NumPy| How to get the unique elements of an Array
Last Updated :
09 Feb, 2024
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 numpy as np
arr = np.array([ 3 , 3 , 4 ,
5 , 6 , 5 ,
6 , 4 ])
rslt = np.unique(arr)
print (rslt)
|
Output:
[3 4 5 6]
Example 2: Finding Unique Elements in a 2D Numpy Array
Python3
import numpy as np
arr = np.array([[ 9 , 9 , 7 , 7 ],
[ 3 , 4 , 3 , 4 ]])
rslt = np.unique(arr)
print (rslt)
|
Output:
[3 4 7 9]
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