Dumbbell charts in Matplotlib - Mini Project: Build & Apply

Dumbbell charts

📖 Scenario: You are a data analyst at a fitness center. You want to compare the average weights lifted by two groups of people: beginners and advanced trainees. A dumbbell chart is a great way to show the difference between these two groups for each exercise.

🎯 Goal: Build a dumbbell chart using matplotlib to visually compare the average weights lifted by beginners and advanced trainees for different exercises.

📋 What You'll Learn

Create a dictionary with exercises as keys and tuples of (beginner weight, advanced weight) as values.

Create a list of exercises from the dictionary keys.

Extract beginner and advanced weights into separate lists.

Plot a dumbbell chart using matplotlib with lines connecting beginner and advanced weights for each exercise.

Label the axes and add a title.

💡 Why This Matters

🌍 Real World

Dumbbell charts are useful to compare two related values side-by-side for multiple categories, such as comparing performance before and after training.

💼 Career

Data analysts and scientists often create such charts to communicate differences clearly in reports and presentations.

1

Create the data dictionary

Create a dictionary called weights with these exact entries: 'Squat': (50, 100), 'Bench Press': (40, 90), 'Deadlift': (60, 120), 'Overhead Press': (30, 70), 'Barbell Row': (45, 95).

Matplotlib

# Your code here

Need a hint?

Use curly braces to create a dictionary. Each key is a string for the exercise, and each value is a tuple with two numbers.

2

Prepare lists for plotting

Create a list called exercises from the keys of weights. Then create two lists called beginner_weights and advanced_weights by extracting the first and second elements of the tuples in weights respectively.

Matplotlib

weights = {'Squat': (50, 100), 'Bench Press': (40, 90), 'Deadlift': (60, 120), 'Overhead Press': (30, 70), 'Barbell Row': (45, 95)}
# Your code here

Need a hint?

Use list(weights.keys()) to get the exercises. Use list comprehensions to get beginner and advanced weights.

3

Plot the dumbbell chart

Import matplotlib.pyplot as plt. Use plt.hlines to draw horizontal lines between beginner_weights and advanced_weights for each exercise index. Then use plt.scatter to plot the beginner and advanced weights as points. Set the y-axis ticks to exercises.

Matplotlib

weights = {'Squat': (50, 100), 'Bench Press': (40, 90), 'Deadlift': (60, 120), 'Overhead Press': (30, 70), 'Barbell Row': (45, 95)}
exercises = list(weights.keys())
beginner_weights = [weights[ex][0] for ex in exercises]
advanced_weights = [weights[ex][1] for ex in exercises]
# Your code here

Need a hint?

Use plt.hlines to draw lines, and plt.scatter to plot points. Use range(len(exercises)) for y positions.

4

Display the chart

Add plt.show() to display the dumbbell chart.

Matplotlib

import matplotlib.pyplot as plt

weights = {'Squat': (50, 100), 'Bench Press': (40, 90), 'Deadlift': (60, 120), 'Overhead Press': (30, 70), 'Barbell Row': (45, 95)}
exercises = list(weights.keys())
beginner_weights = [weights[ex][0] for ex in exercises]
advanced_weights = [weights[ex][1] for ex in exercises]

plt.hlines(y=range(len(exercises)), xmin=beginner_weights, xmax=advanced_weights, color='gray', alpha=0.7)
plt.scatter(beginner_weights, range(len(exercises)), color='blue', label='Beginner')
plt.scatter(advanced_weights, range(len(exercises)), color='red', label='Advanced')
plt.yticks(range(len(exercises)), exercises)
plt.xlabel('Weight (kg)')
plt.title('Dumbbell Chart: Beginner vs Advanced Weights')
plt.legend()
# Your code here

Need a hint?

Use plt.show() to display the plot window.