In this tutorial, we will cover the `numpy.append()`

function of the NumPy library.

The **“append”** word simply means** to add something** to the existing data at the end or at the last.

- In the NumPy library, the
`append()`

function is mainly used**to append or add something**to an existing array. - This function always append the
**values at the end of the array**and that too along the mentioned axis. - The
`append()`

function is mainly used**to merge two arrays**and**return a new array**as a result. - During this operation
**the original array remains unchanged**.

### Syntax of `numpy.append()`

:

The syntax required to use this function is as follows:

`numpy.append(a, values, axis=None)`

**Parameters:**

Let us take a look at the parameters of this function:

**a**This parameter indicates the ndarray to which the new values will be appended and a new array will be created.**values**This parameter is mainly used to define the values that are needed to append to the copy of**a**(the existing ndarray). It is important to note here that these values must be of the**correct shape**just like the original ndarray, only excluding the axis. In the case if the**axis is not defined**, then the values can be in any shape and**will be flattened**before the use.**axis**This is an**optional**parameter and is used to define the axis along which the values are appended. When the axis is not given then in that case both ndarray and values are flattened before use.

**Returned Values:**

The `append()`

function returns the copy of the ndarray along with the values appended to its axis.

## Example 1: Basic usage

Let us have a look at the basic example of this function and the code snippet for the same is as follows:

```
import numpy as np
a = np.array([[1, 2, 3], [7, 8, 9]])
b = np.array([[11, 21, 31], [42, 52, 62]])
print("The first array:\n",a)
print("The second array:\n",b)
print("The resultant array after appending a & b:")
c = np.append(a,b)
c
```

Output:

The output of the above code will be:

## Example 2: With axis=0

Let us have a look at another case where we will take **axis=0** and check the output:

```
import numpy as np
a=np.array([[1, 2, 3], [7, 8, 9]])
b=np.array([[11, 21, 31], [42, 52, 62]])
print("The first array:\n",a)
print("The second array:\n",b)
print("The resultant array after appending a & b:")
c=np.append(a,b,axis=0)
c
```

Output:

The output of the above code will be:

## Example 3: With axis=1

Let us have a look at another case where we will take **axis=1** and check the output:

```
import numpy as np
a=np.array([[1, 2, 3], [7, 8, 9]])
b=np.array([[11, 21, 31], [42, 52, 62]])
print("The first array:\n",a)
print("The second array:\n",b)
print("The resultant array after appending a & b:")
c=np.append(a,b,axis=1)
c
```

Output:

The output of the above code will be: