xskillscore.spearman_r¶
- xskillscore.spearman_r(a, b, dim=None, weights=None, skipna=False, keep_attrs=False)¶
Spearman’s correlation coefficient.
- Parameters
a (xarray.Dataset or xarray.DataArray) – Labeled array(s) over which to apply the function.
b (xarray.Dataset or xarray.DataArray) – Labeled array(s) over which to apply the function.
dim (str, list) – The dimension(s) to apply the correlation along. Note that this dimension will be reduced as a result. Defaults to None reducing all dimensions.
weights (xarray.Dataset or xarray.DataArray or None) – Weights matching dimensions of
dim
to apply during the function.skipna (bool) – If True, skip NaNs when computing function.
keep_attrs (bool) – If True, the attributes (attrs) will be copied from the first input to the new one. If False (default), the new object will be returned without attributes.
- Returns
Spearman’s correlation coefficient.
- Return type
See also
scipy.stats.spearman_r
References
https://github.com/scipy/scipy/blob/v1.3.1/scipy/stats/stats.py#L3613-L3764 https://en.wikipedia.org/wiki/Spearman%27s_rank_correlation_coefficient
Examples
>>> a = xr.DataArray(np.random.rand(5, 3, 3), dims=['time', 'x', 'y']) >>> b = xr.DataArray(np.random.rand(5, 3, 3), dims=['time', 'x', 'y']) >>> xs.spearman_r(a, b, dim='time') <xarray.DataArray (x: 3, y: 3)> array([[-0.6, -0.5, -0.7], [ 0.4, 0.3, 0.3], [-0.3, -0.1, 0.9]]) Dimensions without coordinates: x, y