xarray.core.groupby.DatasetGroupBy

class xarray.core.groupby.DatasetGroupBy(obj, group, squeeze=False, grouper=None, bins=None, restore_coord_dims=None, cut_kwargs={})

__init__(obj, group, squeeze=False, grouper=None, bins=None, restore_coord_dims=None, cut_kwargs={})

Create a GroupBy object

Parameters

objDataset or DataArray

Object to group.

groupDataArray

Array with the group values.

squeezeboolean, 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.

grouperpd.Grouper, optional

Used for grouping values along the group array.

binsarray-like, optional

If bins is specified, the groups will be discretized into the specified bins by pandas.cut.

restore_coord_dimsbool, optional

If True, also restore the dimension order of multi-dimensional coordinates.

cut_kwargsdict, optional

Extra keyword arguments to pass to pandas.cut

Methods

__init__(obj, group[, squeeze, grouper, …])	Create a GroupBy object
all([dim])	Reduce this DatasetGroupBy’s data by applying all along some dimension(s).
any([dim])	Reduce this DatasetGroupBy’s data by applying any along some dimension(s).
apply(func[, args, shortcut])	Apply a function over each Dataset in the group and concatenate them together into a new Dataset.
argmax([dim, skipna])	Reduce this DatasetGroupBy’s data by applying argmax along some dimension(s).
argmin([dim, skipna])	Reduce this DatasetGroupBy’s data by applying argmin along some dimension(s).
assign(**kwargs)	Assign data variables by group.
assign_coords(**kwargs)	Assign coordinates by group.
count([dim])	Reduce this DatasetGroupBy’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
max([dim, skipna])	Reduce this DatasetGroupBy’s data by applying max along some dimension(s).
mean([dim, skipna])	Reduce this DatasetGroupBy’s data by applying mean along some dimension(s).
median([dim, skipna])	Reduce this DatasetGroupBy’s data by applying median along some dimension(s).
min([dim, skipna])	Reduce this DatasetGroupBy’s data by applying min along some dimension(s).
prod([dim, skipna])	Reduce this DatasetGroupBy’s data by applying prod along some dimension(s).
reduce(func[, dim, keep_attrs])	Reduce the items in this group by applying func along some dimension(s).
std([dim, skipna])	Reduce this DatasetGroupBy’s data by applying std along some dimension(s).
sum([dim, skipna])	Reduce this DatasetGroupBy’s data by applying sum along some dimension(s).
var([dim, skipna])	Reduce this DatasetGroupBy’s data by applying var along some dimension(s).
where(cond[, other])	Return elements from self or other depending on cond.

Attributes

groups