pandas.core.groupby.DataFrameGroupBy.filter

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

Return a copy of a DataFrame excluding elements from groups that do not satisfy the boolean criterion specified by func.

Parameters:	f : function Function to apply to each subframe. Should return True or False. dropna : Drop groups that do not pass the filter. True by default; if False, groups that evaluate False are filled with NaNs.
Returns:	filtered : DataFrame

Notes

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

Examples

>>> import pandas as pd
>>> df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
...                           'foo', 'bar'],
...                    'B' : [1, 2, 3, 4, 5, 6],
...                    'C' : [2.0, 5., 8., 1., 2., 9.]})
>>> grouped = df.groupby('A')
>>> grouped.filter(lambda x: x['B'].mean() > 3.)
     A  B    C
1  bar  2  5.0
3  bar  4  1.0
5  bar  6  9.0