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Data Visualization Tool

This is a versatile data visualization tool that allows users to generate various types of plots and graphs based on their input data. The tool provides a web interface for easy interaction and visualization.

Features

  • Upload a CSV file containing data.
  • Select the type of graph or plot to generate.
  • Generate visually appealing and informative data visualizations.
  • Download the generated plots for further use or sharing.

Technologies Used

  • Backend:

    • FastAPI: A modern, fast web framework for building APIs with Python.
    • Matplotlib: A popular Python plotting library for creating static, animated, and interactive visualizations.
    • Pandas: A powerful data manipulation and analysis library for Python.
  • Frontend:

    • HTML, CSS, JavaScript: For building a simple and user-friendly web interface.

Getting Started

  1. Clone the repository:

    git clone <repository-url>
    cd data-visualization-tool
  2. Install the required Python packages:

    pip install -r requirements.txt
  3. Run the FastAPI server:

    uvicorn main:app --reload
  4. Open the home.html in your browser to access the web interface.

Web app usage

  1. Upload a CSV file containing your data.
  2. Select the type of graph or plot you want to generate.
  3. Click on the "Generate Graph" button.
  4. View the generated plot on the page.
  5. Click on the "Download Graph" button to download the generated plot.

Command line usage

```bash
python3 graph_cmd.py --csv_file CSV_FILE --plot_type {line,bar,histogram,scatter,pie,box,heatmap} --title TITLE
```
  • CSV_FILE is the path to the csv file.
  • Select the type of plot from the list in the plot_type option.
  • TITLE is the title of the graph.

Deployment

To deploy this data visualization tool, you can follow these general steps:

  1. Choose a hosting service (e.g., AWS, Heroku, or your preferred provider).
  2. Set up the necessary environment variables for your deployment environment.
  3. Deploy the FastAPI application.

For detailed deployment instructions, refer to the documentation of your chosen hosting service.

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