Using the Add Function

Introduction

In this tutorial, we will go through the steps to use the add() function of the NumPy library. The add() function can concatenate the elements of two arrays. However, it requires that both arrays are of the same shape.

Prerequisites

To follow this tutorial, you need to have a basic understanding of Python and NumPy.

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Skills Graph

Import NumPy

The first step is to import the NumPy library.

import numpy as np

Create Input Arrays

Next, let's create two input arrays that we can use to test the add() function.

x1 = ['Hello', 'World']
x2 = ['NumPy', 'Tutorial']

Apply the add() Function

To concatenate the elements of the two input arrays, we can use the add() function as shown below.

result = np.char.add(x1, x2)

Print the Result

Let's print the concatenated string array that we obtained in the previous step.

print(result)

The output will be:

array(['HelloNumPy', 'WorldTutorial'], dtype='<U14')

Apply the add() Function with Single Element Arrays

We can also apply the add() function if both arrays only have one element.

x1 = ['Hello']
x2 = ['StudyTonight!']
result = np.char.add(x1, x2)
print(result)

The output will be:

array(['HelloStudyTonight!'], dtype='<U18')

Apply the add() Function with Different Length Arrays

Finally, let's see what the add() function does when the input arrays have different lengths.

x1 = ['Welcome', 'to', 'StudyTonight']
x2 = ['Best Place', 'Forlearning']
result = np.char.add(x1, x2)
print(result)

The output will be a ValueError:

ValueError: shape mismatch: objects cannot be broadcast to a single shape

This is because the two arrays have different lengths and cannot be concatenated.

Summary

In this tutorial, we have learned how to use the add() function in NumPy to concatenate elements of two arrays. We also learned that both arrays must be of the same shape for the function to work properly.