Why legends and colorbars guide reading in Matplotlib - See It in Action

Why legends and colorbars guide reading

📖 Scenario: Imagine you are creating a simple chart to show sales data for different products. You want to make sure anyone looking at your chart can easily understand which color means which product and what the color intensity means for sales volume.

🎯 Goal: You will create a bar chart with colors representing sales amounts. You will add a legend to explain the colors for products and a colorbar to explain the sales volume intensity. This will help readers understand the chart quickly and clearly.

📋 What You'll Learn

Create a dictionary with product names and their sales values

Create a list of colors for each product

Plot a bar chart with product names on the x-axis and sales values on the y-axis

Add a legend that shows which color belongs to which product

Add a colorbar that shows the sales volume intensity scale

💡 Why This Matters

🌍 Real World

Legends and colorbars are used in reports and dashboards to help people understand what different colors and intensities mean in charts.

💼 Career

Data analysts and scientists use legends and colorbars to make their visualizations clear and easy to read for decision makers.

1

Create the sales data dictionary

Create a dictionary called sales_data with these exact entries: 'Apples': 50, 'Bananas': 30, 'Cherries': 70, 'Dates': 40.

Matplotlib

# Create the sales_data dictionary with product names and sales values
# Your code here

Need a hint?

Use curly braces {} to create a dictionary with keys as product names and values as sales numbers.

2

Create the colors list for products

Create a list called colors with these exact color names in order: 'red', 'yellow', 'pink', 'brown'.

Matplotlib

sales_data = {'Apples': 50, 'Bananas': 30, 'Cherries': 70, 'Dates': 40}
# Create the colors list for each product
# Your code here

Need a hint?

Use square brackets [] to create a list of color names matching the products order.

3

Plot the bar chart with legend and colorbar

Use matplotlib.pyplot to plot a bar chart with product names on the x-axis and sales values on the y-axis. Use the colors list for the bar colors. Add a legend that shows which color belongs to which product using plt.legend(). Also, add a colorbar that shows sales volume intensity using matplotlib.cm.ScalarMappable and plt.colorbar().

Matplotlib

sales_data = {'Apples': 50, 'Bananas': 30, 'Cherries': 70, 'Dates': 40}
colors = ['red', 'yellow', 'pink', 'brown']
# Plot the bar chart with colors, add legend and colorbar
# Your code here

Need a hint?

Use ax.bar() to plot bars with colors. Use ax.legend() to add the legend. Use matplotlib.cm.ScalarMappable and plt.colorbar() to add the colorbar.

4

Display the plot

Use plt.show() to display the bar chart with legend and colorbar.

Matplotlib

import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as mcolors

sales_data = {'Apples': 50, 'Bananas': 30, 'Cherries': 70, 'Dates': 40}
colors = ['red', 'yellow', 'pink', 'brown']

products = list(sales_data.keys())
sales = list(sales_data.values())

fig, ax = plt.subplots()
bars = ax.bar(products, sales, color=colors)

# Add legend with product names and colors
for bar, product in zip(bars, products):
    bar.set_label(product)
ax.legend()

# Create a color map for sales volume
norm = mcolors.Normalize(vmin=min(sales), vmax=max(sales))
cmap = cm.ScalarMappable(norm=norm, cmap='Reds')
cmap.set_array(sales)

# Add colorbar to show sales volume intensity
plt.colorbar(cmap, ax=ax, label='Sales Volume Intensity')
# Display the plot
# Your code here

Need a hint?

Use plt.show() to display the chart window with legend and colorbar.