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)
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: 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') import pandas as pd import numpy as np nifty = yf