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numpy.equal() in Python
  • Last Updated : 29 Nov, 2018

numpy.equal(arr1, arr2, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None, ufunc ‘not_equal’) : This logical function checks for arr1 == arr2 elemen-twise.

Parameters :

arr1 : [array_like]Input array
arr2 : [array_like]Input array

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 :

Returns arr1 == arr2 element-wise

 
Code 1 :




# Python Program illustrating
# numpy.equal() method
import numpy as geek 
   
= geek.equal([1., 2.], [1., 3.])
print("Check to be Equal : \n", a, "\n")
   
b = geek.equal([1, 2], [[1, 3],[1, 4]])
print("Check to be Equal : \n", b, "\n")


Output :

Check to be Equal : 
 [ True False] 

Check to be Equal : 
 [[ True False]
 [ True False]] 

 
Code 2 : Comparing data-type using .equal() function




# Python Program illustrating
# numpy.equal() method
import numpy as geek 
   
# Here we will compare Complex values with int
a = geek.array([0 + 1j, 2])
b = geek.array([1,2])
   
= geek.equal(a, b)
print("Comparing complex with int using .equal() : ", d)


Output :

Comparing complex with int using .equal() :  [False  True]

 
Code 3 :




# Python Program illustrating
# numpy.not_equal() method
import numpy as geek 
   
# Here we will compare Float with int values
a = geek.array([1.1, 1])
b = geek.array([1, 2])
    
= geek.not_equal(a, b)
print("\nComparing float with int using .not_equal() : ", d)


Output :

Comparing float with int using .not_equal() :  [ True  True]

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

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