# xarray.core.rolling.DatasetRolling¶

class xarray.core.rolling.DatasetRolling(obj, min_periods=None, center=False, **windows)
__init__(obj, min_periods=None, center=False, **windows)

Moving window object for Dataset. You should use Dataset.rolling() method to construct this object instead of the class constructor.

Parameters: obj : Dataset Object to window. min_periods : int, default None Minimum number of observations in window required to have a value (otherwise result is NA). The default, None, is equivalent to setting min_periods equal to the size of the window. center : boolean, default False Set the labels at the center of the window. **windows : dim=window dim : str Name of the dimension to create the rolling iterator along (e.g., time). window : int Size of the moving window. rolling : type of input argument

Dataset.rolling, DataArray.rolling, Dataset.groupby, DataArray.groupby
 __init__(obj[, min_periods, center]) Moving window object for Dataset. argmax(**kwargs) Reduce this Dataset’s data windows by applying argmax along its dimension. argmin(**kwargs) Reduce this Dataset’s data windows by applying argmin along its dimension. construct(window_dim[, stride, fill_value]) Convert this rolling object to xr. count() Reduce this Dataset’s data windows by applying count along its dimension. max(**kwargs) Reduce this Dataset’s data windows by applying max along its dimension. mean(**kwargs) Reduce this Dataset’s data windows by applying mean along its dimension. median(**kwargs) Reduce this Dataset’s data windows by applying median along its dimension. min(**kwargs) Reduce this Dataset’s data windows by applying min along its dimension. prod(**kwargs) Reduce this Dataset’s data windows by applying prod along its dimension. reduce(func, **kwargs) Reduce the items in this group by applying func along some dimension(s). std(**kwargs) Reduce this Dataset’s data windows by applying std along its dimension. sum(**kwargs) Reduce this Dataset’s data windows by applying sum along its dimension. var(**kwargs) Reduce this Dataset’s data windows by applying var along its dimension.