class finstmt.combined.statements.FinancialStatements(income_statements, balance_sheets, calculate=True, auto_adjust_config=True, _combinator=<finstmt.combined.combinator.FinancialStatementsCombinator object>)[source]¶

Bases: object

Main class that holds all the financial statements.

Parameters:: auto_adjust_config¶ (bool) – Whether to automatically adjust the configuration based on the loaded data. Currently will turn forecasting off for items not in the data, and turn forecasting on for items normally calculated off those which are not in the data. For example, if gross_ppe is missing then will start forecasting net_ppe instead

Examples:

>>> bs_path = r'WMT Balance Sheet.xlsx'
>>> inc_path = r'WMT Income Statement.xlsx'
>>> bs_df = pd.read_excel(bs_path)
>>> inc_df = pd.read_excel(inc_path)
>>> bs_data = BalanceSheets.from_df(bs_df)
>>> inc_data = IncomeStatements.from_df(inc_df)
>>> stmts = FinancialStatements(inc_data, bs_data)

__init__(income_statements, balance_sheets, calculate=True, auto_adjust_config=True, _combinator=<finstmt.combined.combinator.FinancialStatementsCombinator object>)¶

property all_config_items: List[ItemConfig]¶

auto_adjust_config: bool = True¶

balance_sheets: BalanceSheets¶

calculate: bool = True¶

property capex: Series¶

change(data_key)[source]¶

Get the change between this period and last for a data series

Parameters:: data_key¶ (str) – key of variable, how it would be accessed with FinancialStatements.data_key
Return type:: Series

copy(**updates)[source]¶

Return type:: Self

property dates: List[Timestamp]¶

property fcf: Series¶

forecast(**kwargs)[source]¶

Run a forecast, returning forecasted financial statements

Parameters:

kwargs¶ – Attributes of finstmt.forecast.config.ForecastConfig

Examples:

>>> stmts.forecast(periods=2)

Return type:

ForecastedFinancialStatements

property forecast_assumptions: DataFrame¶

income_statements: IncomeStatements¶

item_is_empty(data_key)[source]¶

Whether the passed item has no data

Parameters:: data_key¶ (str) – key of variable, how it would be accessed with FinancialStatements.data_key
Return type:: bool
Returns:

lag(data_key, num_lags)[source]¶

Get a data series lagged for a number of periods

Parameters:

data_key¶ (str) – key of variable, how it would be accessed with FinancialStatements.data_key
num_lags¶ (int) – Number of lags

Return type:

Series

property non_cash_expenses: Series¶