yfinance Data Skill

Fetches financial and market data from Yahoo Finance using the

yfinance

Python library.

Important

yfinance is not affiliated with Yahoo, Inc. Data is for research and educational purposes. Step 1: Ensure yfinance Is Available Before running any code, install yfinance if needed: import subprocess , sys subprocess . check_call ( [ sys . executable , "-m" , "pip" , "install" , "-q" , "yfinance" ] ) Always include this at the top of your script. Step 2: Identify What the User Needs Match the user's request to one or more data categories below, then use the corresponding code from references/api_reference.md . User Request Data Category Primary Method Stock price, quote Current price ticker.info or ticker.fast_info Price history, chart data Historical OHLCV ticker.history() or yf.download() Balance sheet Financial statements ticker.balance_sheet Income statement, revenue Financial statements ticker.income_stmt Cash flow Financial statements ticker.cashflow Dividends Corporate actions ticker.dividends Stock splits Corporate actions ticker.splits Options chain, calls, puts Options data ticker.option_chain() Earnings, EPS Analysis ticker.earnings_history Analyst price targets Analysis ticker.analyst_price_targets Recommendations, ratings Analysis ticker.recommendations Upgrades/downgrades Analysis ticker.upgrades_downgrades Institutional holders Ownership ticker.institutional_holders Insider transactions Ownership ticker.insider_transactions Company overview, sector General info ticker.info Compare multiple stocks Bulk download yf.download() Screen/filter stocks Screener yf.Screener + yf.EquityQuery Sector/industry data Market data yf.Sector / yf.Industry News News ticker.news Step 3: Write and Execute the Code General pattern import subprocess , sys subprocess . check_call ( [ sys . executable , "-m" , "pip" , "install" , "-q" , "yfinance" ] ) import yfinance as yf ticker = yf . Ticker ( "AAPL" )

... use the appropriate method from the reference

Key rules Always wrap in try/except — Yahoo Finance may rate-limit or return empty data Use yf.download() for multi-ticker comparisons — it's faster with multi-threading For options, list expiration dates first with ticker.options before calling ticker.option_chain(date) For quarterly data , use quarterly_ prefix: ticker.quarterly_income_stmt , ticker.quarterly_balance_sheet , ticker.quarterly_cashflow For large date ranges , be mindful of intraday limits — 1m data only goes back ~7 days, 1h data ~730 days Print DataFrames clearly — use .to_string() or .to_markdown() for readability, or select key columns Valid periods and intervals Periods 1d , 5d , 1mo , 3mo , 6mo , 1y , 2y , 5y , 10y , ytd , max Intervals 1m , 2m , 5m , 15m , 30m , 60m , 90m , 1h , 1d , 5d , 1wk , 1mo , 3mo Step 4: Present the Data After fetching data, present it clearly: Summarize key numbers in a brief text response (current price, market cap, P/E, etc.) Show tabular data formatted for readability — use markdown tables or formatted DataFrames Highlight notable items — earnings beats/misses, unusual volume, dividend changes Provide context — compare to sector averages, historical ranges, or analyst consensus when relevant If the user seems to want a chart or visualization, combine with an appropriate visualization approach (e.g., generate an HTML chart or describe the trend). Reference Files references/api_reference.md — Complete yfinance API reference with code examples for every data category Read the reference file when you need exact method signatures or edge case handling.