InfogennieAI - Data Analytics Platform

InfogennieAI is a powerful data analytics platform that helps users visualize and analyze their data through various interactive charts and graphs.

Features

Graph Generation

• Multiple Chart Types: Support for various chart types including:

  • Line Graph
  • Bar Chart
  • Pie Chart
  • Scatter Plot
  • Area Chart
  • Bubble Chart
  • Radar Chart
  • Polar Area Chart
  • Doughnut Chart

• Data Source Support:

  • CSV files
  • XLSX files
  • JSON files
  • Google Spreadsheet
  • Microsoft SQL

• Interactive Visualizations:

  • Responsive design
  • Zoom and pan capabilities
  • Interactive legends
  • Downloadable charts
  • Customizable layouts

Tech Stack

Frontend

• React.js
• Plotly.js for interactive charts
• Tailwind CSS for styling
• Papa Parse for CSV parsing
• XLSX for Excel file handling

Backend

• Django REST Framework
• Pandas for data manipulation
• Plotly Express for graph generation
• NumPy for numerical operations

Installation

Prerequisites

• Node.js (v14 or higher)
• Python (v3.8 or higher)
• pip (Python package manager)
• Git

Backend Setup

1. Navigate to the backend directory:

cd backend

2. Create and activate a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Run migrations:

python manage.py migrate

5. Start the backend server:

python manage.py runserver 8080

Frontend Setup

1. Navigate to the frontend directory:

cd frontend

2. Install dependencies:

npm install

3. Start the development server:

npm start

The application will be available at http://localhost:3000

Usage

1. Select Data Source:

   • Choose your data source type from the dropdown
   • Click "Choose File" to upload your data file

2. Select Chart Type:

   • Choose from various chart types in the dropdown menu
   • Each chart type is optimized for different kinds of data visualization

3. Generate Graph:

   • Click "Generate Graph" to create the visualization
   • The graph will automatically adjust based on your data

4. Interact with the Graph:

   • Zoom in/out using the mouse wheel or pinch gesture
   • Pan by clicking and dragging
   • Toggle data series using the legend
   • Download the graph as PNG using the camera icon

Data Format Requirements

• CSV/XLSX files should have headers
• Required columns for optimal visualization:
  • Date: Temporal data (YYYY-MM-DD format)
  • Sales: Numeric values
  • Quantity: Numeric values
  • Category: Categorical values
  • Other columns will be automatically detected and used where appropriate

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For support, please open an issue in the GitHub repository or contact the development team.