DataFrame.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 since version 0.18.0: 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 |
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/0.22.0/generated/pandas.DataFrame.expanding.html