Yahoo Finance Nifty Historical Data !!exclusive!! May 2026

print(nifty[['Adj Close', 'volatility']].tail())

This method gives you – though note: volume for an index is usually the total traded volume of its constituents. Decoding the Columns: What You're Actually Getting When you download the data, you'll see six columns. Here's what they mean for Nifty:

For decades, the Nifty 50 has been the heartbeat of the Indian equity market. Whether you're backtesting a trading strategy, calculating beta against the broader market, or simply tracking long-term wealth creation, reliable historical data is non-negotiable. yahoo finance nifty historical data

import yfinance as yf nifty = yf.download('^NSEI', start='2010-01-01', end='2023-12-31') View the first 5 rows print(nifty.head()) Save to CSV nifty.to_csv('nifty_historical.csv')

While platforms like Bloomberg Terminal and Reuters are gold standards, they come with a hefty price tag. Enter – a surprisingly powerful, free, and widely accessible source for Nifty historical data. print(nifty[['Adj Close', 'volatility']]

By [Your Name/Staff Writer]

import pandas as pd import numpy as np nifty = yf.download('^NSEI', period='1y') nifty['returns'] = nifty['Adj Close'].pct_change() nifty['volatility'] = nifty['returns'].rolling(30).std() * np.sqrt(252) By [Your Name/Staff Writer] import pandas as pd

Download ^NSEI data from 1995 to today. Plot the log-scale chart. You'll see India's growth story in a single graph – and you didn't pay a rupee for it. Disclaimer: This article is for educational purposes. Always verify critical data from official sources before making investment decisions.