xarray.core.groupby.DataArrayGroupBy¶
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class
xarray.core.groupby.
DataArrayGroupBy
(obj, group, squeeze=False, grouper=None, bins=None, restore_coord_dims=None, cut_kwargs={})¶ GroupBy object specialized to grouping DataArray objects
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__init__
(obj, group, squeeze=False, grouper=None, bins=None, restore_coord_dims=None, cut_kwargs={})¶ Create a GroupBy object
Parameters: - obj (Dataset or DataArray) – Object to group.
- group (DataArray) – Array with the group values.
- squeeze (boolean, optional) – If “group” is a coordinate of object, squeeze controls whether the subarrays have a dimension of length 1 along that coordinate or if the dimension is squeezed out.
- grouper (pd.Grouper, optional) – Used for grouping values along the group array.
- bins (array-like, optional) – If bins is specified, the groups will be discretized into the specified bins by pandas.cut.
- restore_coord_dims (bool, optional) – If True, also restore the dimension order of multi-dimensional coordinates.
- cut_kwargs (dict, optional) – Extra keyword arguments to pass to pandas.cut
Methods
__init__
(obj, group[, squeeze, grouper, …])Create a GroupBy object all
([dim, axis])Reduce this DataArrayGroupBy’s data by applying all along some dimension(s). any
([dim, axis])Reduce this DataArrayGroupBy’s data by applying any along some dimension(s). apply
(func[, shortcut, args])Backward compatible implementation of map
argmax
([dim, axis, skipna])Reduce this DataArrayGroupBy’s data by applying argmax along some dimension(s). argmin
([dim, axis, skipna])Reduce this DataArrayGroupBy’s data by applying argmin along some dimension(s). assign_coords
([coords])Assign coordinates by group. count
([dim, axis])Reduce this DataArrayGroupBy’s data by applying count along some dimension(s). fillna
(value)Fill missing values in this object by group. first
([skipna, keep_attrs])Return the first element of each group along the group dimension last
([skipna, keep_attrs])Return the last element of each group along the group dimension map
(func[, shortcut, args])Apply a function to each array in the group and concatenate them together into a new array. max
([dim, axis, skipna])Reduce this DataArrayGroupBy’s data by applying max along some dimension(s). mean
([dim, axis, skipna])Reduce this DataArrayGroupBy’s data by applying mean along some dimension(s). median
([dim, axis, skipna])Reduce this DataArrayGroupBy’s data by applying median along some dimension(s). min
([dim, axis, skipna])Reduce this DataArrayGroupBy’s data by applying min along some dimension(s). prod
([dim, axis, skipna])Reduce this DataArrayGroupBy’s data by applying prod along some dimension(s). quantile
(q[, dim, interpolation, keep_attrs])Compute the qth quantile over each array in the groups and concatenate them together into a new array. reduce
(func[, dim, axis, keep_attrs, shortcut])Reduce the items in this group by applying func along some dimension(s). std
([dim, axis, skipna])Reduce this DataArrayGroupBy’s data by applying std along some dimension(s). sum
([dim, axis, skipna])Reduce this DataArrayGroupBy’s data by applying sum along some dimension(s). var
([dim, axis, skipna])Reduce this DataArrayGroupBy’s data by applying var along some dimension(s). where
(cond[, other])Return elements from self or other depending on cond. Attributes
dims
groups
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