Grouped bar charts in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the matplotlib library.

Matplotlib

import [1] as plt

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

Amatplotlib.pyplot

Bnumpy

Cpandas

Dseaborn

Attempts:

3 left

💡 Hint

Common Mistakes

Importing the wrong library like numpy or pandas.

Forgetting to import pyplot specifically.

We import matplotlib.pyplot as plt to create plots.

2fill in blank

medium

Complete the code to create a list of categories for the x-axis.

Matplotlib

categories = ['A', 'B', 'C', [1]]

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

A4

B'1'

C['D']

D'D'

Attempts:

3 left

💡 Hint

Common Mistakes

Using a number instead of a string for category.

Adding a list inside the list.

Categories should be strings representing groups, so 'D' is correct.

3fill in blank

hard

Fix the error in the code to set the width of each bar.

Matplotlib

bar_width = [1]

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

A1.5

B0.5

C5

D'0.5'

Attempts:

3 left

💡 Hint

Common Mistakes

Using a string instead of a number.

Using a width larger than 1 causing bars to overlap.

The bar width should be a float less than 1 to avoid overlap.

4fill in blank

hard

Fill both blanks to correctly calculate the x positions for the second group of bars.

Matplotlib

x2 = [x + [1] for x in x1]
plt.bar(x2, group2, width=[2], label='Group 2')

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

Abar_width

B0.1

Cbar_width / 2

Dbar_width * 2

Attempts:

3 left

💡 Hint

Common Mistakes

Using a smaller shift causing bars to overlap.

Using different widths causing uneven bars.

We shift the second group's bars by bar_width to place them side by side and use the same width.

5fill in blank

hard

Fill all three blanks to create a grouped bar chart with labels and legend.

Matplotlib

plt.bar(x1, [1], width=[2], label='Group 1')
plt.bar(x2, [3], width=bar_width, label='Group 2')
plt.legend()

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

Agroup1

Bbar_width

Cgroup2

Dcategories

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up data variables for groups.

Forgetting to add legend for clarity.

We plot group1 and group2 data with the same bar_width and add a legend to distinguish groups.

Practice

1. What is the main purpose of a grouped bar chart in data visualization?

easy

A. To compare multiple categories side by side within groups

B. To show the trend of a single variable over time

C. To display parts of a whole as percentages

D. To plot data points on a continuous scale

Solution

1. Step 1: Understand the chart type

   Grouped bar charts place bars for different categories next to each other for easy comparison.

2. Step 2: Identify the purpose

   This helps compare multiple categories side by side within groups, unlike line or pie charts.

3. Final Answer:

   To compare multiple categories side by side within groups -> Option A

4. Quick Check:

   Grouped bars = side-by-side comparison [OK]

Hint: Grouped bars show categories side by side for easy comparison [OK]

Common Mistakes:

• Confusing grouped bar charts with line charts
• Thinking grouped bars show parts of a whole
• Assuming grouped bars plot continuous data

2. Which of the following code snippets correctly shifts bars to create a grouped bar chart in matplotlib?

easy

A. plt.bar(x - width/2, data1, width); plt.bar(x + width/2, data2, width)

B. plt.bar(x, data1, width); plt.bar(x, data2, width)

C. plt.bar(x + width, data1, width); plt.bar(x + width, data2, width)

D. plt.bar(x - width, data1, width); plt.bar(x - width, data2, width)

Solution

1. Step 1: Understand bar shifting for grouping

   To group bars side by side, shift one set left by half the bar width and the other right by half the bar width.

2. Step 2: Check the code

   plt.bar(x - width/2, data1, width); plt.bar(x + width/2, data2, width) shifts bars by -width/2 and +width/2, correctly grouping them.

3. Final Answer:

   plt.bar(x - width/2, data1, width); plt.bar(x + width/2, data2, width) -> Option A

4. Quick Check:

   Shift bars ±width/2 for grouping [OK]

Hint: Shift bars by ±width/2 to group them side by side [OK]

Common Mistakes:

• Not shifting bars, causing overlap
• Shifting bars by full width, creating gaps
• Using the same x positions for all bars

3. What will be the output of the following code?

import matplotlib.pyplot as plt
import numpy as np

labels = ['A', 'B', 'C']
data1 = [5, 7, 9]
data2 = [6, 8, 10]
x = np.arange(len(labels))
width = 0.4

plt.bar(x - width/2, data1, width, label='Data1')
plt.bar(x + width/2, data2, width, label='Data2')
plt.xticks(x, labels)
plt.legend()
plt.show()

medium

A. A stacked bar chart with Data2 bars on top of Data1 bars

B. A grouped bar chart with bars for Data1 and Data2 side by side for each label

C. A line chart connecting data points for Data1 and Data2

D. A scatter plot with points at positions x and data values

Solution

1. Step 1: Analyze the bar positions

   Bars for data1 are at x - width/2, and for data2 at x + width/2, placing them side by side.

2. Step 2: Understand the plot type

   Using plt.bar twice with shifted x positions creates a grouped bar chart, not stacked or line chart.

3. Final Answer:

   A grouped bar chart with bars for Data1 and Data2 side by side for each label -> Option B

4. Quick Check:

   Shifted bars = grouped bar chart [OK]

Hint: Shift bars left and right to get grouped bars, not stacked [OK]

Common Mistakes:

• Thinking bars are stacked instead of grouped
• Confusing bar chart with line or scatter plot
• Ignoring the x-axis label positions

4. Identify the error in this grouped bar chart code:

import matplotlib.pyplot as plt
import numpy as np

labels = ['X', 'Y', 'Z']
data1 = [3, 5, 7]
data2 = [4, 6, 8]
x = np.arange(len(labels))
width = 0.3

plt.bar(x, data1, width, label='Data1')
plt.bar(x + width/2, data2, width, label='Data2')
plt.xticks(x, labels)
plt.legend()
plt.show()

medium

A. Legend labels are missing

B. Width is too large causing bars to be invisible

C. x positions are incorrect and cause an error

D. Bars overlap because data1 bars are not shifted left

Solution

1. Step 1: Check bar positions

   data1 bars are at x, data2 bars at x + width/2, so data1 bars are not shifted left to avoid overlap.

2. Step 2: Understand grouping logic

   To group bars, data1 should be at x - width/2 and data2 at x + width/2; otherwise, bars overlap.

3. Final Answer:

   Bars overlap because data1 bars are not shifted left -> Option D

4. Quick Check:

   Shift both bars ±width/2 to avoid overlap [OK]

Hint: Shift first bars left by width/2 to prevent overlap [OK]

Common Mistakes:

• Not shifting first bar set left
• Using full width shift causing gaps
• Ignoring bar width when setting positions

5. You have sales data for 3 products over 4 quarters:

products = ['P1', 'P2', 'P3']
quarters = ['Q1', 'Q2', 'Q3', 'Q4']
sales = [[10, 15, 20, 25], [12, 18, 22, 28], [14, 20, 24, 30]]

How would you create a grouped bar chart showing sales per quarter for each product using matplotlib?

hard

A. Use a line plot instead of bars for grouped comparison

B. Plot bars at x positions equal to product indices without shifting

C. Use x = np.arange(len(quarters)), width = 0.25, then plot bars for each product shifted by -width, 0, +width

D. Stack bars for all products at the same x positions for quarters

Solution

1. Step 1: Set x positions for quarters

   Use x = np.arange(len(quarters)) to represent each quarter on the x-axis.

2. Step 2: Define bar width and shifts

   Set width = 0.25 and shift bars for each product by -width, 0, and +width to group them side by side.

3. Step 3: Plot bars for each product

   Plot bars for each product's sales data at shifted x positions to create grouped bars per quarter.

4. Final Answer:

   Use x = np.arange(len(quarters)), width = 0.25, then plot bars for each product shifted by -width, 0, +width -> Option C

5. Quick Check:

   Shift bars by ±width around x for grouping [OK]

Hint: Shift bars by ±width around x for each product group [OK]

Common Mistakes:

• Not shifting bars causing overlap
• Using product indices as x instead of quarters
• Stacking bars instead of grouping