pandas.DataFrame.expanding#
- DataFrame.expanding(min_periods=1, axis=0, 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.New in version 1.3.0.
- Returns
Expanding
subclass
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