cudf.core.groupby.groupby.GroupBy.pipe#

GroupBy.pipe(func, *args, **kwargs)[source]#

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:

See also

cudf.Series.pipe: Apply a function with arguments to a series.
cudf.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