pandas.core.groupby.DataFrameGroupBy.last#
- DataFrameGroupBy.last(numeric_only=False, min_count=-1, skipna=True)[source]#
Compute the last entry of each column within each group.
Defaults to skipping NA elements.
- 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
valid values are present the result will be NA.- skipnabool, default True
Exclude NA/null values. If an entire row/column is NA, the result will be NA.
Added in version 2.2.1.
- Returns:
- Series or DataFrame
Last of values within each group.
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