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Showing content from https://docs.scipy.org/doc/numpy/reference/generated/numpy.argwhere.html below:

numpy.argwhere — NumPy v2.3 Manual

numpy.argwhere(a)[source]#

Find the indices of array elements that are non-zero, grouped by element.

Parameters:

aarray_like

Input data.

Returns:

index_array(N, a.ndim) ndarray

Indices of elements that are non-zero. Indices are grouped by element. This array will have shape (N, a.ndim) where N is the number of non-zero items.

Notes

np.argwhere(a) is almost the same as np.transpose(np.nonzero(a)), but produces a result of the correct shape for a 0D array.

The output of argwhere is not suitable for indexing arrays. For this purpose use nonzero(a) instead.

Examples

>>> import numpy as np
>>> x = np.arange(6).reshape(2,3)
>>> x
array([[0, 1, 2],
       [3, 4, 5]])
>>> np.argwhere(x>1)
array([[0, 2],
       [1, 0],
       [1, 1],
       [1, 2]])

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