pandas.core.groupby.SeriesGroupBy.bfill — pandas 3.0.0.dev0+2097.gcdc5b7418e documentation (original) (raw)

SeriesGroupBy.bfill(limit=None)[source]#

Backward fill the values.

Parameters:

limitint, optional

Limit of how many values to fill.

Returns:

Series or DataFrame

Object with missing values filled.

See also

Series.bfill

Backward fill the missing values in the dataset.

DataFrame.bfill

Backward fill the missing values in the dataset.

Series.fillna

Fill NaN values of a Series.

DataFrame.fillna

Fill NaN values of a DataFrame.

Examples

With Series:

index = ["Falcon", "Falcon", "Parrot", "Parrot", "Parrot"] s = pd.Series([None, 1, None, None, 3], index=index) s Falcon NaN Falcon 1.0 Parrot NaN Parrot NaN Parrot 3.0 dtype: float64 s.groupby(level=0).bfill() Falcon 1.0 Falcon 1.0 Parrot 3.0 Parrot 3.0 Parrot 3.0 dtype: float64 s.groupby(level=0).bfill(limit=1) Falcon 1.0 Falcon 1.0 Parrot NaN Parrot 3.0 Parrot 3.0 dtype: float64

With DataFrame:

df = pd.DataFrame( ... {"A": [1, None, None, None, 4], "B": [None, None, 5, None, 7]}, ... index=index, ... ) df A B Falcon 1.0 NaN Falcon NaN NaN Parrot NaN 5.0 Parrot NaN NaN Parrot 4.0 7.0 df.groupby(level=0).bfill() A B Falcon 1.0 NaN Falcon NaN NaN Parrot 4.0 5.0 Parrot 4.0 7.0 Parrot 4.0 7.0 df.groupby(level=0).bfill(limit=1) A B Falcon 1.0 NaN Falcon NaN NaN Parrot NaN 5.0 Parrot 4.0 7.0 Parrot 4.0 7.0