Core Guide
Financial Statements
Income statements, balance sheets, and cash flow statements — quarterly or annual — straight into DataFrames. No PDF parsing, no copy-paste from a browser tab.
The three statements
pythonstatements.py
from yahooquery import Ticker aapl = Ticker('aapl') aapl.income_statement() # revenue, expenses, net income... aapl.balance_sheet() # assets, liabilities, equity... aapl.cash_flow() # operating, investing, financing...
Quarterly vs. annual
Each method accepts a frequency argument:
pythonfrequency.py
aapl.income_statement(frequency='q') # quarterly (default) aapl.income_statement(frequency='a') # annual
What you get back
Statements return as DataFrames with line items as columns and reporting dates as rows — ready for ratio analysis or trend plots:
pythonanalyze.py
inc = aapl.income_statement(frequency='a') # revenue trend inc['TotalRevenue'].plot(kind='bar') # gross margin by year inc['GrossProfit'] / inc['TotalRevenue']
Related modules
| Property / Method | Contents |
|---|---|
| financial_data | Current margins, revenue growth, cash & debt snapshot |
| key_stats | Valuation ratios, share counts, short interest |
| earnings_history() | Past earnings dates with estimate vs. actual EPS |
| calendar_events | Upcoming earnings and dividend dates |
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