Skip to main content
`Ctrl`+`K`

# pandas.api.typing.Resampler.asfreq

final Resampler.asfreq(fill_value=None)

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

  This method selects data at the specified frequency without aggregation, useful for upsampling to a higher frequency or selecting specific time points.

  Parameters:
    fill_value scalar, 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