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NumPy| How to get the unique elements of an Array

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To find unique elements of an array we use the numpy.unique() method of the NumPy library in Python.

It returns unique elements in a new sorted array.

Example:

Python3




import numpy as np
arr = np.array([1, 2, 3, 1, 4, 5, 2, 5])
unique_elements = np.unique(arr)
print(unique_elements)


Output:

[1 2 3 4 5]

Syntax

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

Parameters

  • ar: Input array. 
  • return_index: If True, also return the indices of ar that result in the unique array.
  • return_inverse: If True, also return the indices of the unique array that can be used to reconstruct ar.
  • return_counts: If True, also return the number of times each unique item appears in ar.
  • axis: The axis to operate on. If None, ar will be flattened.

Returns: Return the unique of an array. 

Let us look at some examples of how to get the unique elements of an array using NumPy library:

More Examples

Here we will see examples of how to find unique elements in 1D and 2D NumPy arrays.

Example 1: Finding Unique Elements in a 1D Numpy Array

Python3




# import library
import numpy as np             
  
# create 1d-array
arr = np.array([3, 3, 4
                5, 6, 5,
                6, 4])
  
# find unique element 
# from a array
rslt = np.unique(arr)
  
print(rslt)


Output:

[3 4 5 6]

Example 2: Finding Unique Elements in a 2D Numpy Array

Python3




# import library
import numpy as np
  
# create a numpy 2d-array
arr = np.array([[9, 9, 7, 7],
              [3, 4, 3, 4]])
  
# find unique element
# from a array
rslt = np.unique(arr)
  
print(rslt)


Output:

[3 4 7 9] 


Last Updated : 09 Feb, 2024
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