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# pandas.api.typing.SeriesGroupBy.filter

SeriesGroupBy.filter(func, dropna=True, *args, **kwargs)

  Filter elements from groups that don’t satisfy a criterion.

  Elements from groups are filtered if they do not satisfy the boolean criterion specified by func.

  Parameters:
    func function

      Criterion to apply to each group. Should return True or False.

    dropna bool, optional

      Drop groups that do not pass the filter. True by default; if False, groups that evaluate False are filled with NaNs.

    *args tuple

      Optional positional arguments to pass to func.

    **kwargs dict

      Optional keyword arguments to pass to func.

  Returns:
    Series

      The filtered subset of the original Series.

  See also

  `Series.filter`

    Filter elements of ungrouped Series.

  `DataFrameGroupBy.filter`

    Filter elements from groups base on criterion.

  Notes

  Functions that mutate the passed object can produce unexpected behavior or errors and are not supported. See Mutating with User Defined Function (UDF) methods for more details.

  Examples

      >>> df = pd.DataFrame(
      ...     {
      ...         "A": ["foo", "bar", "foo", "bar", "foo", "bar"],
      ...         "B": [1, 2, 3, 4, 5, 6],
      ...         "C": [2.0, 5.0, 8.0, 1.0, 2.0, 9.0],
      ...     }
      ... )
      >>> grouped = df.groupby("A")
      >>> df.groupby("A").B.filter(lambda x: x.mean() > 3.0)
      1    2
      3    4
      5    6
      Name: B, dtype: int64