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DataFrame.expanding(min_periods=1, freq=None, center=False, axis=0)
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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
Returns: a Window sub-classed for the particular operation
Notes
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 ofresample()
(i.e. using themean
).Examples
>>> 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
DataFrame.expanding()
2017-01-12 04:45:48
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