Skip to main content
`Ctrl`+`K`

# pandas.api.typing.Resampler.sum

final Resampler.sum(numeric_only=False, min_count=0)

  Compute sum of group values.

  This method provides a simple way to compute the sum of values within each resampled group, particularly useful for aggregating time-based data into daily, monthly, or yearly sums.

  Parameters:
    numeric_only bool, default False

      Include only float, int, boolean columns.

      Changed in version 2.0.0: numeric_only no longer accepts `None`.

    min_count int, default 0

      The required number of valid values to perform the operation. If fewer than `min_count` non-NA values are present the result will be NA.

  Returns:
    Series or DataFrame

      Computed sum of values within each group.

  See also

  `core.resample.Resampler.mean`

    Compute mean of groups, excluding missing values.

  `core.resample.Resampler.count`

    Compute count of group, excluding missing values.

  `DataFrame.resample`

    Resample time-series data.

  `Series.sum`

    Return the sum of the values over the requested axis.

  Examples

      >>> 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
      >>> ser.resample("MS").sum()
      2023-01-01    3
      2023-02-01    7
      Freq: MS, dtype: int64