Color mapping with colorbar in Matplotlib - Mini Project: Build & Apply

Color mapping with colorbar

📖 Scenario: You are working with temperature data for a week. You want to visualize the temperatures using colors so it is easy to see which days were hotter or colder.

🎯 Goal: Create a color map for the temperature values and display a colorbar to show the temperature scale.

📋 What You'll Learn

Create a list of temperatures for 7 days

Create a colormap using matplotlib

Map the temperatures to colors using the colormap

Display a colorbar showing the temperature scale

💡 Why This Matters

🌍 Real World

Color mapping with colorbars is used in weather maps, heatmaps, and scientific visualizations to show data intensity or value ranges clearly.

💼 Career

Data scientists and analysts use color mapping to make data easier to understand visually, helping in reports and presentations.

1

Create the temperature data list

Create a list called temperatures with these exact values: 22, 25, 19, 30, 28, 24, 20 representing temperatures for 7 days.

Matplotlib

# Create the list of temperatures for 7 days
# Your code here

Need a hint?

Use square brackets to create a list and separate values with commas.

2

Create a colormap and normalization

Import matplotlib.pyplot as plt and Normalize from matplotlib.colors. Then create a Normalize object called norm with vmin=19 and vmax=30 to normalize the temperature range.

Matplotlib

temperatures = [22, 25, 19, 30, 28, 24, 20]
# Import matplotlib.pyplot as plt and Normalize from matplotlib.colors
# Create a Normalize object called norm with vmin=19 and vmax=30
# Your code here

Need a hint?

Use import matplotlib.pyplot as plt and from matplotlib.colors import Normalize.

Create norm = Normalize(vmin=19, vmax=30).

3

Map temperatures to colors using a colormap

Create a variable called cmap and set it to plt.cm.viridis. Then create a list called colors by applying cmap(norm(temp)) for each temp in temperatures using a list comprehension.

Matplotlib

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

temperatures = [22, 25, 19, 30, 28, 24, 20]
norm = Normalize(vmin=19, vmax=30)
# Create cmap as plt.cm.viridis
# Create colors list by applying cmap(norm(temp)) for each temp in temperatures
# Your code here

Need a hint?

Use plt.cm.viridis for the colormap.

Use a list comprehension to map each temperature to a color.

4

Display the colorbar with the temperature scale

Create a figure and axis using plt.subplots(). Then create a ScalarMappable object called sm with the norm and cmap. Use sm.set_array([]). Finally, add a colorbar to the axis with plt.colorbar(sm, ax=ax) and call plt.show() to display the plot.

Matplotlib

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

temperatures = [22, 25, 19, 30, 28, 24, 20]
norm = Normalize(vmin=19, vmax=30)
cmap = plt.cm.viridis
colors = [cmap(norm(temp)) for temp in temperatures]
# Create figure and axis with plt.subplots()
# Create ScalarMappable sm with norm and cmap
# Call sm.set_array([])
# Add colorbar with plt.colorbar(sm, ax=ax)
# Show the plot with plt.show()
# Your code here

Need a hint?

Use ScalarMappable to create a mappable for the colorbar.

Call plt.colorbar with the mappable and axis.