter-naas/awesome-notebooks/blob/master/spaCy/SpaCy_Build_a_sentiment_analysis_model_using_Twitter.ipynb", "imports": ["os", "requests", "pandas", "json", "ast", "yaml", "numpy", "datetime.datetime, date", "matplotlib.pyplot", "matplotlib", "wordcloud.WordCloud, STOPWORDS, ImageColorGenerator", "re", "seaborn", "string", "warnings", "random", "spacy", "spacy.training.Example", "spacy.pipeline.textcat.DEFAULT_SINGLE_TEXTCAT_MODEL", "spacy.matcher.PhraseMatcher", "pathlib.Path"], "image_url": ""}] \ No newline at end of file