0Dumbbell charts help compare two related values side by side for each item. They make it easy to see differences and changes.
import matplotlib.pyplot as plt # Data categories = ['A', 'B', 'C'] value1 = [10, 20, 15] value2 = [15, 18, 20] # Plot plt.hlines(y=categories, xmin=value1, xmax=value2, color='gray') plt.scatter(value1, categories, color='blue', label='Value 1') plt.scatter(value2, categories, color='red', label='Value 2') plt.legend() plt.show()
Use hlines to draw horizontal lines between two values.
Use scatter to plot points at each value.
import matplotlib.pyplot as plt categories = ['X', 'Y'] val1 = [5, 7] val2 = [8, 6] plt.hlines(y=categories, xmin=val1, xmax=val2, color='black') plt.scatter(val1, categories, color='green') plt.scatter(val2, categories, color='orange') plt.show()
import matplotlib.pyplot as plt categories = ['Item1', 'Item2', 'Item3'] val1 = [12, 9, 14] val2 = [15, 11, 13] plt.hlines(categories, val1, val2, color='purple', linewidth=2) plt.scatter(val1, categories, color='purple', s=100) plt.scatter(val2, categories, color='orange', s=100) plt.title('Dumbbell Chart Example') plt.show()
This program creates a dumbbell chart comparing sales for 2023 and 2024 for four products. Lines connect the two sales values for each product, and points show exact sales.
import matplotlib.pyplot as plt # Categories and two sets of values categories = ['Product A', 'Product B', 'Product C', 'Product D'] sales_2023 = [200, 340, 300, 280] sales_2024 = [220, 310, 330, 290] # Draw lines between sales of 2023 and 2024 plt.hlines(y=categories, xmin=sales_2023, xmax=sales_2024, color='gray', linewidth=2) # Plot sales points for each year plt.scatter(sales_2023, categories, color='blue', label='2023 Sales', s=100) plt.scatter(sales_2024, categories, color='red', label='2024 Sales', s=100) # Add labels and legend plt.xlabel('Sales') plt.title('Sales Comparison Dumbbell Chart') plt.legend() plt.show()
Make sure your two value lists have the same length as the categories list.
You can customize colors and sizes of points to improve clarity.
Dumbbell charts work best when comparing exactly two values per category.
Dumbbell charts show two values side by side for easy comparison.
Use horizontal lines and scatter points to build the chart in matplotlib.
They help visualize changes or differences clearly.
dumbbell chart in data visualization?hlines draws horizontal lines, scatter plots points, so these two create dumbbell charts.hlines and scatter -> Option Dimport matplotlib.pyplot as plt categories = ['A', 'B'] start = [1, 3] end = [4, 5] plt.hlines(y=categories, xmin=start, xmax=end, color='gray') plt.scatter(start, categories, color='blue') plt.scatter(end, categories, color='red') plt.show()
plt.hlines(y=categories, xmin=start, xmax=end, color='gray') fails because y-coordinates must be numeric, but categories=['A', 'B'] are strings. Raises ValueError: could not convert string to float.plt.scatter(start, categories) and subsequent scatter require numeric y-values, leading to the same error.import matplotlib.pyplot as plt categories = ['X', 'Y'] start = [2, 4] end = [5, 7] plt.hlines(y=categories, xmin=start, xmax=end) plt.scatter(start, categories) plt.scatter(end, categories) plt.show()
hlines and scatter both require numeric y-values. Passing string categories as y causes ValueError (cannot convert string to float).y_pos = list(range(len(categories))), use y=y_pos in hlines and scatters, then plt.yticks(y_pos, categories).products = ['P1', 'P2', 'P3', 'P4'], sales_2022 = [100, 150, 200, 130], sales_2023 = [120, 140, 210, 160]. How would you create a dumbbell chart to compare sales changes using matplotlib?hlines draws lines between sales_2022 and sales_2023 at y=products; scatter plots points for each year's sales.plt.hlines with y as products, xmin as sales_2022, xmax as sales_2023, and plt.scatter for points -> Option APass the test and this pattern moves unknown strong while earning +1 Grip toward your certificate.