xorbits.pandas.groupby.SeriesGroupBy.bfill#
- SeriesGroupBy.bfill(limit=None)#
Backward fill the values.
- Parameters
limit (int, optional) – Limit of how many values to fill.
- Returns
Object with missing values filled.
- Return type
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
This docstring was copied from pandas.core.groupby.generic.SeriesGroupBy.