pandas.core.groupby.DataFrameGroupBy.filter

DataFrameGroupBy.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

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

*argstuple

Additional positional arguments to pass to func.

**kwargsdict

Additional keyword arguments to pass to func.

Returns:

DataFrame

The filtered subset of the original DataFrame.

See also

DataFrame.filter

Filter elements of ungrouped DataFrame.

SeriesGroupBy.filter

Filter elements from groups base on criterion.

Notes

Each subframe is endowed the attribute ‘name’ in case you need to know which group you are working on.

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")
>>> grouped.filter(lambda x: x["B"].mean() > 3.0)
     A  B    C
1  bar  2  5.0
3  bar  4  1.0
5  bar  6  9.0