Stock Intelligence Dashboard

A mini financial data platform built with FastAPI, Pandas, and Chart.js. Tracks real NSE stock data for 10 Indian companies with ML price forecasting.

Features

• Real-time NSE stock data via yfinance
• Calculated metrics: Daily Return, 7D Moving Average, 52W High/Low, Volatility
• REST API with FastAPI
• Interactive dashboard with Chart.js
• 7-day ML price prediction using Linear Regression
• Dockerized for easy deployment

Tech Stack

Layer	Technology
Data	yfinance, Pandas, NumPy
Backend	FastAPI, Uvicorn
ML	Scikit-learn (Linear Regression)
Frontend	HTML, Chart.js
DevOps	Docker

API Endpoints

Method	Endpoint	Description
GET	/companies	List all tracked companies
GET	/data/{symbol}?days=30	Last N days of stock data
GET	/summary/{symbol}	52W high/low, avg, volatility
GET	/compare?symbol1=X&symbol2=Y	Normalized comparison + correlation
GET	/movers	Top 3 gainers and losers
GET	/predict/{symbol}	7-day ML price forecast

Setup & Run

Local

git init
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt
uvicorn app.main:app --reload

Docker

docker build -t stock-dashboard .
docker run -p 8000:8000 stock-dashboard

Project Structure

stock-dashboard/
├── app/
│   ├── main.py       # FastAPI routes
│   ├── data.py       # Data fetching & processing
│   └── ml.py         # ML prediction
├── static/
│   └── index.html    # Frontend dashboard
├── data/             # Cached CSV files
├── Dockerfile
├── requirements.txt
└── README.md

Tracked Companies

INFY, TCS, RELIANCE, HDFCBANK, WIPRO, ICICIBANK, HINDUNILVR, SBIN, BAJFINANCE, MARUTI