Creating custom style sheets in Matplotlib - Visual Walkthrough

Concept Flow - Creating custom style sheets

Create style dict or file

↓

Save style sheet file

↓

Load style sheet in matplotlib

↓

Plot with custom styles applied

↓

Visualize styled plot

You create a style sheet file or dictionary, save it, load it in matplotlib, then plot to see your custom styles.

Execution Sample

Matplotlib

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

This code loads a custom style sheet and plots a simple line chart using those styles.

Execution Table

Step	Action	Evaluation	Result
1	Create style dict or file	Define colors, fonts, line widths	Style file 'my_custom_style.mplstyle' created
2	Save style sheet file	Write to matplotlib style folder or local	File saved and accessible
3	Load style sheet	plt.style.use('my_custom_style.mplstyle')	Style settings loaded into matplotlib
4	Plot data	plt.plot([1,2,3], [4,5,6])	Plot uses custom colors, fonts, line widths
5	Show plot	plt.show()	Window opens showing styled plot
6	Exit	Plot displayed	Execution ends

💡 Plot displayed and execution ends

Variable Tracker

Variable	Start	After Step 3	After Step 4	Final
style_sheet	null	'my_custom_style.mplstyle' loaded	Applied to plot	Remains applied for plot
plot_data_x	null	null	[1, 2, 3]	[1, 2, 3]
plot_data_y	null	null	[4, 5, 6]	[4, 5, 6]

Key Moments - 2 Insights

Why does the plot change appearance after loading the style sheet?

Because the style sheet sets colors, fonts, and line widths that matplotlib applies to the plot, as shown in step 4 of the execution table.

Can I use a style sheet without saving it as a file?

You can use a style dictionary temporarily, but to reuse styles easily, saving as a .mplstyle file is best, as shown in step 2.

Visual Quiz - 3 Questions

Look at the execution table, at which step is the custom style sheet loaded into matplotlib?

A Step 2

B Step 3

C Step 4

D Step 5

💡 Hint

Check the 'Action' and 'Evaluation' columns for loading the style sheet.

According to the variable tracker, what is the value of 'plot_data_x' after step 4?

A [1, 2, 3]

B null

C [4, 5, 6]

D 'my_custom_style.mplstyle'

💡 Hint

Look at the 'plot_data_x' row under 'After Step 4' in the variable tracker.

If you skip saving the style sheet file, which step in the execution table would be missing?

A Step 1

B Step 3

C Step 2

D Step 4

💡 Hint

Saving the style sheet file is described in step 2.

Concept Snapshot

Creating custom style sheets in matplotlib:
- Define style settings in a .mplstyle file
- Save the file in matplotlib's style folder or local directory
- Load with plt.style.use('filename')
- Plot as usual to see custom styles applied
- Reuse style sheets for consistent visuals

Full Transcript

To create custom style sheets in matplotlib, first define your style settings such as colors, fonts, and line widths in a .mplstyle file. Save this file in a location matplotlib can access. Then, load the style sheet in your Python code using plt.style.use with the file name. When you plot data after loading the style, matplotlib applies your custom settings to the plot. This process helps you keep your charts consistent and visually appealing. The execution table shows each step from creating the style file to displaying the styled plot. The variable tracker shows how variables like the style sheet and plot data change during execution.

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