# Numpy – Remove Duplicates From Array

The Numpy library in Python comes with a number of useful functions to work with and manipulate data in Numpy arrays. In this tutorial, we will look at how to remove duplicates from a Numpy array with the help of some examples.

## How to remove duplicates from a Numpy array?

You can use the Numpy `unique()` function to remove duplicates from an array. Pass the array as an argument. The following is the syntax –

```# remove duplicates from numpy array
np.unique(ar)```

It returns a Numpy array with the duplicate elements removed from the passed array.

You can also use the Numpy `unique()` function to remove duplicate rows and columns from a 2-D Numpy array (see the examples below)

## Remove duplicate values from a one-dimensional Numpy array

Let’s now look at an example of using the above syntax to remove duplicate values from a one-dimensional Numpy array.

First, let’s create a 1-D array.

```import numpy as np

# create a numpy array
ar = np.array([1, 2, 2, 3, 2, 3, 1, 4])
# print the array
print(ar)```

Output:

`[1 2 2 3 2 3 1 4]`

Here, we use the `np.array()` function to create a Numpy array of some numbers. You can see that there are duplicate values present in the above array.

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Let’s now remove the duplicate values from the above array using the `np.unique()` function.

```# remove duplicates from numpy array
print(np.unique(ar))```

Output:

`[1 2 3 4]`

The resulting array contains only the unique values from the passed array.

## Remove duplicate rows or columns of two-dimensional Numpy array

You can also use the `np.unique()` function to remove duplicate rows or columns from a two-dimensional Numpy array.

### Remove duplicate rows in Numpy

To remove duplicate rows of a 2-D Numpy array, use the `np.unique()` function with `axis=0` parameter.

Let’s look at an example. First, we will create a 2-D array.

```# create a numpy array
ar = np.array([[1, 2, 1], [2, 3, 5], [1, 2, 1]])
# print the array
print(ar)```

Output:

```[[1 2 1]
[2 3 5]
[1 2 1]]```

Here, we created a 2-D Numpy array with three rows and three columns. You can see that this array contains a duplicate row (the first and the last rows are duplicates).

Let’s now remove the duplicate rows using the `np.unique()` function.

```# remove duplicate rows from numpy array
print(np.unique(ar, axis=0))```

Output:

```[[1 2 1]
[2 3 5]]```

The resulting Numpy array contains only the unique rows from the original array.

### Remove duplicate columns in Numpy

You can similarly remove duplicate columns from a 2-D Numpy array. For this, pass `axis=1` to the `np.unique()` function.

Let’s look at an example. First, we will create a 2-D array.

```# create a numpy array
ar = np.array([[1, 2, 2], [4, 1, 1], [3, 1, 1]])
# print the array
print(ar)```

Output:

```[[1 2 2]
[4 1 1]
[3 1 1]]```

Here, we created a 2-D Numpy array with three rows and three columns. You can see that this array contains a duplicate column (the second and the third columns are duplicates).

Let’s now remove the duplicate columns using the `np.unique()` function.

```# remove duplicate columns from numpy array
print(np.unique(ar, axis=1))```

Output:

```[[1 2]
[4 1]
[3 1]]```

The resulting Numpy array contains only the unique columns from the original array.

## Summary – Remove duplicates in Numpy

In this tutorial, we looked at how to remove duplicates from a Numpy array. The following is a short summary of the important points mentioned in this tutorial –

• Use the `np.unique()` function to remove duplicates from a Numpy array.
• Pass `axis=0` to the `np.unique()` function to remove duplicate rows from a 2-D Numpy array.
• Pass `axis=1` to the `np.unique()` function to remove duplicate columns from a 2-D Numpy array.

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