Run notebooks to show output

03_reading_files.ipynb

@@ -36,11 +36,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "EGU 2017: Data analysis with Python and Jupyter\n",
+      "Preparation\n",
+      "Material\n",
+      "Downloading the material\n",
+      "License\n"
+     ]
+    }
+   ],
    "source": [
     "with open('README.md', mode='r') as fid:\n",
     "    for line in fid:\n",
@@ -71,11 +81,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "EGU 2017: Data analysis with Python and Jupyter\n",
+      "Preparation\n",
+      "Material\n",
+      "Downloading the material\n",
+      "License\n"
+     ]
+    }
+   ],
    "source": [
     "with open('README.md', mode='r') as fid:\n",
     "    lines = fid.readlines()\n",
@@ -95,11 +115,84 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['# EGU 2017: Data analysis with Python and Jupyter\\n',\n",
+       " '\\n',\n",
+       " 'During the [EGU 2017](http://egu2017.eu) we presented a short course introducing\\n',\n",
+       " 'how to do data science with Python and Jupyter. This is the material used in the\\n',\n",
+       " 'course. The course itself was 90 minutes. However, there is a bit more material\\n',\n",
+       " 'that can also be used for self-study and for finding references that go more\\n',\n",
+       " 'in-depth.\\n',\n",
+       " '\\n',\n",
+       " '## Preparation\\n',\n",
+       " '\\n',\n",
+       " '[Install Anaconda](https://www.continuum.io/downloads), Python 3.x\\n',\n",
+       " 'version. Anaconda is an open data science platform which includes Python and\\n',\n",
+       " 'most packages necessary for doing data science. Anaconda can be installed even\\n',\n",
+       " 'without root/administrator privileges.\\n',\n",
+       " '\\n',\n",
+       " '## Material\\n',\n",
+       " '\\n',\n",
+       " 'The course is made available as a series of Jupyter Notebooks. The notebooks can\\n',\n",
+       " 'be read directly here at Github, but you will have a better, more interactive\\n',\n",
+       " 'experience by downloading them and running the locally. How to do this is\\n',\n",
+       " 'explained [below](#downloading-the-material).\\n',\n",
+       " '\\n',\n",
+       " 'This short course is not a course in Python, the programming language. Instead\\n',\n",
+       " 'we aim to show you how Python has become a full-blown platform for doing data\\n',\n",
+       " 'science.\\n',\n",
+       " '\\n',\n",
+       " 'The following short lessons are available:\\n',\n",
+       " '\\n',\n",
+       " '+ [Anaconda](01_anaconda.ipynb)\\n',\n",
+       " '+ [Jupyter Notebooks](02_jupyter_notebooks.ipynb)\\n',\n",
+       " '+ [Reading files](03_reading_files.ipynb)\\n',\n",
+       " '+ [Working with JSON-data](04_working_with_json.ipynb)\\n',\n",
+       " '+ [Numerical data in numpy](05_numerical_data_in_numpy.ipynb)\\n',\n",
+       " '+ [Pandas and time series](06_pandas_and_time_series.ipynb)\\n',\n",
+       " '+ [Plotting data](07_plotting_data.ipynb)\\n',\n",
+       " '+ [Storing data](08_storing_data.ipynb)\\n',\n",
+       " '+ [Distributing Jupyter notebooks](09_distributing_jupyter_notebooks.ipynb)\\n',\n",
+       " '+ [Further resources](10_further_resources.ipynb)\\n',\n",
+       " '\\n',\n",
+       " '## Downloading the material\\n',\n",
+       " '\\n',\n",
+       " 'The notebooks can be downloaded from this github-page, by scrolling to the top,\\n',\n",
+       " 'click the green `Clone or download`-button and then clicking the `Download ZIP`\\n',\n",
+       " 'link.\\n',\n",
+       " '\\n',\n",
+       " 'After downloading the zip-file, unpack it on your computer. Then open a terminal\\n',\n",
+       " '(on Windows you should open a Anaconda terminal) and type\\n',\n",
+       " '\\n',\n",
+       " '    jupyter notebook\\n',\n",
+       " ' \\n',\n",
+       " 'This will start a local webserver, so the terminal will print some messages to\\n',\n",
+       " 'that effect. You do not need to worry about these message. Furthermore, your\\n',\n",
+       " 'default web browser will open up with a new window showing a file browser. You\\n',\n",
+       " 'can then navigate to the folder you just downloaded, and click on any of the\\n',\n",
+       " 'files to see the content.\\n',\n",
+       " '\\n',\n",
+       " '## License\\n',\n",
+       " '\\n',\n",
+       " '[![Creative Commons License](https://i.creativecommons.org/l/by-sa/4.0/80x15.png)](http://creativecommons.org/licenses/by-sa/4.0/)\\n',\n",
+       " 'This work is licensed under a\\n',\n",
+       " '[Creative Commons Attribution-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-sa/4.0/).\\n',\n",
+       " '\\n',\n",
+       " 'If you want to reuse this material, feel free to [fork](#fork-destination-box) it. If you find any\\n',\n",
+       " 'errors or have suggestions for improvements raising an [issue](../../issues/) or sending a\\n',\n",
+       " '[pull request](../../pulls/) would be very welcome. Thank you for your interest.\\n']"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "lines"
    ]
@@ -115,11 +208,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": false
-   },
-   "outputs": [],
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['EGU 2017: Data analysis with Python and Jupyter',\n",
+       " 'Preparation',\n",
+       " 'Material',\n",
+       " 'Downloading the material',\n",
+       " 'License']"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "headlines"
    ]
@@ -169,7 +275,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.5.3"
+   "version": "3.6.2"
   }
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