You can use the numpy `append()`

function to append values to a numpy array. In this tutorial, we’ll look at the syntax and usage of the numpy `append()`

function through some examples.

## Numpy `append()`

function

It is used to append values at the end of an array. Note that it does not modify the original array. Rather, the values are appended to a copy of the original array and the resulting array is returned. The following is its syntax:

new_arr = numpy.append(arr, values, axis=None)

**Parameters:**

**arr**: The original array to append the values on (*Values are appended to a copy of this array*).**values**: The values to be appended.**axis**(*optional*): The axis along which the values are to be appended. If the axis is not provided,`arr`

and`values`

are flattened before appending.

**Returns:**

A copy of the original array (a numpy ndarray object) with the values appended along the given axis.

## Examples

Let’s look at some of the use-cases of the `append()`

function through examples –

### 1. Append values to a 1D array

import numpy as np # create a sample array arr = np.array([1,2,3,4]) # append values to arr new_arr = np.append(arr, [5,6,7]) # print print("Appended Array:", new_arr) print("Type:", type(new_arr))

Output:

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Appended Array: [1 2 3 4 5 6 7] Type: <class 'numpy.ndarray'>

In the above example, note that we didn’t provide an axis. The `append()`

function thus flattened the array and value to be appended and returned the resulting array.

### 2. Append a new row to a 2D array

Suppose you have a 2D array, and you want to append a new row to it. You can do so by using the `append()`

function and setting the `axis`

parameter to `0`

.

import numpy as np # create a sample array arr = np.array([[1,2,3],[4,5,6]]) # append values to arr new_arr = np.append(arr, [7,8,9], axis=0) # print print("Original array:\n", arr) print("Appended Array:\n", new_arr)

Output:

--------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-14-2f4ac95a52b4> in <module> 3 arr = np.array([[1,2,3],[4,5,6]]) 4 # append values to arr ----> 5 new_arr = np.append(arr, [7,8,9], axis=0) 6 # print 7 print("Original array:\n", arr) ValueError: all the input arrays must have same number of dimensions, but the array at index 0 has 2 dimension(s) and the array at index 1 has 1 dimension(s)

**Some lines in the above error message are skipped to focus on main reason for the error.*

When appending values along a specific axis, the array and the values to be appended should have the correct shapes. In the above example, we want to add a row to an array of shape `(2, 3)`

, thus, the values to be appended should also have similar dimensions, but the array `[7,8,9]`

has shape `(3,)`

. To append it as a row, it must be modified so that the dimensions match. See the corrected example below:

import numpy as np # create a sample array arr = np.array([[1,2,3],[4,5,6]]) # append values to arr new_arr = np.append(arr, [[7,8,9]], axis=0) # print print("Original array:\n", arr) print("Appended Array:\n", new_arr)

Output:

Original array: [[1 2 3] [4 5 6]] Appended Array: [[1 2 3] [4 5 6] [7 8 9]]

Here, the array `[[7,8,9]]`

has shape `(1, 3)`

which is compatible to be appended as a row to the original `(2, 3)`

array.

### 3. Append a new column to a 2D array

Suppose you have a 2D array, and you want to append a new column to it. You can do so by using the `append()`

function and setting the `axis`

parameter to `1`

. Like the above example, make sure that the shapes are compatible to be appended along the particular axis.

import numpy as np # create a sample array arr = np.array([[1,1,1],[2,2,2]]) values = np.array([1,2]).reshape(2,1) # append values to arr new_arr = np.append(arr, values, axis=1) # print print("Original array:\n", arr) print("Appended Array:\n", new_arr)

Output:

Original array: [[1 1 1] [2 2 2]] Appended Array: [[1 1 1 1] [2 2 2 2]]

In the above examples, `values`

is reshaped so that it can be appended to the `arr`

along `axis=1`

.

## Keep in mind

You know that numpy arrays are objects of the numpy ndarray class but it’s important to keep in mind that `append()`

is a function of the numpy class and not the numpy ndarray class. Thus, you cannot directly call the `append()`

function from a numpy array like this –

import numpy as np arr = np.array([1,2,3,4]) # This gives error print(arr.append([5,6,7]))

Output:

--------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <ipython-input-26-bf9bf23e0201> in <module> 2 arr = np.array([1,2,3,4]) 3 # This gives error ----> 4 print(arr.append([5,6,7])) AttributeError: 'numpy.ndarray' object has no attribute 'append'

If you want to use the `append()`

function, you’ll have call it through numpy directly. Like this –

import numpy as np arr = np.array([1,2,3,4]) # This gives error print(np.append(arr, [5,6,7]))

Output:

[1 2 3 4 5 6 7]

For more on the numpy `append()`

function, refer to its official documentation.

With this, we come to the end of this tutorial. The code examples and results presented in this tutorial have been implemented in a Jupyter Notebook with a python (version 3.8.3) kernel having numpy version 1.18.5

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