## Introduction

In this tutorial, we want to **join NumPy arrays **along different axes. In order to do this, we use the functions **hstack()**, **vstack() **and **dstack()** of **NumPy.**

## Import Libraries

First, we import the following python module**:**

```
import numpy as np
```

## Define Data

Let's consider two arrays a and b.

### Array a

```
a = np.array([5,7,8])
print(a)
```

`a.shape`

### Array b

```
b = np.array([4,2,1])
print(b)
```

`b.shape`

**Horizontal Stacking**

For stacking a sequence of arrays horizontally (column wise), the NumPy function **hstack()** can be used. The arrays are joined together along the first axis.

```
hstacked = np.hstack((a,b))
print(hstacked)
```

`hstacked.shape`

**Vertical Stacking**

For stacking a sequence of arrays vertically (row wise), the NumPy function **vstack()** can be used. The arrays are joined together along the second axis.

```
vstacked = np.vstack((a,b))
print(vstacked)
```

`vstacked.shape`

## Depth Wise Stacking

For stacking a sequence of arrays depth wise, the NumPy function **dstack()** can be used. The arrays are joined together along the third axis.

```
dstacked = np.dstack((a,b))
print(dstacked)
```

`dstacked.shape`

## Conclusion

Congratulations! Now you are one step closer to become an **AI Expert**. You have seen that it is very easy to **join NumPy arrays **along different axes. We can simply use the functions **hstack()**, **vstack() **and **dstack()** of **NumPy**. Try it yourself!

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