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Financial statement

As explained in Investing for Programmers

A financial statement is a formal record of a company's financial condition and results, including revenues, expenses, assets, and liabilities.

A financial statement is a standardized dataset describing how a company performs and what it owns, owes, and generates in cash. Read it like source code: individual numbers need business and reporting context before they support an investment decision. section 1.5.1 section 2.1

Use the statements together rather than treating a single metric as conclusive:

  • Income statements organize revenue, expenses, profit, EBIT, and EBITDA across reporting periods. section 3.4.1
  • Balance sheets show assets, liabilities, and shareholders’ equity; their relationship is Assets = Liabilities + Shareholders’ equity. section 2.1.2
  • Cash-flow statements add evidence about solvency because reported positive balances do not guarantee that bills can be paid. section 2.1.2
  • Accounting standards such as GAAP and IFRS create a more consistent reporting baseline, but context remains necessary. section 2.1

Inspecting statements with Python

A yfinance Ticker exposes annual income_stmt, balance_sheet, and cash_flow DataFrames, with reporting dates as columns and metrics as rows. Select a period and calculate ratios such as profit margin, return on assets, or debt-to-equity. Compare companies by sector, since inventory, assets, and operating patterns differ substantially between businesses. section 3.4.1 section 2.2.1

Table 3.2 Microsoft’s income statement in a DataFrame
2024-06-30
2023-06-30
2022-06-30
2021-06-30
Tax effect of unusual items
-99918000.0
-2850000.0
43754000.0
180160797.164637
Tax rate for calcs
0.182
0.19
0.131
0.138266
Normalized EBITDA
133558000000.0
105155000000.0
99905000000.0
83031000000.0
Total unusual item
-549000000.0
-15000000.0
334000000.0
1303000000.0
Total unusual item excluding goodwill
-549000000.0
-15000000.0
334000000.0
1303000000.0
Net income from continuing operational net
88136000000.0
72361000000.0
72738000000.0
61271000000.0
Reconciled depreciation
22287000000.0
13861000000.0
14461000000.0
11686000000.0
Reconciled cost of revenue
74114000000.0
65863000000.0
62650000000.0
52232000000.0
EBITDA
133009000000.0
105140000000.0
100239000000.0
85134000000.0
EBIT
110722000000.0
91279000000.0
85779000000.0
73448000000.0
Source: yfinance

Use the Microsoft income-statement table to inspect multi-year rows such as EBITDA, EBIT, unusual items, and net income. section 3.4.1

How Investing for Programmers covers it

How deep it goes
Explains statement roles, accounting standards, solvency context, DataFrame access, and ratio formulas, but defers comprehensive accounting interpretation.
Examples
Demonstrates Microsoft statement DataFrames, multi-year EBITDA and EBIT rows, sector comparisons, and debt-to-equity calculations.
What it assumes
Assumes basic programming and investing interest, while introducing accounting statements, reporting standards, and interpretation from fundamentals.
What you can do after
Apply financial statements through yfinance and pandas to retrieve reports, inspect periods, calculate ratios, and compare companies cautiously.
How it connects
Connects financial statements with fundamental analysis, accounting standards, balance sheets, cash flow statements, financial ratios, and business models.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Investing for Programmers. The section links point to the parts of the book it draws on.