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
- 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, axis, keep_attrs])Reduce this DataArrayGroupBy’s data by applying all along some dimension(s).
any
([dim, axis, keep_attrs])Reduce this DataArrayGroupBy’s data by applying any along some dimension(s).
apply
(func[, shortcut, args])Apply a function over each array in the group and concatenate them together into a new array.
argmax
([dim, axis, skipna, keep_attrs])Reduce this DataArrayGroupBy’s data by applying argmax along some dimension(s).
argmin
([dim, axis, skipna, keep_attrs])Reduce this DataArrayGroupBy’s data by applying argmin along some dimension(s).
assign_coords
(**kwargs)Assign coordinates by group.
count
([dim, axis, keep_attrs])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
max
([dim, axis, skipna, keep_attrs])Reduce this DataArrayGroupBy’s data by applying max along some dimension(s).
mean
([dim, axis, skipna, keep_attrs])Reduce this DataArrayGroupBy’s data by applying mean along some dimension(s).
median
([dim, axis, skipna, keep_attrs])Reduce this DataArrayGroupBy’s data by applying median along some dimension(s).
min
([dim, axis, skipna, keep_attrs])Reduce this DataArrayGroupBy’s data by applying min along some dimension(s).
prod
([dim, axis, skipna, keep_attrs])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, keep_attrs])Reduce this DataArrayGroupBy’s data by applying std along some dimension(s).
sum
([dim, axis, skipna, keep_attrs])Reduce this DataArrayGroupBy’s data by applying sum along some dimension(s).
var
([dim, axis, skipna, keep_attrs])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
groups
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