pandas.DataFrame.expanding#

DataFrame.expanding(min_periods=1,axis=<no_default>,method='single')[source]#

Provide expanding window calculations.

Parameters:

min_periodsint, default 1

Minimum number of observations in window required to have a value;otherwise, result isnp.nan.

axisint or str, default 0

If0 or'index', roll across the rows.

If1 or'columns', roll across the columns.

ForSeries this parameter is unused and defaults to 0.

methodstr {‘single’, ‘table’}, default ‘single’

Execute the rolling operation per single column or row ('single')or over the entire object ('table').

This argument is only implemented when specifyingengine='numba'in the method call.

Added in version 1.3.0.

Returns:

pandas.api.typing.Expanding

See also

rolling

Provides rolling window calculations.

ewm

Provides exponential weighted functions.

Notes

SeeWindowing Operations for further usage detailsand examples.

Examples

>>>df=pd.DataFrame({"B":[0,1,2,np.nan,4]})>>>df     B0  0.01  1.02  2.03  NaN4  4.0

min_periods

Expanding sum with 1 vs 3 observations needed to calculate a value.

>>>df.expanding(1).sum()     B0  0.01  1.02  3.03  3.04  7.0>>>df.expanding(3).sum()     B0  NaN1  NaN2  3.03  3.04  7.0