Statistical Data Visualization Platform

Overview

This project is a web application that allows users to upload CSV or Excel files, which are then processed on the server-side using Python Flask. The processed data is visualized and displayed to the user. The front end is built using Next.js and Node.js.

File Structure

project-root/
│
├── client/ # Frontend directory
│ ├── pages/ # Next.js pages
│ ├── public/ # Public static files
│ ├── styles/ # CSS styles
│ ├── components/ # React components
│ └── .gitignore # Git ignore file
│ └── package.json # Node.js dependencies and scripts
│
├── server/ # Backend directory
│ ├── app.py # Flask application
│ ├── api # API folder
│ ├── requirements.txt # Python dependencies
│
└── .gitignore # Git ignore file

Setup Instructions

Frontend Setup

Navigate to the Client Directory**:

cd client

Install Dependencies:

Ensure you have Node.js v18.17.0 or later installed. Run:

npm install

Run the Development Server:

npm run dev

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

Backend Setup

Navigate to the Server Directory:

cd server

Set Up a Virtual Environment (optional but recommended)::

Ensure you have Python 3.8 or later installed. Run:

python -m venv venv
source venv/bin/activate

Install Dependencies:

pip install -r requirements.txt

Run the Flask Application:

python app.py

The Flask application will be available at http://localhost:5000.

Project Description

Frontend:

•	The frontend is built with Next.js and is responsible for providing a user interface where users can upload CSV or Excel files.
•	Upon file upload, the frontend sends a POST request to the backend with the file.

Backend:

•	The backend is built with Flask and processes the uploaded files.
•	It reads the file, performs data analysis, and generates visualizations (Curve Plot, Boxplot, Moments, and Heatmap).
•	The visualizations are returned as images to the frontend.

Visualizations:

•	Curve Plot: Shows a line plot for the first numeric column.
•	Boxplot: Displays the distribution of data through boxplots for numeric columns.
•	Moments Plot: Visualizes statistical moments including mean, variance, skewness, and kurtosis.
•	Heatmap: Shows the correlation matrix of numeric columns.