pandas.core.groupby.SeriesGroupBy.last#

SeriesGroupBy.last(numeric_only=False, min_count=-1)[source]#

Compute the last non-null entry of each column.

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

Returns:

See also

DataFrame.groupby: Apply a function groupby to each row or column of a DataFrame.
pandas.core.groupby.DataFrameGroupBy.first: Compute the first non-null entry of each column.
pandas.core.groupby.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