cudf.core.groupby.SeriesGroupBy.pipe

SeriesGroupBy.pipe(func, *args, **kwargs)

Apply a function func with arguments to this GroupBy object and return the function’s result.

Parameters:

funcfunction

Function to apply to this GroupBy object or, alternatively, a (callable, data_keyword) tuple where data_keyword is a string indicating the keyword of callable that expects the GroupBy object.

argsiterable, optional

Positional arguments passed into func.

kwargsmapping, optional

A dictionary of keyword arguments passed into func.

Returns:

objectthe return type of func.

See also

Series.pipe

Apply a function with arguments to a series.

DataFrame.pipe

Apply a function with arguments to a dataframe.

apply

Apply function to each group instead of to the full GroupBy object.

Examples

>>> import cudf
>>> df = cudf.DataFrame({'A': ['a', 'b', 'a', 'b'], 'B': [1, 2, 3, 4]})
>>> df
   A  B
0  a  1
1  b  2
2  a  3
3  b  4

To get the difference between each groups maximum and minimum value in one pass, you can do

>>> df.groupby('A', sort=True).pipe(lambda x: x.max() - x.min())
   B
A
a  2
b  2