pandas.rolling_window¶
-
pandas.
rolling_window
(arg, window=None, win_type=None, min_periods=None, freq=None, center=False, mean=True, axis=0, how=None, **kwargs)¶ Applies a moving window of type
window_type
and sizewindow
on the data.Parameters: arg : Series, DataFrame
window : int or ndarray
Weighting window specification. If the window is an integer, then it is treated as the window length and win_type is required
win_type : str, default None
Window type (see Notes)
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)
Frequency to conform the data to before computing the statistic. Specified as a frequency string or DateOffset object.
center : boolean, default False
Whether the label should correspond with center of window
mean : boolean, default True
If True computes weighted mean, else weighted sum
axis : {0, 1}, default 0
how : string, default ‘mean’
Method for down- or re-sampling
Returns: y : type of input argument
Notes
The recognized window types are:
boxcar
triang
blackman
hamming
bartlett
parzen
bohman
blackmanharris
nuttall
barthann
kaiser
(needs beta)gaussian
(needs std)general_gaussian
(needs power, width)slepian
(needs width).
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).