RUSSELL 1000 yfinance Dataset (Enriched)

Clean and ready-to-use dataset of RUSSELL 1000 equities, fully compatible with yfinance, enriched with market data and ICB classification.

Dataset

The file russell1000_full_enriched.csv contains the following columns:

• Ticker: base ticker
• Company: company name
• market_cap: market capitalization (when available)

GICS classification

• GICSSector: sector classification
• GICS Sub-Industry: detailed subsector classification

Usage

import pandas as pd
import yfinance as yf

df = pd.read_csv("russell1000_full_enriched.csv")

tickers = df["Ticker"].dropna().unique().tolist()

data = yf.download(tickers[:10], period="1y", interval="1d")

Use cases

Stock screening (by sector, industry, market cap, etc.) Factor research and quantitative analysis Backtesting strategies on Russell1000 equities Portfolio construction & diversification studies Financial data analysis in Python

Methodology

Scraped official Russell1000 listings Mapped tickers to Yahoo Finance format Validated tickers using yfinance price availability Enriched dataset with: Market capitalization GICS classification (industry → subsector) Company names and ISIN mapping

Notes

Some fields (notably market_cap) may be missing or partially outdated due to Yahoo Finance limitations All tickers are validated against live data availability in yfinance Dataset is focused on Russell1000 listings only

Requirements

Python 3.x pandas yfinance

pip install pandas yfinance

Disclaimer

This dataset is provided for informational and research purposes only. It does not constitute financial or investment advice.