numpy.divide() in Python

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.

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

# Python program explaining
# divide() function
import numpy as np

# input_array
arr1 = [2, 27, 2, 21, 23]
arr2 = [2, 3, 4, 5, 6]
print ("arr1         : ", arr1)
print ("arr2         : ", arr2)

# output_array
out = np.divide(arr1, arr2)
print ("\nOutput array : \n", out)

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

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

# Python program explaining
# divide() function
import numpy as np

# input_array
arr1 = [2, 27, 2, 21, 23]
divisor = 3
print ("arr1         : ", arr1)

# output_array
out = np.divide(arr1, divisor)
print ("\nOutput array : \n", out)

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

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

# Python program explaining
# divide() function
import numpy as np

# input_array
arr1 = [2, 27, 2, 21, 23]
arr2 = [2, 3, 0, 5, 6]
print ("arr1         : ", arr1)
print ("arr2         : ", arr2)

# output_array
out = np.divide(arr1, arr2)
print ("\nOutput array : ", out)

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)

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Article Tags :

• Python
• Python-numpy
• Python numpy-Mathematical Function

Practice Tags :

• python