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 of np.unique() in Python

Syntax: numpy.unique()

Parameter:

• ar: array
• return_index: Bool, if True return the indices of the input array
• return_inverse: Bool, if True return the indices of the input array
• return_counts: Bool, if True return the number of times each unique item appeared in the input array
• axis: int or none, defines the axis to operate on

Examples to get unique rows in a NumPy array

Example 1:

Get unique rows from complete 2D-array.

Output:

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

Example 2:

Get unique rows from complete 2D-array by passing axis = 0 in unique function along with 2D-array. You will notice that rows 1 and 4 are the same hence one of the columns is excluded.

Output:

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

Example 3:

Get unique rows from complete 2D-array by passing axis=1 in unique function along with 2D-array. You will notice that columns 1 and 4 are the same hence one of the columns is excluded.

Output:

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

Example 4:

Returning the index of unique elements.

Output:

Unique Rows:
(array([11, 12, 13, 16]), array([0, 2, 4, 8], dtype=int64))

Example 5:

In this output, a ndarray will be shown that contains the indices to reconstruct the original array from the unique array.

Output:

Unique Rows:
(array([11, 12, 13, 16]), array([0, 0, 1, 0, 2, 0, 1, 0, 3, 0, 1, 0, 0, 0, 1, 0], dtype=int64))