Custom colormaps in Matplotlib - Mini Project: Build & Apply

Custom colormaps

📖 Scenario: You are working with a heatmap that shows temperature data for a week. You want to make the colors more meaningful by creating your own color scale.

🎯 Goal: Create a custom colormap using matplotlib and apply it to a heatmap of temperature data.

📋 What You'll Learn

Create a 2D list called temperatures with exact values for 7 days and 3 times per day

Create a custom colormap named my_cmap using LinearSegmentedColormap.from_list with specified colors

Use plt.imshow with my_cmap to display the heatmap

Print the heatmap with plt.colorbar() to show the color scale

💡 Why This Matters

🌍 Real World

Custom colormaps help make data visualizations clearer and more meaningful, especially when showing temperature, elevation, or other continuous data.

💼 Career

Data scientists and analysts often create custom colormaps to highlight important data ranges and improve reports or dashboards.

1

Create the temperature data

Create a 2D list called temperatures with these exact values: [[22, 24, 19], [21, 23, 20], [20, 22, 18], [19, 21, 17], [18, 20, 16], [17, 19, 15], [16, 18, 14]]

Matplotlib

# Create the 2D list temperatures with the exact values
# Your code here

Need a hint?

Use square brackets to create a list of lists with the exact numbers.

2

Create the custom colormap

Import LinearSegmentedColormap from matplotlib.colors and create a colormap called my_cmap using LinearSegmentedColormap.from_list with the colors ['blue', 'white', 'red'].

Matplotlib

temperatures = [[22, 24, 19], [21, 23, 20], [20, 22, 18], [19, 21, 17], [18, 20, 16], [17, 19, 15], [16, 18, 14]]
# Import LinearSegmentedColormap and create my_cmap with colors ['blue', 'white', 'red']
# Your code here

Need a hint?

Use from matplotlib.colors import LinearSegmentedColormap and then call LinearSegmentedColormap.from_list with the name and color list.

3

Plot the heatmap with the custom colormap

Import matplotlib.pyplot as plt. Use plt.imshow to display temperatures with the colormap my_cmap. Then add a colorbar with plt.colorbar().

Matplotlib

from matplotlib.colors import LinearSegmentedColormap

temperatures = [[22, 24, 19], [21, 23, 20], [20, 22, 18], [19, 21, 17], [18, 20, 16], [17, 19, 15], [16, 18, 14]]

my_cmap = LinearSegmentedColormap.from_list('my_cmap', ['blue', 'white', 'red'])
# Import matplotlib.pyplot as plt and plot temperatures with my_cmap
# Your code here

Need a hint?

Use plt.imshow with the cmap argument set to my_cmap. Then call plt.colorbar() to show the scale.

4

Show the heatmap

Add plt.show() to display the heatmap with the custom colormap and colorbar.

Matplotlib

from matplotlib.colors import LinearSegmentedColormap
import matplotlib.pyplot as plt

temperatures = [[22, 24, 19], [21, 23, 20], [20, 22, 18], [19, 21, 17], [18, 20, 16], [17, 19, 15], [16, 18, 14]]

my_cmap = LinearSegmentedColormap.from_list('my_cmap', ['blue', 'white', 'red'])

plt.imshow(temperatures, cmap=my_cmap)
plt.colorbar()
# Add plt.show() to display the plot
# Your code here

Need a hint?

Use plt.show() to open the window with the heatmap.