numpy.divide() in Python (original) (raw)

Last Updated : 29 Nov, 2018

numpy.divide(arr1, arr2, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None) :
Array element from first array is divided by elements from second element (all happens element-wise). Both arr1 and arr2 must have same shape and element in arr2 must not be zero; otherwise it will raise an error.

Parameters :

arr1 : [array_like]Input array or object which works as dividend.
arr2 : [array_like]Input array or object which works as divisor.
out : [ndarray, optional]Output array with same dimensions as Input array,
placed with result.
**kwargs : allows you to pass keyword variable length of argument to a function.
It is used when we want to handle named argument in a function.
where : [array_like, optional]True value means to calculate the universal
functions(ufunc) at that position, False value means to leave the
value in the output alone.

Return :

An array with arr1/arr2(element-wise) as elements of output array.

Code 1 : arr1 divide by arr2 elements

import numpy as np

arr1 = [ 2 , 27 , 2 , 21 , 23 ]

arr2 = [ 2 , 3 , 4 , 5 , 6 ]

print ( "arr1 : " , arr1)

print ( "arr2 : " , arr2)

out = np.divide(arr1, arr2)

print ( "\nOutput array : \n" , out)

Output :

arr1 : [2, 27, 2, 21, 23] arr2 : [2, 3, 4, 5, 6]

Output array : [ 1. 9. 0.5 4.2 3.83333333]

Code 2 : elements of arr1 divided by divisor

import numpy as np

arr1 = [ 2 , 27 , 2 , 21 , 23 ]

divisor = 3

print ( "arr1 : " , arr1)

out = np.divide(arr1, divisor)

print ( "\nOutput array : \n" , out)

Output :

arr1 : [2, 27, 2, 21, 23]

Output array : [ 0.66666667 9. 0.66666667 7. 7.66666667]

Code 3 : warning if arr2 has element = 0

import numpy as np

arr1 = [ 2 , 27 , 2 , 21 , 23 ]

arr2 = [ 2 , 3 , 0 , 5 , 6 ]

print ( "arr1 : " , arr1)

print ( "arr2 : " , arr2)

out = np.divide(arr1, arr2)

print ( "\nOutput array : " , out)

Output :

arr1 : [2, 27, 2, 21, 23] arr2 : [2, 3, 0, 5, 6]

Output array : [ 1. 9. inf 4.2 3.83333333] RuntimeWarning: divide by zero encountered in true_divide out = np.power(arr1, arr2)

References :
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.divide.html
.