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Find Unique Rows in a NumPy Array

In this tutorial, we will learn how to find the unique rows from a given multi-dimensional (2D) NumPy array? By Pranit Sharma Last updated : May 26, 2023

Problem Statement

Given a multi-dimensional (2D) NumPy array, we have to find its unique rows.

Finding unique rows in a NumPy array

The numpy.unique() method can be used to find the unique rows in a NumPy array. You can use this method with axis = 0 parameter to exclude the common rows. Consider the below statement for finding the unique rows:

np.unique(arr, axis=0)

Where, arr is a 2D NumPy array.

Let us understand with the help of an example,

Example 1: Find unique rows in a NumPy array

# Import NumPy
import numpy as np

# Creating 2D NumPy array
arr = np.array(
    [
        [1, 1, 1, 0, 0, 0],
        [0, 1, 1, 1, 0, 0],
        [0, 1, 1, 1, 0, 0],
        [1, 1, 1, 0, 0, 0],
        [1, 1, 1, 1, 1, 0],
    ]
)

# Printing original array
print("Original array (arr):\n", arr, "\n")

# Finding unique rows
res = np.unique(arr, axis=0)

# Display result
print("Unique rows (res):\n", res)

Output

Original array (arr):
 [[1 1 1 0 0 0]
 [0 1 1 1 0 0]
 [0 1 1 1 0 0]
 [1 1 1 0 0 0]
 [1 1 1 1 1 0]] 

Unique rows (res):
 [[0 1 1 1 0 0]
 [1 1 1 0 0 0]
 [1 1 1 1 1 0]]

Example 2: Find unique rows in a NumPy array

# Import NumPy
import numpy as np

# Creating 2D NumPy array
arr = np.array(
    [
        [10, 20, 30, 40, 50],
        [20, 30, 40, 50, 60],
        [30, 60, 40, 80, 90],
        [20, 30, 40, 50, 60],
        [10, 20, 30, 40, 50],
    ]
)

# Printing original array
print("Original array (arr):\n", arr, "\n")

# Finding unique rows
res = np.unique(arr, axis=0)

# Display result
print("Unique rows (res):\n", res)

Output

Original array (arr):
 [[10 20 30 40 50]
 [20 30 40 50 60]
 [30 60 40 80 90]
 [20 30 40 50 60]
 [10 20 30 40 50]] 

Unique rows (res):
 [[10 20 30 40 50]
 [20 30 40 50 60]
 [30 60 40 80 90]]

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