pandas.core.resample.Resampler.sem#

finalResampler.sem(ddof=1, numeric_only=False)[source] #

Compute standard error of the mean of groups, excluding missing values.

For multiple groupings, the result index will be a MultiIndex.

Parameters:

ddofint, default 1: Degrees of freedom.
numeric_onlybool, default False: Include only float, int or boolean data.

Added in version 1.5.0.

Changed in version 2.0.0: numeric_only now defaults to False.

Returns:

Series or DataFrame: Standard error of the mean of values within each group.

See also

DataFrame.sem: Return unbiased standard error of the mean over requested axis.
Series.sem: Return unbiased standard error of the mean over requested axis.

Examples

>>> ser = pd.Series(
...  [1, 3, 2, 4, 3, 8],
...  index=pd.DatetimeIndex(
...  [
...  "2023年01月01日",
...  "2023年01月10日",
...  "2023年01月15日",
...  "2023年02月01日",
...  "2023年02月10日",
...  "2023年02月15日",
...  ]
...  ),
... )
>>> ser.resample("MS").sem()
2023年01月01日 0.577350
2023年02月01日 1.527525
Freq: MS, dtype: float64

pandas.core.resample.Resampler.sem#

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