pandas.core.resample.Resampler.asfreq#

final Resampler.asfreq(fill_value=None)[source]#

Return the values at the new freq, essentially a reindex.

Parameters:

fill_valuescalar, optional: Value to use for missing values, applied during upsampling (note this does not fill NaNs that already were present).

Returns:

DataFrame or Series: Values at the specified freq.

See also

Series.asfreq: Convert TimeSeries to specified frequency.
DataFrame.asfreq: Convert TimeSeries to specified frequency.

Examples

>>> ser = pd.Series([1, 2, 3, 4], index=pd.DatetimeIndex(
...                 ['2023-01-01', '2023-01-31', '2023-02-01', '2023-02-28']))
>>> ser
2023-01-01    1
2023-01-31    2
2023-02-01    3
2023-02-28    4
dtype: int64
>>> ser.resample('MS').asfreq()
2023-01-01    1
2023-02-01    3
Freq: MS, dtype: int64