Introduction

In this tutorial, we want to create a Heatmap. In order to do this, we use the heatmap() function of Seaborn.

Import Libraries

First, we import the following python modules:

import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np

Define Data

Let's define our example data. We consider the exam results of a university class. The number of points ranges from 0 to 100. We consider a class with 20 students that took part in five exams.

exam_result = np.random.randint(100, size=(5,20))

print(exam_result)

Plot Heatmap

Now, we would like to visualize the exam results with a heatmap. In order to do this, we use the heatmap() function of Seaborn.

# plotting the heatmap
hm = sns.heatmap(data = exam_result, cmap='Blues',
                yticklabels = ('Machine Learning', 'Statistics', 'Computer Science', 
                               'Neural Networks', 'Economics'))
  
# displaying the heatmap
plt.xlabel("Student Number")
plt.ylabel("Exam")
plt.show()

Conclusion

Congratulations! Now you are one step closer to become an AI Expert. You have seen that it is very easy to create a Heatmap. We can simply use the heatmap() function of Seaborn. Try it yourself!

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