pandas.core.groupby.DataFrameGroupBy.expanding#

DataFrameGroupBy.expanding(min_periods=1, method='single')[source]#

Return an expanding grouper, providing expanding functionality per group.

Parameters:

min_periodsint, default 1

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

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

Execute the expanding 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.

Returns:

pandas.api.typing.ExpandingGroupby

An object that supports expanding transformations over each group.

See also

Series.expanding

Expanding transformations for Series.

DataFrame.expanding

Expanding transformations for DataFrames.

Series.groupby

Apply a function groupby to a Series.

DataFrame.groupby

Apply a function groupby.

Examples

>>> df = pd.DataFrame(
...     {
...         "Class": ["A", "A", "A", "B", "B", "B"],
...         "Value": [10, 20, 30, 40, 50, 60],
...     }
... )
>>> df
Class  Value
0     A     10
1     A     20
2     A     30
3     B     40
4     B     50
5     B     60

>>> df.groupby("Class").expanding().mean()
        Value
Class
A     0   10.0
      1   15.0
      2   20.0
B     3   40.0
      4   45.0
      5   50.0