# np.expand_dims: What is numpy expand_dims() Function

Numpy expand_dims() method expands the shape of an array. The np expand_dims inserts a new axis that will appear at the axis position in the expanded array shape.

## np.expand_dims

The np.expand_dims() is a mathematical library function that expands the array by inserting a new axis at the specified position. This function requires two parameters.

### Syntax

```np.expand_dims(arr, axis)
```

### Parameters

arr: The arr is a required parameter, and it is an input array.

axis: Position where a new axis is to be inserted.

### Example of numpy expand_dims()

See the following code.

```# app.py

import numpy as np

x = np.array([11, 21])

print('Array x:', x)
print('x shape: ', x.shape)
```

#### Output

```python3 app.py
Array x: [11 21]
x shape:  (2,)```

Now, let’s expand the dimension on the x-axis. Write the following code.

```# app.py

import numpy as np

x = np.array([11, 21])

print('Array x:', x)
print('x shape: ', x.shape)

y = np.expand_dims(x, axis=0)
print(y)
print('y shape: ', y.shape)```

#### Output

```python3 app.py
Array x: [11 21]
x shape:  (2,)
[[11 21]]
y shape:  (1, 2)```

The y is the result of adding a new dimension to x.

From the output, you can see that we have added a new dimension on axis = 0.

```# app.py

import numpy as np

x = np.array(([11, 21], [19, 18]))

print('Array x:', x)
print('\n')

# insert axis at position 0
y = np.expand_dims(x, axis=0)

print('Array y:')
print(y)
print('\n')

print('The shape of X and Y array:')
print(x.shape, y.shape)
print('\n')

# insert axis at position 1
y = np.expand_dims(x, axis=1)

print('Array Y after inserting axis at position 1:')
print(y)
print('\n')

print('x.ndim and y.ndim:')
print(x.ndim, y.ndim)
print('\n')

print('x.shape and y.shape:')
print(x.shape, y.shape)
```

#### Output

```python3 app.py
Array x: [[11 21]
[19 18]]

Array y:
[[[11 21]
[19 18]]]

The shape of X and Y array:
(2, 2) (1, 2, 2)

Array Y after inserting axis at position 1:
[[[11 21]]

[[19 18]]]

x.ndim and y.ndim:
2 3

x.shape and y.shape:
(2, 2) (2, 1, 2)```

In this example, we can see that using Numpy.expanded_dims() method, and we can get the expanded array using this method.

That’s it for this tutorial.