Creating custom style sheets in Matplotlib - Try It Yourself

Creating custom style sheets

📖 Scenario: You are working on a data science project where you want your charts to have a consistent and unique look. Instead of setting colors and fonts every time, you decide to create a custom style sheet for matplotlib. This will save time and make your charts look professional and uniform.

🎯 Goal: Create a custom matplotlib style sheet with specific colors and font sizes, then apply it to a simple line plot to see the effect.

📋 What You'll Learn

Create a dictionary with style settings for colors and fonts

Save the style dictionary as a custom style sheet

Load and apply the custom style sheet in matplotlib

Plot a simple line chart using the custom style

💡 Why This Matters

🌍 Real World

Custom style sheets help data scientists and analysts keep their charts consistent and visually appealing across reports and presentations.

💼 Career

Knowing how to create and apply custom styles in matplotlib is useful for roles involving data visualization, reporting, and dashboard creation.

1

Create a style dictionary

Create a dictionary called custom_style with these exact entries: 'axes.facecolor' set to '#EAEAF2', 'axes.edgecolor' set to '#333333', 'lines.linewidth' set to 2, and 'font.size' set to 14.

Matplotlib

# Create the custom_style dictionary with specified keys and values
# Your code here

Need a hint?

Use curly braces {} to create a dictionary. Each key-value pair should be separated by a comma.

2

Save the style dictionary as a style sheet

Import matplotlib and save the custom_style dictionary as a style sheet file named 'custom_style.mplstyle' using matplotlib.style.core.write_style_file.

Matplotlib

custom_style = {
    'axes.facecolor': '#EAEAF2',
    'axes.edgecolor': '#333333',
    'lines.linewidth': 2,
    'font.size': 14
}

# Import matplotlib and save the custom_style dictionary as 'custom_style.mplstyle'
# Your code here

Need a hint?

Use import matplotlib first. Then call matplotlib.style.core.write_style_file with the dictionary and filename.

3

Load and apply the custom style sheet

Import matplotlib.pyplot as plt and use plt.style.use to apply the style sheet file 'custom_style.mplstyle'.

Matplotlib

import matplotlib
custom_style = {
    'axes.facecolor': '#EAEAF2',
    'axes.edgecolor': '#333333',
    'lines.linewidth': 2,
    'font.size': 14
}

matplotlib.style.core.write_style_file(custom_style, 'custom_style.mplstyle')

import matplotlib.pyplot as plt

# Apply the custom style sheet 'custom_style.mplstyle'
# Your code here

Need a hint?

Use plt.style.use with the filename string to apply the style.

4

Plot a line chart using the custom style

Create a list x with values [1, 2, 3, 4, 5] and a list y with values [2, 3, 5, 7, 11]. Use plt.plot(x, y) to plot the line chart and then call plt.show() to display it.

Matplotlib

import matplotlib
custom_style = {
    'axes.facecolor': '#EAEAF2',
    'axes.edgecolor': '#333333',
    'lines.linewidth': 2,
    'font.size': 14
}

matplotlib.style.core.write_style_file(custom_style, 'custom_style.mplstyle')

import matplotlib.pyplot as plt
plt.style.use('custom_style.mplstyle')

# Create lists x and y, plot them, and show the plot
# Your code here

Need a hint?

Make sure to call plt.show() to display the plot window.