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Find unique rows in a NumPy array
• Last Updated : 02 Sep, 2020

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:

## Python3

 `# 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'``)`

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:

## Python3

 `# 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'``)`

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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