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numpy string operations | equal() function

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numpy.core.defchararray.equal(arr1, arr2) is another function for doing string operations in numpy. It checks the elements of two same-shaped array one by one and returns True if they are equal. Otherwise, it returns False.
Parameters: arr1 : array_like of str or unicode. arr2 : array_like of str or unicode. Returns : [ndarray] Output array of bools, or a single bool if arr1 and arr2 are scalars.
Code #1 :
# Python program explaining
# numpy.char.equal() method 
  
# importing numpy 
import numpy as geek
  
# input arrays  
in_arr1 = geek.array('numpy')
print ("1st Input array : ", in_arr1)
  
in_arr2 = geek.array('numpy')
print ("2nd Input array : ", in_arr2)  
  
# checking if they are equal
out_arr = geek.char.equal(in_arr1, in_arr2)
print ("Output array: ", out_arr) 

                    
Output:
1st Input array :  numpy
2nd Input array :  numpy
Output array:  True
  Code #2 :
# Python program explaining
# numpy.char.equal() method 
  
# importing numpy 
import numpy as geek
  
# input arrays  
in_arr1 = geek.array(['Geeks', 'for', 'Geeks'])
print ("1st Input array : ", in_arr1) 
  
in_arr2 = geek.array(['Geek', 'for', 'Geek'])
print ("2nd Input array : ", in_arr2) 
  
# checking if they are equal
out_arr = geek.char.equal(in_arr1, in_arr2)
print ("Output array: ", out_arr) 

                    
Output:
1st Input array :  ['Geeks' 'for' 'Geeks']
2nd Input array :  ['Geek' 'for' 'Geek']
Output array:  [False  True False]
  Code #3 :
# Python program explaining
# numpy.char.equal() method 
  
# importing numpy 
import numpy as geek
  
# input arrays  
in_arr1 = geek.array(['10', '11', '12'])
print ("1st Input array : ", in_arr1) 
  
in_arr2 = geek.array(['10', '11', '121'])
print ("2nd Input array : ", in_arr2) 
  
  
# checking if they are equal
out_arr = geek.char.equal(in_arr1, in_arr2)
print ("Output array: ", out_arr) 

                    
Output:
1st Input array :  ['10' '11' '12']
2nd Input array :  ['10' '11' '121']
Output array:  [ True  True False]


Last Updated : 26 Jan, 2019
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