modin.pandas.Resampler.bfill

Resampler.bfill(limit: Optional[int] = None)[source]

Backward fill the new missing values in the resampled data.

Parameters:

limit (int, optional) – This parameter is not supported and will raise NotImplementedError.

Returns:

An upsampled Series or DataFrame with backward filled NaN values.

Return type:

Series or DataFrame

Examples

>>> s = pd.Series([1, 2, 3],
... index=pd.date_range('20180101', periods=3, freq='h'))
>>> s
2018-01-01 00:00:00    1
2018-01-01 01:00:00    2
2018-01-01 02:00:00    3
Freq: None, dtype: int64
>>> s.resample('30min').bfill()
2018-01-01 00:00:00    1
2018-01-01 00:30:00    2
2018-01-01 01:00:00    2
2018-01-01 01:30:00    3
2018-01-01 02:00:00    3
Freq: None, dtype: int64
>>> df = pd.DataFrame({'a': [2, np.nan, 6], 'b': [1, 3, 5]},
...      index=pd.date_range('20180101', periods=3,
...      freq='h'))
>>> df
                       a  b
2018-01-01 00:00:00  2.0  1
2018-01-01 01:00:00  NaN  3
2018-01-01 02:00:00  6.0  5
>>> df.resample('30min').bfill()
                       a  b
2018-01-01 00:00:00  2.0  1
2018-01-01 00:30:00  NaN  3
2018-01-01 01:00:00  NaN  3
2018-01-01 01:30:00  6.0  5
2018-01-01 02:00:00  6.0  5
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