pandas.Series.expanding#

Series.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 is np.nan.

axisint or str, default 0

If 0 or 'index', roll across the rows.

If 1 or 'columns', roll across the columns.

For Series 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 specifying engine='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

See Windowing Operations for further usage details and examples.

Examples

>>> df = pd.DataFrame({"B": [0, 1, 2, np.nan, 4]})
>>> df
     B
0  0.0
1  1.0
2  2.0
3  NaN
4  4.0

min_periods

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

>>> df.expanding(1).sum()
     B
0  0.0
1  1.0
2  3.0
3  3.0
4  7.0
>>> df.expanding(3).sum()
     B
0  NaN
1  NaN
2  3.0
3  3.0
4  7.0