Yfinance Data

by himself6501fc7b4b34aeNo license3.3K starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 3 days ago

Fetch financial and market data with the yfinance Python library (Yahoo Finance). Use this skill whenever the user wants stock data: current quotes and price history, financial statements (income statement, balance sheet, cash flow), options chains, dividends and splits, earnings and analyst estimates, price targets and ratings, institutional and insider holdings, news, multi-ticker comparisons, stock screens, or sector and industry data. Use it even when the user gives only a ticker symbol (AAPL, MSFT, TSLA) and the intent has to be inferred. For earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, or ETF premium analysis, prefer the dedicated skill.

AI-generated overview

Fetches stock and market data from Yahoo Finance via the yfinance Python library and presents it.

What it does
Guides an agent through installing and using the yfinance Python library to pull financial and market data from Yahoo Finance. It maps user requests to data categories such as quotes, price history, financial statements, options chains, dividends and splits, earnings, analyst estimates, holdings, news, multi-ticker comparisons, screens, and sector or industry data. It then has the agent write and run code, handle rate limits and timezones, and present the numbers with supporting tables and context.
When to use it
Use when a user asks for stock or market data, including cases where only a ticker symbol is given and the intent must be inferred. It covers quotes, price history, statements, options, corporate actions, analyst and ownership data, news, comparisons, screens, and sector data. The skill notes that earnings previews or recaps, estimate revisions, valuation, correlation, liquidity, and ETF premium analysis are better served by a dedicated skill.
Requirements
Requires the yfinance Python library, installed via pip if missing, and Python 3 with network access to Yahoo Finance. It ships no scripts; it is instructions plus a reference file. Data is described as for research and educational purposes, and yfinance is noted as not affiliated with Yahoo.

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

Current environment status:

!`python3 -c "exec('try:\n import yfinance\n print(\'yfinance \' + yfinance.__version__ + \' installed\')\nexcept Exception:\n print(\'YFINANCE_NOT_INSTALLED\')')"`

If YFINANCE_NOT_INSTALLED, install it before running any code:

python
import subprocess, syssubprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance"])

If yfinance is already installed, skip the install step and proceed directly.


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 RequestData CategoryPrimary Method
Stock price, quoteCurrent priceticker.info or ticker.fast_info
Price history, chart dataHistorical OHLCVticker.history() or yf.download()
Balance sheetFinancial statementsticker.balance_sheet
Income statement, revenueFinancial statementsticker.income_stmt
Cash flowFinancial statementsticker.cashflow
DividendsCorporate actionsticker.dividends
Stock splitsCorporate actionsticker.splits
Options chain, calls, putsOptions dataticker.option_chain()
Earnings, EPSAnalysisticker.earnings_history
Analyst price targetsAnalysisticker.analyst_price_targets
Recommendations, ratingsAnalysisticker.recommendations
Upgrades/downgradesAnalysisticker.upgrades_downgrades
Institutional holdersOwnershipticker.institutional_holders
Insider transactionsOwnershipticker.insider_transactions
Company overview, sectorGeneral infoticker.info
Compare multiple stocksBulk downloadyf.download()
Screen/filter stocksScreeneryf.screen() + yf.EquityQuery
Sector/industry dataMarket datayf.Sector / yf.Industry
NewsNewsticker.news

Step 3: Write and Execute the Code

General pattern

python
import yfinance as yf
ticker = yf.Ticker("AAPL")# ... use the appropriate method from the reference

Key rules

  1. Always wrap in try/except — Yahoo Finance may rate-limit or return empty data
  2. Use yf.download() for multi-ticker comparisons — it's faster with multi-threading
  3. For options, list expiration dates first with ticker.options before calling ticker.option_chain(date)
  4. For quarterly data, use quarterly_ prefix: ticker.quarterly_income_stmt, ticker.quarterly_balance_sheet, ticker.quarterly_cashflow
  5. For large date ranges, be mindful of intraday limits — 1m data only goes back ~7 days, 1h data ~730 days
  6. Print DataFrames clearly — use .to_string() or .to_markdown() for readability, or select key columns
  7. Timezone handling — yfinance returns tz-aware datetime indices (e.g., America/New_York). When comparing dates, always use pd.Timestamp(..., tz=...) or strip timezones with .tz_localize(None). See the reference file for details.

Valid periods and intervals

Periods1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max
Intervals1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo

Step 4: Present the Data

Answer with the numbers the user asked for first, then the supporting table (markdown, or a trimmed DataFrame with the key columns). Call out anything notable in the data — an earnings beat or miss, unusual volume, a dividend change — and add context such as sector averages, historical ranges, or analyst consensus where it changes how the numbers read. If the user wants a chart, pair the data with a visualization.


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.

Source and attribution

Source:himself65/finance-skillsinplugins/market-analysis/skills/yfinance-dataat commit01fc7b4

License: No license

Content belongs to its original authors. SourceWeft indexes it from a public repository.

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