Why annotations tell the data story in Matplotlib - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to add a title to the plot.

Matplotlib

plt.plot(x, y)
plt.[1]('Sales Over Time')
plt.show()

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

Atitle

Bxlabel

Cylabel

Dlegend

Attempts:

3 left

💡 Hint

Common Mistakes

Using xlabel or ylabel instead of title.

Forgetting to call plt.show() to display the plot.

The title function adds a title to the plot, which helps tell the story of the data.

2fill in blank

medium

Complete the code to add an annotation pointing to the highest sales point.

Matplotlib

max_index = y.index(max(y))
plt.plot(x, y)
plt.annotate('Peak Sales', xy=(x[max_index], y[max_index]), xytext=(x[max_index], y[max_index]+5), arrowprops={'arrowstyle': '[1]'})
plt.show()

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A<-

B-|>

C<->

D->

Attempts:

3 left

💡 Hint

Common Mistakes

Using arrow styles that point backwards or double arrows.

Not setting arrowprops correctly.

The arrow style '->' draws a simple arrow pointing from the text to the data point.

3fill in blank

hard

Fix the error in the annotation code by completing the missing parameter.

Matplotlib

plt.plot(x, y)
plt.annotate('Lowest Point', xy=(x[0], y[0]), xytext=(x[0], y[0]-5), [1]={'arrowstyle': '->'})
plt.show()

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Atextprops

Barrowprops

Clabel

Dfontsize

Attempts:

3 left

💡 Hint

Common Mistakes

Using textprops instead of arrowprops.

Omitting the arrowprops parameter.

The arrowprops parameter is required to define the arrow style in annotations.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that annotates points with sales above 50.

Matplotlib

annotations = {x: y[1] for x, y in data.items() if y [2] 50}

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A**2

B>

C>=

D*2

Attempts:

3 left

💡 Hint

Common Mistakes

Using exponentiation instead of multiplication.

Using less than operators instead of greater than.

The comprehension doubles the sales values (using *2) and filters for sales greater than 50.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that annotates words longer than 3 letters with their uppercase form.

Matplotlib

annotations = { [1]: [2] for word in words if len(word) [3] 3 }

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Aword.upper()

Bword

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping keys and values.

Using less than instead of greater than in the condition.

The comprehension uses the word as key, its uppercase as value, and filters words longer than 3 letters.