The **np.vstack()** is a **numpy** **library** function that **returns an array in the vertically stacked order. **The **vstack stands **for a** vertical stack. **The **np.vstack() **function returns an array that combines the first array followed by the second array. The **np.vstack()** function stacks the second array after the first array.

To horizontal stack array elements in Python, use the **np.hstack() **function.

Let’s see the syntax of the **numpy vstack()** method.

**Syntax**

`numpy.vstack(tup)`

**Parameters**

The **np.vstack()** function takes one required arguments as a parameter:

**tup**: The arrays are passed inside the tuple. From these arrays, the **np.vstack()** function returns the new array that contains values from the first array, followed by the values from the second array. It is the required argument for returning the vertically stacked array. The **np.vstack()** function appends the value of the second array to the first array. The arrays should contain the same shape.

**Return value**

It returns the array. This array consists of all the elements from the first array and is followed by all the elements from the second array.

**Python program for returning the vertically stacked array using np.vstack() function**

```
# Importing numpy as np
import numpy as np
# Creating an numpy array called arr1
arr1 = np.array([4, 5, 6])
# Creating an numpy array called arr2
arr2 = np.array([7, 8, 9])
# Creating a vertically stacked array from arr1 and arr2
res = np.vstack((arr1, arr2))
print(res)
```

**Output**

```
[[4 5 6]
[7 8 9]]
```

In this program, we imported a numpy package that has functions for numerical calculations. Then, we have created two numpy arrays called **arr1** and **arr2** using the function called **np.array()**. Then, we passed these two arrays into the vstack function. The **np.vstack()** function combines array 1 and array 2 vertically and returns a combined array.

**Python program for returning the vertically stacked nested array using np.vstack()**

```
# Importing numpy as np
import numpy as np
# Creating an numpy array called arr1
arr1 = np.array([[4], [5], [6]])
# Creating an numpy array called arr2
arr2 = np.array([[7], [8], [9]])
# Creating a vertically stacked array from arr1 and arr2
res = np.vstack((arr1, arr2))
print(res)
```

**Output**

```
[[4]
[5]
[6]
[7]
[8]
[9]]
```

In this program, two nested arrays are created. These nested arrays are then passed to the **np.vstack(**) function. The **np.vstack()** function vertically stacks the **arr1** with the **arr2**. Hence, the resultant array is formed by appending the **arr2** in the **arr1** array. The **np.vstack()** function is similar to concatenating **arr2** with the **arr1 **using np.concatenate() function.

That’s it for numpy vstack() function.