VisualizeCSV

Run Web Application with CSV 🔥

Table Of Contents

• About the Project
• Built With
• Getting Started
  • Prerequisites
  • Installation
  • Usage
  • Docker
  • DemoCSVChange
• Features
• License
• Authors
• Acknowledgements
• RenderDeployment

About The Project

Built With

Visualize CSV with Python Code using Pandas, Pygwalker and Streamlit.

Getting Started

These instructions will help you set up and run the project on your local machine.

Prerequisites

• Python 3.10
• Pandas 2.1.3
• Streamlit 1.28.2
• Pygwalker 0.3.16

Installation

1. Clone the repo

git clone https://github.com/6abc/VisualizeCSV.git
cd VisualizeCSV

2.1 Create a virtual environment [Unix](optional but recommended):

python -m venv venv
source venv/bin/activate

2.2 Create a virtual environment [Windows](optional but recommended):

python -m venv venv
.\venv\Scripts\activate

3. Install project dependencies:

pip install -r requirements.txt

Usage

1. 🔥Start the Application server:

streamlit run main.py

2. Open a web browser and navigate to http://127.0.0.1:8501/ to access the Web page.
3. 💧Stop the Application server by Pressing Ctrl+C.

Docker

1. Create folder name as data and add csv file named as source.csv and copy path of folder

mkdir data

2. Use data path here

docker run -d -p 8501:8501 -v /path/to/your/data:/app/data paulisgood/visualizecsv:latest

Example :

docker run -d -p 8501:8501 -v /home/ash/data:/app/data paulisgood/visualizecsv:latest

DemoCSVChange

Demo.mp4

Features

• Can Visualize CSV data without Excel and complex table function.
• Can work on complex data types as well.
• Pandas, Streamlit and Pygwalker which is usefull for Data Scientist.
• Simple UI, No code required.

License

Distributed under the MIT License. See LICENSE for more information.

Authors

• Ashish Thakur - Senior Command Center Analyst - Ashish Thakur

Acknowledgements

• Inspired by Pygwalker
• Inspired by Pandas
• Inspired by Streamlit
• Inspired by ReadME-Generator

RenderDeployment

Visitors :