# 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]]
```