pandas.core.resample.Resampler.sum#

final Resampler.sum(numeric_only=False, min_count=0)[source]#

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_onlybool, default False: Include only float, int, boolean columns.

Changed in version 2.0.0: numeric_only no longer accepts None.
min_countint, 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