pandas.core.resample.Resampler.ffill#
- final Resampler.ffill(limit=None)[source]#
Forward fill the values.
- Parameters:
- limitint, optional
Limit of how many values to fill.
- Returns:
- An upsampled Series.
See also
Series.fillna
Fill NA/NaN values using the specified method.
DataFrame.fillna
Fill NA/NaN values using the specified method.
Examples
Here we only create a
Series
.>>> ser = pd.Series([1, 2, 3, 4], index=pd.DatetimeIndex( ... ['2023-01-01', '2023-01-15', '2023-02-01', '2023-02-15'])) >>> ser 2023-01-01 1 2023-01-15 2 2023-02-01 3 2023-02-15 4 dtype: int64
Example for
ffill
with downsampling (we have fewer dates after resampling):>>> ser.resample('MS').ffill() 2023-01-01 1 2023-02-01 3 Freq: MS, dtype: int64
Example for
ffill
with upsampling (fill the new dates with the previous value):>>> ser.resample('W').ffill() 2023-01-01 1 2023-01-08 1 2023-01-15 2 2023-01-22 2 2023-01-29 2 2023-02-05 3 2023-02-12 3 2023-02-19 4 Freq: W-SUN, dtype: int64
With upsampling and limiting (only fill the first new date with the previous value):
>>> ser.resample('W').ffill(limit=1) 2023-01-01 1.0 2023-01-08 1.0 2023-01-15 2.0 2023-01-22 2.0 2023-01-29 NaN 2023-02-05 3.0 2023-02-12 NaN 2023-02-19 4.0 Freq: W-SUN, dtype: float64