pandas.core.groupby.SeriesGroupBy.bfill#
- SeriesGroupBy.bfill(limit=None)[源代码]#
向后填充值。
- Parameters:
- <strong>limit</strong>int, optional
要填充的最大值数量。
- Returns:
- Series 或 DataFrame
填充了缺失值。
参见
Series.bfill向后填充数据集中缺失的值。
DataFrame.bfill向后填充数据集中缺失的值。
Series.fillna填充 Series 的 NaN 值。
DataFrame.fillna填充 DataFrame 的 NaN 值。
Examples
对于 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
对于 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