xarray.DataArray.groupby_bins¶
-
DataArray.
groupby_bins
(group, bins, right=True, labels=None, precision=3, include_lowest=False, squeeze=True, restore_coord_dims=None)[source]¶ Returns a GroupBy object for performing grouped operations.
Rather than using all unique values of group, the values are discretized first by applying pandas.cut 1 to group.
- Parameters
group (
str
,DataArray
orIndexVariable
) – Array whose binned values should be used to group this array. If a string, must be the name of a variable contained in this dataset.bins (
int
or array-like) – If bins is an int, it defines the number of equal-width bins in the range of x. However, in this case, the range of x is extended by .1% on each side to include the min or max values of x. If bins is a sequence it defines the bin edges allowing for non-uniform bin width. No extension of the range of x is done in this case.right (
bool
, default:True
) – Indicates whether the bins include the rightmost edge or not. If right == True (the default), then the bins [1,2,3,4] indicate (1,2], (2,3], (3,4].labels (array-like or
bool
, default:None
) – Used as labels for the resulting bins. Must be of the same length as the resulting bins. If False, string bin labels are assigned by pandas.cut.precision (
int
) – The precision at which to store and display the bins labels.include_lowest (
bool
) – Whether the first interval should be left-inclusive or not.squeeze (
bool
, default:True
) – If “group” is a dimension of any arrays in this dataset, squeeze controls whether the subarrays have a dimension of length 1 along that dimension or if the dimension is squeezed out.restore_coord_dims (
bool
, optional) – If True, also restore the dimension order of multi-dimensional coordinates.
- Returns
grouped
– A GroupBy object patterned after pandas.GroupBy that can be iterated over in the form of (unique_value, grouped_array) pairs. The name of the group has the added suffix _bins in order to distinguish it from the original variable.
References