Before-after comparison plots in Matplotlib - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of a simple before-after bar plot

What will be the output of this code that plots before and after values side by side?

Matplotlib

import matplotlib.pyplot as plt

before = [5, 7, 9]
after = [6, 8, 10]
labels = ['A', 'B', 'C']

x = range(len(labels))
plt.bar(x, before, width=0.4, label='Before', align='center')
plt.bar([i + 0.4 for i in x], after, width=0.4, label='After', align='center')
plt.xticks([i + 0.2 for i in x], labels)
plt.legend()
plt.show()

A A bar chart with two bars per label: 'Before' bars at positions 0,1,2 and 'After' bars shifted right by 0.4, with labels A, B, C centered between bars.

B A line plot connecting before and after values for each label.

C A scatter plot with before values on x-axis and after values on y-axis.

D A pie chart showing proportions of before and after values combined.

💡 Hint

Look at how the bars are positioned with the x values and the width parameter.

The code creates two bar charts side by side for each label by shifting the 'after' bars by 0.4 on the x-axis. The xticks are set to be centered between the two bars for each label.

❓ data_output

intermediate

Number of bars in a before-after plot

Given two lists of values for before and after, how many bars will be shown in a grouped bar plot?

Matplotlib

before = [3, 4, 5, 6]
after = [4, 5, 6, 7]
# Plotting code groups bars side by side for each index

A 16 bars total

B 4 bars total

C 2 bars total

D 8 bars total

💡 Hint

Each index has one 'before' and one 'after' bar.

There are 4 indices, each with 2 bars (before and after), so total bars = 4 * 2 = 8.

❓ visualization

advanced

Identify the correct code for a before-after line plot with markers

Which code snippet correctly creates a before-after comparison line plot with markers for each point?

A

plt.hist(before, label='Before')
plt.hist(after, label='After')
plt.legend()
plt.show()

B

plt.bar(x, before, label='Before')
plt.bar(x, after, label='After')
plt.legend()
plt.show()

C

plt.plot(x, before, marker='o', label='Before')
plt.plot(x, after, marker='o', label='After')
plt.legend()
plt.show()

D

plt.scatter(x, before, label='Before')
plt.scatter(x, after, label='After')
plt.legend()
plt.show()

💡 Hint

Look for line plots with markers, not bars or histograms.

Option C uses plt.plot with markers to show lines connecting before and after values, which is typical for before-after comparison line plots.

🔧 Debug

advanced

Identify the error in this before-after bar plot code

What error will this code produce when run?

Matplotlib

import matplotlib.pyplot as plt
before = [1, 2, 3]
after = [2, 3, 4]
labels = ['X', 'Y', 'Z']

x = range(len(labels))
plt.bar(x, before, width=0.5, label='Before')
plt.bar([i + 0.5 for i in x], after, width=0.5, label='After')
plt.xticks(x, labels)
plt.legend()
plt.show()

A TypeError: unsupported operand type(s) for +: 'range' and 'float'

B No error, plot shows correctly

C ValueError: x and height must have same first dimension

D IndexError: list index out of range

💡 Hint

Check the operation on the range object in plt.bar second call.

You cannot add a float to a range object directly. You need to convert range to a list or use a list comprehension.

🚀 Application

expert

Calculate and plot percentage change before and after

Given before and after values, which code correctly calculates the percentage change and plots it as a bar chart?

Matplotlib

import matplotlib.pyplot as plt
before = [10, 20, 30]
after = [15, 18, 33]
labels = ['P', 'Q', 'R']

A

pct_change = [(b - a) / a * 100 for a, b in zip(before, after)]
plt.bar(labels, pct_change)
plt.ylabel('Percentage Change (%)')
plt.show()

B

pct_change = [(a - b) / b * 100 for b, a in zip(before, after)]
plt.bar(labels, pct_change)
plt.ylabel('Percentage Change (%)')
plt.show()

C

pct_change = [(a / b) * 100 for b, a in zip(before, after)]
plt.bar(labels, pct_change)
plt.ylabel('Percentage Change (%)')
plt.show()

D

pct_change = [a - b for b, a in zip(before, after)]
plt.bar(labels, pct_change)
plt.ylabel('Percentage Change (%)')
plt.show()

💡 Hint

Percentage change formula is (new - old) / old * 100.

Option B correctly computes percentage change as (after - before) / before * 100 and plots it.