pandas.core.groupby.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:

funcfunction

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

dropnabool, optional

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

*argstuple

Optional positional arguments to pass to func.

**kwargsdict

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