Storytelling with visualization sequence in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this matplotlib code sequence?

Consider the following Python code using matplotlib to create a sequence of plots. What will be the output shown after running this code?

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 10, 100)
y = np.sin(x)

plt.plot(x, y)
plt.title('Sine Wave')
plt.show()

plt.plot(x, np.cos(x))
plt.title('Cosine Wave')
plt.show()

A Two separate plots: first a sine wave, then a cosine wave, each with their own title.

B An error occurs because plt.show() is called twice.

C Only the sine wave plot is shown; the cosine plot is not displayed.

D One plot showing both sine and cosine waves together with the title 'Cosine Wave'.

💡 Hint

Think about what plt.show() does in matplotlib and how it affects the display of plots.

Each plt.show() call displays the current figure and clears it. So the first plot shows the sine wave, then the second plot shows the cosine wave separately.

❓ data_output

intermediate

How many data points are plotted in this sequence?

Given the code below, how many points are plotted in total across all plots?

Matplotlib

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 5, 50)

plt.plot(x, x**2)
plt.show()

plt.plot(x, np.sqrt(x))
plt.show()

A 25 points in total (split between two plots).

B 50 points in total (all in one plot).

C 50 points in total (25 in each plot).

D 100 points in total (50 in each plot).

💡 Hint

Check how many points are generated by np.linspace and how many plots are created.

np.linspace(0, 5, 50) creates 50 points. Each plot uses all 50 points, so total points plotted are 50 + 50 = 100.

❓ visualization

advanced

Identify the correct sequence of plots for storytelling

You want to tell a story showing data trends over time using three plots: a line plot, a bar chart, and a scatter plot. Which sequence best supports a clear storytelling flow?

A Scatter plot → Bar chart → Line plot

B Line plot → Bar chart → Scatter plot

C Line plot → Scatter plot → Bar chart

D Bar chart → Line plot → Scatter plot

💡 Hint

Think about introducing the trend first, then details, then individual points.

Starting with a line plot shows the overall trend, followed by a bar chart to compare categories, and ending with a scatter plot to show individual data points supports a clear story.

🔧 Debug

advanced

What error does this matplotlib code raise?

Examine the code below. What error will it raise when run?

Matplotlib

import matplotlib.pyplot as plt

plt.plot([1, 2, 3], [4, 5])
plt.show()

A ValueError: x and y must have same first dimension

B TypeError: 'list' object is not callable

C IndexError: list index out of range

D No error; plot displays correctly

💡 Hint

Check if the x and y data lists have the same length.

Matplotlib requires x and y data to have the same length. Here, x has 3 points but y has 2, causing a ValueError.

🚀 Application

expert

Which option produces a multi-plot storytelling figure with shared x-axis?

Which code snippet correctly creates a figure with 3 vertically stacked plots sharing the same x-axis for storytelling?

A

fig, axs = plt.subplots(3, 1)
axs[0].plot([1,2,3], [1,4,9])
axs[1].bar([1,2,3], [3,2,1])
axs[2].scatter([1,2,3], [2,3,1])
plt.show()

B

fig, axs = plt.subplots(1, 3, sharey=True)
axs[0].plot([1,2,3], [1,4,9])
axs[1].bar([1,2,3], [3,2,1])
axs[2].scatter([1,2,3], [2,3,1])
plt.show()

C

fig, axs = plt.subplots(3, 1, sharex=True)
axs[0].plot([1,2,3], [1,4,9])
axs[1].bar([1,2,3], [3,2,1])
axs[2].scatter([1,2,3], [2,3,1])
plt.show()

D

fig, axs = plt.subplots(3, 1, sharey=True)
axs[0].plot([1,2,3], [1,4,9])
axs[1].bar([1,2,3], [3,2,1])
axs[2].scatter([1,2,3], [2,3,1])
plt.show()

💡 Hint

Consider the layout and which axis should be shared for aligned storytelling.

Option C creates 3 rows (3,1) with shared x-axis, which aligns the plots vertically and shares the x-axis for better comparison.