Find unique rows in a NumPy array

In this article we will discuss how to find unique rows in a NumPy array. To find unique rows in a NumPy array we are using numpy.unique() function of NumPy library.

Syntax : numpy.unique(ar, return_index=False, return_inverse=False, return_counts=False, axis=None)

Now, let’s see an example:

Example 1:

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# import library
import numpy as np
  
# Create a 2D numpy array
arr2D = np.array([[11, 11, 12, 11],
                     [13, 11, 12, 11],
                     [16, 11, 12, 11],
                     [11, 11, 12, 11]])
  
print('Original Array :' ,
      arr2D, sep = '\n')
  
# Get unique rows from
# complete 2D-array by 
# passing axis = 0 in 
# unique function along
# with 2D-array
uniqueRows = np.unique(arr2D, 
                       axis = 0)
  
# print the output result
print('Unique Rows:',
      uniqueRows, sep = '\n')

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Output:


Original Array :
[[11 11 12 11]
[13 11 12 11]
[16 11 12 11]
[11 11 12 11]]
Unique Rows:
[[11 11 12 11]
[13 11 12 11]
[16 11 12 11]]



Example 2:






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# import library 


import numpy as np 


  


# create 2d numpy array 


array = np.array([[1, 2, 3, 4], 


                  [3, 2, 4, 1], 


                  [6, 8, 1, 2]]) 


  


print("Original array: \n", 


      array) 


  


# Get unique rows from 


# complete 2D-array by  


# passing axis = 0 in  


# unique function along 


# with 2D-array 


uniqueRows = np.unique(array,  


                       axis = 0) 


  


# print the output result 


print('Unique Rows :', 


      uniqueRows, 


      sep = '\n')



















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Output:


Original array: 
 [[1 2 3 4]
 [3 2 4 1]
 [6 8 1 2]]
Unique Rows :
[[1 2 3 4]
 [3 2 4 1]
 [6 8 1 2]]





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