numpy.nonzero() in Python
Last Updated :
28 Nov, 2018
numpy.nonzero()
function is used to Compute the indices of the elements that are non-zero.
It returns a tuple of arrays, one for each dimension of arr, containing the indices of the non-zero elements in that dimension.
The corresponding non-zero values in the array can be obtained with arr[nonzero(arr)]
. To group the indices by element, rather than dimension we can use transpose(nonzero(arr))
.
Syntax : numpy.nonzero(arr)
Parameters :
arr : [array_like] Input array.
Return : [tuple_of_arrays] Indices of elements that are non-zero.
Code #1 : Working
import numpy as geek
arr = geek.array([[ 0 , 8 , 0 ], [ 7 , 0 , 0 ], [ - 5 , 0 , 1 ]])
print ( "Input array : \n" , arr)
out_tpl = geek.nonzero(arr)
print ( "Indices of non zero elements : " , out_tpl)
|
Output :
Input array :
[[ 0 8 0]
[ 7 0 0]
[-5 0 1]]
Indices of non zero elements : (array([0, 1, 2, 2], dtype=int64), array([1, 0, 0, 2], dtype=int64))
Code #2 :
out_arr = arr[geek.nonzero(arr)]
print ( "Output array of non-zero number: " , out_arr)
|
Output :
Output array of non-zero number: [ 8 7 -5 1]
Code #3 :
out_ind = geek.transpose(geek.nonzero(arr))
print ( "indices of non-zero number: \n" , out_ind)
|
Output :
indices of non-zero number:
[[0 1]
[1 0]
[2 0]
[2 2]]
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