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.

Practice

1. What is the main purpose of a before-after comparison plot in matplotlib?

easy

A. To visually compare data from two different time points

B. To show the distribution of a single dataset

C. To display the correlation between two variables

D. To create a 3D surface plot

Solution

1. Step 1: Understand the concept of before-after plots

   Before-after plots are used to compare data points from two different times or conditions to see changes.

2. Step 2: Identify the correct purpose

   Among the options, only To visually compare data from two different time points describes comparing data from two time points, which matches the before-after plot purpose.

3. Final Answer:

   To visually compare data from two different time points -> Option A

4. Quick Check:

   Before-after plots = compare two time points [OK]

Hint: Before-after plots compare two sets of data visually [OK]

Common Mistakes:

• Confusing before-after plots with distribution plots
• Thinking they show correlation instead of change
• Assuming they create 3D plots

2. Which of the following is the correct way to plot two sets of data side-by-side for before-after comparison using matplotlib?

easy

A. plt.plot(before_data); plt.plot(after_data)

B. plt.bar([0,1], before_data); plt.bar([0,1], after_data)

C. plt.bar([0,1], before_data); plt.bar([1,2], after_data)

D. plt.bar([1,2], [before_data, after_data])

Solution

1. Step 1: Understand bar plot positioning

   To show before and after side-by-side, bars must not overlap. Using different x positions for before and after data avoids overlap.

2. Step 2: Analyze options for correct bar positions

   plt.bar([0,1], before_data); plt.bar([1,2], after_data) places before_data at positions 0 and 1, and after_data at 1 and 2, so bars for the same category are side-by-side without overlap.

3. Final Answer:

   plt.bar([0,1], before_data); plt.bar([1,2], after_data) -> Option C

4. Quick Check:

   Side-by-side bars need different x positions [OK]

Hint: Use different x positions to avoid bar overlap [OK]

Common Mistakes:

• Plotting bars at same x positions causing overlap
• Using plt.plot instead of plt.bar for categorical data
• Passing data incorrectly as list of lists

3. What will be the output of this code snippet?

import matplotlib.pyplot as plt
before = [5, 7]
after = [8, 6]
plt.plot([1, 2], before, label='Before')
plt.plot([1, 2], after, label='After')
plt.legend()
plt.show()

medium

A. An error because plt.plot cannot take two lists

B. A bar chart comparing before and after data

C. A scatter plot with points at (1,5), (2,7), (1,8), (2,6)

D. Two overlapping line plots showing before and after data

Solution

1. Step 1: Understand plt.plot with x and y lists

   plt.plot([1, 2], before) plots points (1,5) and (2,7) connected by a line. Similarly for after data.

2. Step 2: Identify plot type and legend

   Two line plots will appear overlapping on the same axes with labels 'Before' and 'After'. No error occurs.

3. Final Answer:

   Two overlapping line plots showing before and after data -> Option D

4. Quick Check:

   plt.plot with x,y lists = line plot [OK]

Hint: plt.plot(x, y) draws lines connecting points [OK]

Common Mistakes:

• Thinking plt.plot creates bar charts
• Expecting scatter plot without plt.scatter
• Assuming plt.plot with two lists causes error

4. Identify the error in this code for before-after bar plot:

import matplotlib.pyplot as plt
before = [3, 4]
after = [5, 6]
plt.bar([0, 1], before)
plt.bar([0, 1], after)
plt.show()

medium

A. plt.show() is missing

B. Bars for before and after overlap at same positions

C. before and after lists must be same length

D. plt.bar requires three arguments

Solution

1. Step 1: Check bar positions

   Both before and after bars are plotted at positions 0 and 1, causing them to overlap and hide one another.

2. Step 2: Identify correct fix

   To avoid overlap, after bars should be shifted to different x positions, e.g., [0.3, 1.3].

3. Final Answer:

   Bars for before and after overlap at same positions -> Option B

4. Quick Check:

   Same x positions cause bar overlap [OK]

Hint: Shift bars on x-axis to avoid overlap [OK]

Common Mistakes:

• Thinking plt.bar needs 3 arguments
• Ignoring bar overlap issue
• Assuming plt.show() is missing

5. You have sales data before and after a marketing campaign for 3 products: before = [100, 150, 200], after = [120, 180, 210]. How would you create a clear before-after bar plot with labels and legend in matplotlib?

hard

A. Use plt.bar with shifted x positions for before and after, add labels and legend

B. Plot before and after using plt.plot without labels

C. Use plt.scatter for both datasets on same x positions

D. Plot only after data as a bar chart

Solution

1. Step 1: Plan bar positions and labels

   To compare before and after clearly, plot bars side-by-side with shifted x positions, e.g., before at [0,1,2], after at [0.3,1.3,2.3]. Add x-axis labels for products.

2. Step 2: Add legend and labels for clarity

   Use plt.legend() to distinguish before and after bars, and plt.xlabel/plt.ylabel for axis labels.

3. Final Answer:

   Use plt.bar with shifted x positions for before and after, add labels and legend -> Option A

4. Quick Check:

   Shift bars + labels + legend = clear before-after plot [OK]

Hint: Shift bars and add legend for clear comparison [OK]

Common Mistakes:

• Plotting bars at same positions causing confusion
• Skipping labels and legend
• Using scatter plot instead of bar plot