Series.expanding(min_periods=1, freq=None, center=False, axis=0)
[source]
Provides expanding transformations.
New in version 0.18.0.
Parameters: |
min_periods : int, default None Minimum number of observations in window required to have a value (otherwise result is NA). freq : string or DateOffset object, optional (default None) (DEPRECATED) Frequency to conform the data to before computing the statistic. Specified as a frequency string or DateOffset object. center : boolean, default False Set the labels at the center of the window. axis : int or string, default 0 |
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Returns: |
a Window sub-classed for the particular operation |
By default, the result is set to the right edge of the window. This can be changed to the center of the window by setting center=True
.
The freq
keyword is used to conform time series data to a specified frequency by resampling the data. This is done with the default parameters of resample()
(i.e. using the mean
).
>>> df = DataFrame({'B': [0, 1, 2, np.nan, 4]}) B 0 0.0 1 1.0 2 2.0 3 NaN 4 4.0
>>> df.expanding(2).sum() B 0 NaN 1 1.0 2 3.0 3 3.0 4 7.0
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Licensed under the 3-clause BSD License.
http://pandas.pydata.org/pandas-docs/version/0.19.2/generated/pandas.Series.expanding.html