dask.dataframe.api.SeriesGroupBy.last

SeriesGroupBy.last(numeric_only=False, sort=None, **kwargs)

Compute the last entry of each column within each group.

This docstring was copied from pandas.core.groupby.groupby.GroupBy.last.

Some inconsistencies with the Dask version may exist.

NA values are skipped by default, so the result is the last non-NA value per column — which may differ from the last row of the group. Pass skipna=False to keep NAs.

Parameters:

numeric_onlybool, default False

Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data.

min_countint, default -1 (Not supported in Dask)

The required number of valid values to perform the operation. If fewer than min_count valid values are present the result will be NA.

skipnabool, default True (Not supported in Dask)

Exclude NA values. If an entire group is NA, the result will be NA.

Added in version 2.2.1.

Returns:

Series or DataFrame

Last values within each group.

See also

DataFrame.groupby

Apply a function groupby to each row or column of a DataFrame.

api.typing.DataFrameGroupBy.first

Compute the first entry of each column within each group.

api.typing.DataFrameGroupBy.nth

Take the nth row from each group.

Examples

>>> df = pd.DataFrame(dict(A=[1, 1, 3], B=[5, None, 6], C=[1, 2, 3]))
>>> df.groupby("A").last()
     B  C
A
1  5.0  2
3  6.0  3