xarray.DataArray.idxmax#
- DataArray.idxmax(dim=None, *, skipna=None, fill_value=<NA>, keep_attrs=None)[source]#
Return the coordinate label of the maximum value along a dimension.
Returns a new DataArray named after the dimension with the values of the coordinate labels along that dimension corresponding to maximum values along that dimension.
In comparison to
argmax()
, this returns the coordinate label whileargmax()
returns the index.- Parameters
dim (
Hashable
, optional) – Dimension over which to apply idxmax. This is optional for 1D arrays, but required for arrays with 2 or more dimensions.skipna (
bool
orNone
, default:None
) – If True, skip missing values (as marked by NaN). By default, only skips missing values forfloat
,complex
, andobject
dtypes; other dtypes either do not have a sentinel missing value (int
) orskipna=True
has not been implemented (datetime64
ortimedelta64
).fill_value (
Any
, default:NaN
) – Value to be filled in case all of the values along a dimension are null. By default this is NaN. The fill value and result are automatically converted to a compatible dtype if possible. Ignored ifskipna
is False.keep_attrs (
bool
orNone
, optional) – If True, the attributes (attrs
) will be copied from the original object to the new one. If False, the new object will be returned without attributes.
- Returns
reduced (
DataArray
) – New DataArray object with idxmax applied to its data and the indicated dimension removed.
See also
Dataset.idxmax
,DataArray.idxmin
,DataArray.max
,DataArray.argmax
Examples
>>> array = xr.DataArray( ... [0, 2, 1, 0, -2], dims="x", coords={"x": ["a", "b", "c", "d", "e"]} ... ) >>> array.max() <xarray.DataArray ()> Size: 8B array(2) >>> array.argmax(...) {'x': <xarray.DataArray ()> Size: 8B array(1)} >>> array.idxmax() <xarray.DataArray 'x' ()> Size: 4B array('b', dtype='<U1')
>>> array = xr.DataArray( ... [ ... [2.0, 1.0, 2.0, 0.0, -2.0], ... [-4.0, np.nan, 2.0, np.nan, -2.0], ... [np.nan, np.nan, 1.0, np.nan, np.nan], ... ], ... dims=["y", "x"], ... coords={"y": [-1, 0, 1], "x": np.arange(5.0) ** 2}, ... ) >>> array.max(dim="x") <xarray.DataArray (y: 3)> Size: 24B array([2., 2., 1.]) Coordinates: * y (y) int64 24B -1 0 1 >>> array.argmax(dim="x") <xarray.DataArray (y: 3)> Size: 24B array([0, 2, 2]) Coordinates: * y (y) int64 24B -1 0 1 >>> array.idxmax(dim="x") <xarray.DataArray 'x' (y: 3)> Size: 24B array([0., 4., 4.]) Coordinates: * y (y) int64 24B -1 0 1