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Yfinance

As explained in Statistics Every Programmer Needs

yfinance is a Python library that retrieves market data from Yahoo Finance.

yfinance retrieves historical Yahoo Finance data directly from Python. Given a ticker symbol and date range, it can provide prices, trading volumes, dividends, and related data for financial analysis and time-series modeling. section 7.2.1

A typical retrieval workflow is:

  • Import yfinance using the yf alias. section 7.2.1
  • Identify the security with a ticker symbol such as AAPL. section 7.2.1
  • Create a Ticker object and call history with start, end, and interval parameters. section 7.2.1
  • Select the Close column and reset its index before further analysis. section 7.2.1

Fetch daily AAPL history

Define fetch_stock_data to retrieve AAPL history from 2023-10-01 through 2024-04-30, then retain only closing prices for analysis. section 7.2.1

>>> def fetch_stock_data(ticker_symbol, start_date, end_date, 
>>>                      interval = '1d'):
>>>     ticker_data = yf.Ticker(ticker_symbol)
>>> stock_data = ticker_data.history(start = start_date, 
                                 end = end_date, 
                                 interval = interval)
>>> return stock_data

Shows the reusable function that creates a ticker object and retrieves historical data with configurable dates and interval. section 7.2.1

How Statistics Every Programmer Needs covers it

How deep it goes
Demonstrates ticker-based retrieval and basic closing-price preparation, stopping before model validation or statistical interpretation.
Examples
Uses AAPL, a reusable fetch_stock_data function, daily history, and a Close-only DataFrame.
What it assumes
Assumes yfinance is installed and teaches ticker symbols through the AAPL example.
What you can do after
Build it from scratch by importing yfinance, fetching ticker history, and preparing closing-price data for analysis.
How it connects
Connects ticker symbols with pandas, visualization, financial analysis, and time-series modeling.

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This explainer was generated by Manning's knowledge graph from the text of Statistics Every Programmer Needs. The section links point to the parts of the book it draws on.