pyspark.pandas.resample.Resampler.std#

Resampler.std()[source]#

Compute std of resampled values.

New in version 3.4.0.

See also

pyspark.pandas.Series.groupby
pyspark.pandas.DataFrame.groupby

Examples

>>> import numpy as np
>>> from datetime import datetime
>>> np.random.seed(22)
>>> dates = [
...    datetime(2022, 5, 1, 4, 5, 6),
...    datetime(2022, 5, 3),
...    datetime(2022, 5, 3, 23, 59, 59),
...    datetime(2022, 5, 4),
...    pd.NaT,
...    datetime(2022, 5, 4, 0, 0, 1),
...    datetime(2022, 5, 11),
... ]
>>> df = ps.DataFrame(
...    np.random.rand(len(dates), 2), index=pd.DatetimeIndex(dates), columns=["A", "B"]
... )
>>> df
                            A         B
2022-05-01 04:05:06  0.208461  0.481681
2022-05-03 00:00:00  0.420538  0.859182
2022-05-03 23:59:59  0.171162  0.338864
2022-05-04 00:00:00  0.270533  0.691041
NaT                  0.220405  0.811951
2022-05-04 00:00:01  0.010527  0.561204
2022-05-11 00:00:00  0.813726  0.745100
>>> df.resample("3D").std().sort_index()
                   A         B
2022-05-01  0.134509  0.268835
2022-05-04  0.183852  0.091809
2022-05-07       NaN       NaN
2022-05-10       NaN       NaN