dask.dataframe.tseries.resample.Resampler.sum

Contents

dask.dataframe.tseries.resample.Resampler.sum#

Resampler.sum()[source]#

Compute sum of group values.

This docstring was copied from pandas.api.typing.Resampler.sum.

Some inconsistencies with the Dask version may exist.

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 (Not supported in Dask)

Include only float, int, boolean columns.

Changed in version 2.0.0: numeric_only no longer accepts None.

min_countint, default 0 (Not supported in Dask)

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
Contents