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

   # Python program explaining 
# nonzero() function 
  
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 :

   # Python program for getting 
# The corresponding non-zero values: 
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 :

   # Python program for grouping the indices 
# by element, rather than dimension 
  
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]]

numpy.nanmin() in Python

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