xarray.DataArray.groupby¶
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DataArray.
groupby
(group, squeeze=True)¶ Returns a GroupBy object for performing grouped operations.
Parameters: - group : str, DataArray or IndexVariable
Array whose unique values should be used to group this array. If a string, must be the name of a variable contained in this dataset.
- squeeze : boolean, optional
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.
Returns: - grouped : GroupBy
A GroupBy object patterned after pandas.GroupBy that can be iterated over in the form of (unique_value, grouped_array) pairs.
Examples
Calculate daily anomalies for daily data:
>>> da = xr.DataArray(np.linspace(0, 1826, num=1827), ... coords=[pd.date_range('1/1/2000', '31/12/2004', ... freq='D')], ... dims='time') >>> da <xarray.DataArray (time: 1827)> array([0.000e+00, 1.000e+00, 2.000e+00, ..., 1.824e+03, 1.825e+03, 1.826e+03]) Coordinates: * time (time) datetime64[ns] 2000-01-01 2000-01-02 2000-01-03 ... >>> da.groupby('time.dayofyear') - da.groupby('time.dayofyear').mean('time') <xarray.DataArray (time: 1827)> array([-730.8, -730.8, -730.8, ..., 730.2, 730.2, 730.5]) Coordinates: * time (time) datetime64[ns] 2000-01-01 2000-01-02 2000-01-03 ... dayofyear (time) int64 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 ...