Why categorical visualization matters in Matplotlib - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the matplotlib plotting library.

Matplotlib

import [1] as plt

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Aseaborn

Bmatplotlib.pyplot

Cpandas

Dnumpy

Attempts:

3 left

💡 Hint

Common Mistakes

Importing the whole matplotlib instead of pyplot

Using seaborn or pandas instead of matplotlib.pyplot

Forgetting the 'as plt' alias

We import matplotlib.pyplot as plt to create plots.

2fill in blank

medium

Complete the code to create a bar chart for categories and their counts.

Matplotlib

categories = ['A', 'B', 'C']
counts = [10, 15, 7]
plt.[1](categories, counts)
plt.show()

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Ascatter

Bhist

Cplot

Dbar

Attempts:

3 left

💡 Hint

Common Mistakes

Using plot or scatter which are better for continuous data

Using hist which is for numerical distributions

The bar function creates bar charts, which are good for categorical data.

3fill in blank

hard

Fix the error in the code to label the x-axis with category names.

Matplotlib

plt.bar([1, 2, 3], [5, 7, 3])
plt.xticks([1, 2, 3], [1])
plt.show()

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A['A', 'B', 'C']

B['5', '7', '3']

C[5, 7, 3]

D[1, 2, 3]

Attempts:

3 left

💡 Hint

Common Mistakes

Using counts or positions as labels instead of category names

Passing numbers instead of strings for labels

The xticks function sets the labels on the x-axis. We want to label the bars with category names.

4fill in blank

hard

Fill both blanks to create a horizontal bar chart with labels and title.

Matplotlib

plt.[1](counts, categories)
plt.xlabel('[2]')
plt.title('Category Counts')
plt.show()

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Abarh

Bbar

CCounts

DCategories

Attempts:

3 left

💡 Hint

Common Mistakes

Using bar instead of barh for horizontal bars

Labeling the x-axis as 'Categories' instead of 'Counts'

barh creates horizontal bars. The x-axis label should describe the counts.

5fill in blank

hard

Fill all three blanks to create a pie chart with labels and percentage display.

Matplotlib

plt.[1](counts, labels=[2], autopct='[3]')
plt.title('Category Distribution')
plt.show()

Drag options to blanks, or click blank then click option'

Apie

Bcategories

C%1.1f%%

Dbar

Attempts:

3 left

💡 Hint

Common Mistakes

Using bar instead of pie for pie charts

Not passing labels or passing wrong labels

Incorrect format string for autopct

The pie function creates pie charts. Labels are category names. autopct formats percentages.