yf-data

A small Python client that returns normalized Yahoo Finance data as Pandas DataFrames.

Features

Available data include:

• OHLC values for stocks and exchange rates
• dividends
• company financial data from income and balance sheets

All results are returned as Pandas DataFrames.

Temporal values follow their domain semantics:

The public API does not return naive datetimes.

Usage

from yfdata import YahooProvider

yp = YahooProvider()

# Frequency for prices and exchange rates can be daily ("1D") or 1-minute ("1m").

# Get daily OHLC data.
df = yp.get_prices(["aapl"], "1D")

# Get exchange rates with frequency of 1 minute.
df = yp.get_rates("usd", "eur", freq="1m")

# Get company dividends.
df = yp.get_dividends(["aapl", "msft"])

# Income frequency can be annual ("A"), quarterly ("Q"), or
# trailing twelve months ("TTM").

# Balance-sheet frequency can be annual ("A") or quarterly ("Q").

# Get annual income data.
df = yp.get_income(["aapl", "msft"], freq="A")

# Get quarterly balance data.
df = yp.get_balance(["aapl", "msft"], freq="Q")

# Define a list of specific metrics for income data.
metrics = ["total_revenue", "ebitda"]
df = yp.get_income(["aapl", "msft"], freq="A", metrics=metrics)

Output examples

An excerpt from 1-minute OHLC price data:

An excerpt from annual balance data:

Financial metrics

Available metrics for the income statement are:

• total_revenue
• cost_of_revenue
• gross_profit
• operating_expense
• operating_income
• non_operating_interest_income_expense
• other_income_expense
• basic_eps
• diluted_eps
• basic_average_shares
• total_expense
• normalized_income
• ebit
• ebitda

Available metrics for balance sheet are:

• total_assets
• total_liabilities_net_minority_interest
• total_equity_gross_minority_interest
• total_capitalization
• common_stock_equity
• capital_lease_obligations
• net_tangible_assets
• working_capital
• invested_capital
• tangible_book_value
• total_debt
• net_debt
• share_issued
• ordinary_shares_number