numpy.count_nonzero() function counts the number of non-zero values in the array arr.
Syntax : numpy.count_nonzero(arr, axis=None)
Parameters :
arr : [array_like] The array for which to count non-zeros.
axis : [int or tuple, optional] Axis or tuple of axes along which to count non-zeros. Default is None, meaning that non-zeros will be counted along a flattened version of arr.Return : [int or array of int] Number of non-zero values in the array along a given axis. Otherwise, the total number of non-zero values in the array is returned.
Code #1 :
# Python program explaining# numpy.count_nonzero() function # importing numpy as geek import numpy as geek arr = [[0, 1, 2, 3, 0], [0, 5, 6, 0, 7]] gfg = geek.count_nonzero(arr) print (gfg) |
Output :
6
Code #2 :
# Python program explaining# numpy.count_nonzero() function # importing numpy as geek import numpy as geek arr = [[0, 1, 2, 3, 4], [5, 0, 6, 0, 7]] gfg = geek.count_nonzero(arr, axis = 0) print (gfg) |
Output :
7
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