pandas.core.resample.Resampler.sum#

finalResampler.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年01月01日", "2023年01月15日", "2023年02月01日", "2023年02月15日"]
...  ),
... )
>>> ser
2023年01月01日 1
2023年01月15日 2
2023年02月01日 3
2023年02月15日 4
dtype: int64
>>> ser.resample("MS").sum()
2023年01月01日 3
2023年02月01日 7
Freq: MS, dtype: int64

pandas.core.resample.Resampler.sum#

This Page