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

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

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

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

Hint

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

Practice

1. What is the main purpose of creating a custom style sheet in matplotlib?

easy

A. To make charts look consistent and save time when plotting

B. To write Python code faster

C. To change the data in the plot

D. To export plots as images

Solution

1. Step 1: Understand the role of style sheets

   Style sheets control the appearance of plots, such as colors and fonts.

2. Step 2: Identify the benefit of custom style sheets

   Custom style sheets help keep charts consistent and save time by reusing styles.

3. Final Answer:

   To make charts look consistent and save time when plotting -> Option A

4. Quick Check:

   Custom style sheets = consistent charts + time saving [OK]

Hint: Custom styles = consistent look + less work [OK]

Common Mistakes:

• Thinking style sheets change data
• Confusing style sheets with exporting images
• Believing style sheets speed up coding

2. Which of the following is the correct way to apply a custom style sheet named my_style.mplstyle in matplotlib?

easy

A. plt.style('my_style')

B. plt.use_style('my_style')

C. plt.style.use('my_style.mplstyle')

D. plt.style.apply('my_style.mplstyle')

Solution

1. Step 1: Recall the correct function to apply styles

   The function to apply a style sheet is plt.style.use().

2. Step 2: Check the correct argument format

   The style file name should be passed as a string, including the extension if needed.

3. Final Answer:

   plt.style.use('my_style.mplstyle') -> Option C

4. Quick Check:

   Use plt.style.use() with filename [OK]

Hint: Use plt.style.use('filename') to apply styles [OK]

Common Mistakes:

• Using incorrect function names like plt.use_style
• Omitting .mplstyle extension when needed
• Using plt.style() instead of plt.style.use()

3. Given the following code, what will be the color of the line in the plot?

import matplotlib.pyplot as plt
plt.style.use('custom_style.mplstyle')
plt.plot([1, 2, 3], [4, 5, 6])
plt.show()

Assuming custom_style.mplstyle contains:

lines.color: red

medium

A. Black

B. Blue

C. Green

D. Red

Solution

1. Step 1: Understand style sheet effect

   The style sheet sets lines.color to red, which changes line color.

2. Step 2: Apply style to plot

   Since plt.style.use('custom_style.mplstyle') is called, the line color becomes red.

3. Final Answer:

   Red -> Option D

4. Quick Check:

   Style sets lines.color = red, so line is red [OK]

Hint: Style file sets line color, so plot uses that color [OK]

Common Mistakes:

• Ignoring style file and expecting default color
• Confusing color names
• Not applying style before plotting

4. What is wrong with this code snippet if the custom style sheet my_style.mplstyle is not applied?

import matplotlib.pyplot as plt
plt.style.use(my_style.mplstyle)
plt.plot([1, 2], [3, 4])
plt.show()

medium

A. The style file name should be a string in quotes

B. plt.plot() is missing required arguments

C. plt.show() should be called before plt.plot()

D. The style file must be imported as a module

Solution

1. Step 1: Check how style file is passed

   The style file name must be a string, so it needs quotes around it.

2. Step 2: Identify the error in code

   Without quotes, Python treats my_style.mplstyle as a variable, causing an error.

3. Final Answer:

   The style file name should be a string in quotes -> Option A

4. Quick Check:

   File name must be string in plt.style.use() [OK]

Hint: Put style file name in quotes inside plt.style.use() [OK]

Common Mistakes:

• Forgetting quotes around style file name
• Calling plt.show() too early
• Trying to import style file as Python module

5. You want to create a custom style sheet that sets the plot background to light gray and the grid lines to dashed blue. Which of the following .mplstyle file contents will achieve this?

hard

A. figure.facecolor: #d3d3d3
grid.color: blue
grid.linestyle: '--'

B. axes.facecolor: lightgray
grid.color: blue
grid.linestyle: '--'

C. background.color: lightgray
grid.color: blue
grid.line: dashed

D. axes.background: lightgray
grid.style: dashed
grid.color: blue

Solution

1. Step 1: Identify correct keys for background and grid

   The correct key for plot background is axes.facecolor. Grid color uses grid.color and line style uses grid.linestyle.

2. Step 2: Match values to keys

   Light gray is 'lightgray', grid color is 'blue', and dashed lines use '--'. axes.facecolor: lightgray grid.color: blue grid.linestyle: '--' matches all correctly.

3. Final Answer:

   axes.facecolor: lightgray grid.color: blue grid.linestyle: '--' -> Option B

4. Quick Check:

   Use axes.facecolor and grid.linestyle for background and grid [OK]

Hint: Use axes.facecolor and grid.linestyle keys in style file [OK]

Common Mistakes:

• Using wrong keys like axes.background or grid.style
• Wrong color names or formats
• Missing quotes or incorrect line style syntax