How to Download All NSE EOD Stock Data Using Python and YFinance

Introduction

For retail investors, traders, data scientists, and finance students, access to clean and structured historical stock data is invaluable.

While many APIs exist, few are as convenient and free as Yahoo Finance, especially when paired with Python’s powerful yfinance library.

In this article, I’ll walk you through how to:

1. Fetch all NSE-listed stocks’ End of Day (EOD) data
2. Use EQUITY_L.csv, an official list of NSE stocks
3. Download 20 years of data and save them to CSVs for local use

It is useful:

If you’re:

• A quant trying to backtest trading strategies
• A developer building financial dashboards
• A student working on a finance project
• Or just a curious investor…

Then automating the retrieval of 20 years of historical EOD data for all NSE stocks is a powerful capability.

Step 1: Download EQUITY_L.csv from NSE

Visit the official NSE website and download the full list of equity securities: https://www.nseindia.com/market-data/securities-available-for-trading

Look for a file named :

Securities available for Equity segment (.csv)

This file contains all actively listed equities on NSE, including their SYMBOLs, which are required by yfinance.

After downloading, save this file as EQUITY_L.csv in your project folder.

Step 2: Fetch EOD Data with yfinance

Install yfinance if you haven’t:

pip install yfinance

Then use the following Python script

import yfinance as yf
import pandas as pd
import os
# Create directory to store EOD files
os.makedirs("EOD", exist_ok=True)
# Load NSE equity symbols
equity_details = pd.read_csv("EQUITY_L.csv")
# Loop through each symbol
for name in equity_details.SYMBOL:
    try:
        print(f"Fetching {name}...")
        data = yf.download(f"{name}.NS", period="20y")
        if not data.empty:
            data.to_csv(f"./EOD/{name}.csv")
        else:
            print(f"No data for {name}")
    except Exception as e:
        print(f"{name} ===> {e}")

What’s Happening Behind the Scenes?

• We’re looping through every stock symbol in the EQUITY_L.csv file.
• .NS is appended to each symbol to match Yahoo Finance’s naming convention for NSE stocks.
• yf.download() fetches 20 years of daily OHLCV (Open, High, Low, Close, Volume) data.
• Each stock’s data is saved as a CSV file inside a local folder named EOD.

Folder Structure After Execution

project_folder/
│
├── EQUITY_L.csv
├── fetch_stocks.py
└── EOD/
    ├── INFY.csv
    ├── RELIANCE.csv
    ├── TCS.csv
    └── ...

What Can You Build Next?

• Backtest trading strategies with historical data
• Train ML models for stock forecasting
• Build dashboards in Streamlit or Dash
• Perform data cleaning and feature engineering

Conclusion

In just a few lines of Python, you’ve automated the collection of 20 years of EOD data for all NSE stocks. This project forms the foundation of many advanced financial applications, from algorithmic trading to AI-driven market analytics.

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