pandas.core.groupby.SeriesGroupBy.filter#

SeriesGroupBy.filter(func, dropna=True, *args, **kwargs)[source]#

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