numpy.nanargmax#

numpy.nanargmax(a, axis=None, out=None, *, keepdims=<no value>)[source]#

Return the indices of the maximum values in the specified axis ignoring NaNs. For all-NaN slices ValueError is raised. Warning: the results cannot be trusted if a slice contains only NaNs and -Infs.

Parameters:

aarray_like: Input data.
axisint, optional: Axis along which to operate. By default flattened input is used.
outarray, optional: If provided, the result will be inserted into this array. It should be of the appropriate shape and dtype.

New in version 1.22.0.
keepdimsbool, optional: If this is set to True, the axes which are reduced are left in the result as dimensions with size one. With this option, the result will broadcast correctly against the array.

New in version 1.22.0.

Returns:

index_arrayndarray: An array of indices or a single index value.

See also

argmax, nanargmin

Examples

>>> import numpy as np
>>> a = np.array([[np.nan, 4], [2, 3]])
>>> np.argmax(a)
0
>>> np.nanargmax(a)
1
>>> np.nanargmax(a, axis=0)
array([1, 0])
>>> np.nanargmax(a, axis=1)
array([1, 1])