xarray.core.groupby.DatasetGroupBy¶
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class
xarray.core.groupby.
DatasetGroupBy
(obj, group, squeeze=False, grouper=None, bins=None, restore_coord_dims=None, cut_kwargs={})¶ -
__init__
(self, obj, group, squeeze=False, grouper=None, bins=None, restore_coord_dims=None, cut_kwargs={})¶ Create a GroupBy object
- Parameters
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__
(self, obj, group[, squeeze, …])Create a GroupBy object
all
(self[, dim])Reduce this DatasetGroupBy’s data by applying all along some dimension(s).
any
(self[, dim])Reduce this DatasetGroupBy’s data by applying any along some dimension(s).
apply
(self, func[, args, shortcut])Backward compatible implementation of
map
argmax
(self[, dim, skipna])Reduce this DatasetGroupBy’s data by applying argmax along some dimension(s).
argmin
(self[, dim, skipna])Reduce this DatasetGroupBy’s data by applying argmin along some dimension(s).
assign
(self, \*\*kwargs)Assign data variables by group.
assign_coords
(self[, coords])Assign coordinates by group.
count
(self[, dim])Reduce this DatasetGroupBy’s data by applying count along some dimension(s).
fillna
(self, value)Fill missing values in this object by group.
first
(self[, skipna, keep_attrs])Return the first element of each group along the group dimension
last
(self[, skipna, keep_attrs])Return the last element of each group along the group dimension
map
(self, func[, args, shortcut])Apply a function to each Dataset in the group and concatenate them together into a new Dataset.
max
(self[, dim, skipna])Reduce this DatasetGroupBy’s data by applying max along some dimension(s).
mean
(self[, dim, skipna])Reduce this DatasetGroupBy’s data by applying mean along some dimension(s).
median
(self[, dim, skipna])Reduce this DatasetGroupBy’s data by applying median along some dimension(s).
min
(self[, dim, skipna])Reduce this DatasetGroupBy’s data by applying min along some dimension(s).
prod
(self[, dim, skipna])Reduce this DatasetGroupBy’s data by applying prod along some dimension(s).
quantile
(self, q[, dim, interpolation, …])Compute the qth quantile over each array in the groups and concatenate them together into a new array.
reduce
(self, func[, dim, keep_attrs])Reduce the items in this group by applying func along some dimension(s).
std
(self[, dim, skipna])Reduce this DatasetGroupBy’s data by applying std along some dimension(s).
sum
(self[, dim, skipna])Reduce this DatasetGroupBy’s data by applying sum along some dimension(s).
var
(self[, dim, skipna])Reduce this DatasetGroupBy’s data by applying var along some dimension(s).
where
(self, cond[, other])Return elements from self or other depending on cond.
Attributes
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