Why interactivity enhances exploration in Matplotlib - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the matplotlib library for plotting.

Matplotlib

import [1] as plt

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

Apandas

Bseaborn

Cnumpy

Dmatplotlib.pyplot

Attempts:

3 left

💡 Hint

Common Mistakes

Importing the whole matplotlib instead of pyplot.

Using unrelated libraries like pandas or numpy for plotting.

We import matplotlib.pyplot as plt to create plots.

2fill in blank

medium

Complete the code to enable interactive mode in matplotlib.

Matplotlib

plt.[1]()

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

Aion

Bshow

Cinteractive

Dplot

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.show(True) which does not enable interactive mode.

Trying plt.interactive(True) which is not a valid function.

The ion() function turns on interactive mode in matplotlib.

3fill in blank

hard

Fix the error in the code to update the plot dynamically.

Matplotlib

plt.plot(x, y)
plt.[1]()

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

Apause

Bdraw

Cshow

Dupdate

Attempts:

3 left

💡 Hint

Common Mistakes

Using plt.show() which blocks execution.

Using plt.pause() without arguments.

After plotting, plt.draw() refreshes the figure in interactive mode.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that filters data points with y values greater than 5.

Matplotlib

filtered_points = {x: y for x, y in data.items() if y [1] 5 and 'point' [2] x}

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

A>

B<

Cin

Dnot in

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' for filtering.

Using 'not in' which excludes keys containing 'point'.

The comprehension keeps points where y is greater than 5 and the key contains 'point'.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that converts keys to uppercase, keeps values, and filters values greater than 10.

Matplotlib

result = { [1]: [2] for k, v in data.items() if v [3] 10 }

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

Ak.lower()

Bv

C>

Dk.upper()

Attempts:

3 left

💡 Hint

Common Mistakes

Using k.lower() instead of k.upper() for keys.

Using '<' instead of '>' for filtering values.

This comprehension changes keys to uppercase, keeps values, and filters values greater than 10.