Grouped bar charts in Matplotlib - Mini Project: Build & Apply

Grouped Bar Charts

📖 Scenario: You work in a small store that sells two types of fruits: apples and oranges. You want to compare the sales of these fruits over three months to see which fruit sold better each month.

🎯 Goal: Create a grouped bar chart to visually compare the monthly sales of apples and oranges side by side.

📋 What You'll Learn

Create a dictionary called sales with keys as months and values as another dictionary with keys 'apples' and 'oranges' and their sales numbers.

Create a list called months containing the months in order.

Create a variable called bar_width to set the width of each bar.

Use matplotlib.pyplot to plot grouped bars for apples and oranges for each month.

Add labels for the x-axis, y-axis, and a title for the chart.

Add a legend to distinguish apples and oranges.

💡 Why This Matters

🌍 Real World

Grouped bar charts help compare multiple categories across different groups, like sales of different products over months.

💼 Career

Data analysts and scientists use grouped bar charts to visualize and communicate comparisons clearly to stakeholders.

1

Create the sales data dictionary

Create a dictionary called sales with these exact entries: 'January': {'apples': 30, 'oranges': 25}, 'February': {'apples': 40, 'oranges': 35}, and 'March': {'apples': 35, 'oranges': 30}.

Matplotlib

# Create the sales dictionary with exact values
# Your code here

Hint

Use a dictionary with months as keys and another dictionary for fruit sales as values.

2

Set up months list and bar width

Create a list called months with the values 'January', 'February', and 'March'. Then create a variable called bar_width and set it to 0.35.

Matplotlib

sales = {
    'January': {'apples': 30, 'oranges': 25},
    'February': {'apples': 40, 'oranges': 35},
    'March': {'apples': 35, 'oranges': 30}
}
# Create the months list and bar_width variable
# Your code here

Hint

Use a list for months and a float for bar_width.

3

Plot the grouped bar chart

Import matplotlib.pyplot as plt. Create two lists called apples_sales and oranges_sales that contain the sales numbers for apples and oranges for each month in order. Create a list called positions using range(len(months)). Plot grouped bars for apples and oranges using plt.bar with positions and positions + bar_width for x positions. Add x-axis labels using plt.xticks at the middle of the grouped bars with the month names. Add labels for x-axis as 'Months', y-axis as 'Sales', and a title 'Monthly Fruit Sales'. Add a legend for apples and oranges.

Matplotlib

sales = {
    'January': {'apples': 30, 'oranges': 25},
    'February': {'apples': 40, 'oranges': 35},
    'March': {'apples': 35, 'oranges': 30}
}

months = ['January', 'February', 'March']
bar_width = 0.35

# Import matplotlib.pyplot as plt
# Create apples_sales and oranges_sales lists
# Create positions list
# Plot grouped bars for apples and oranges
# Add x-axis labels, y-axis labels, title, and legend
# Your code here

Hint

Use list comprehensions to get sales lists. Use plt.bar twice with shifted positions for grouped bars.

4

Display the grouped bar chart

Add a line to display the plot using plt.show().

Matplotlib

import matplotlib.pyplot as plt

sales = {
    'January': {'apples': 30, 'oranges': 25},
    'February': {'apples': 40, 'oranges': 35},
    'March': {'apples': 35, 'oranges': 30}
}

months = ['January', 'February', 'March']
bar_width = 0.35

apples_sales = [sales[month]['apples'] for month in months]
oranges_sales = [sales[month]['oranges'] for month in months]

positions = list(range(len(months)))

plt.bar(positions, apples_sales, width=bar_width, label='Apples')
plt.bar([p + bar_width for p in positions], oranges_sales, width=bar_width, label='Oranges')

plt.xticks([p + bar_width / 2 for p in positions], months)
plt.xlabel('Months')
plt.ylabel('Sales')
plt.title('Monthly Fruit Sales')
plt.legend()

# Display the plot
# Your code here

Hint

Use plt.show() to display the chart.

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