Introduction

In this tutorial, we want to create a Boxplot. In order to do this, we use the boxplot() 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
import pandas as pd

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=(20,5))

print(exam_result)

Create DataFrame

Now, we would like to store our generated data in a DataFrame:

df = pd.DataFrame(exam_result, columns=['Machine Learning',
                                        'Statistics', 
                                        'Computer Science', 
                                        'Neural Networks', 
                                        'Economics'])
print(df)

Plot Boxplot

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

#Set figure size
f = plt.figure()
f.set_figwidth(12)
f.set_figheight(8)

# plotting the boxplot
boxplot = sns.boxplot(data = df)
  
# displaying the boxplot
plt.xlabel("Exam")
plt.ylabel("Points")
plt.tight_layout()
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 Boxplot. We can simply use the boxplot() function of Seaborn. Try it yourself!

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