# pandas.core.groupby.GroupBy.pipe

`GroupBy.``pipe`(func, *args, **kwargs)

  Apply a function with arguments to this GroupBy object,

  New in version 0.21.0.

  Parameters:

  func : callable or tuple of (callable, string)

  > 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.

  args : iterable, optional

  > positional arguments passed into `func`.

  kwargs : dict, optional

  > a dictionary of keyword arguments passed into `func`.

  Returns: | object : the return type of `func`.

  See also

  `pandas.Series.pipe`
    Apply a function with arguments to a series
  `pandas.DataFrame.pipe`
    Apply a function with arguments to a dataframe
  `apply`
    Apply function to each group instead of to the full GroupBy object.

  Notes

  Use `.pipe` when chaining together functions that expect Series, DataFrames or GroupBy objects. Instead of writing

      >>> f(g(h(df.groupby('group')), arg1=a), arg2=b, arg3=c)

  You can write

      >>> (df
      ...    .groupby('group')
      ...    .pipe(f, arg1)
      ...    .pipe(g, arg2)
      ...    .pipe(h, arg3))

  See more here

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