pandas.api.typing.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_countnon-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.meanCompute mean of groups, excluding missing values.
core.resample.Resampler.countCompute count of group, excluding missing values.
DataFrame.resampleResample time-series data.
Series.sumReturn 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