Creating custom style sheets in Matplotlib - Practice Exercises

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of applying a custom style sheet

What will be the color of the line in the plot after applying the custom style sheet?

Matplotlib

import matplotlib.pyplot as plt
import matplotlib as mpl

custom_style = {
    'lines.linewidth': 3,
    'lines.color': 'red',
    'axes.titlesize': 'large'
}

mpl.rcParams.update(custom_style)
plt.plot([1, 2, 3], [1, 4, 9])
plt.title('Test Plot')
plt.show()

A The line will be thick and red in color.

B The line will be thin and blue in color.

C The line will be thick and blue in color.

D The line will be thin and red in color.

💡 Hint

Check the lines.linewidth and lines.color keys in the style dictionary.

The custom style sets lines.linewidth to 3, making the line thick, and lines.color to 'red', so the line color is red.

❓ data_output

intermediate

Number of style parameters applied

How many style parameters are applied when using the following custom style sheet?

Matplotlib

custom_style = {
    'lines.linewidth': 2,
    'axes.facecolor': 'lightgray',
    'grid.color': 'white',
    'grid.linestyle': '--'
}

import matplotlib.pyplot as plt
import matplotlib as mpl

mpl.rcParams.update(custom_style)
params = mpl.rcParams
count = sum(1 for key in custom_style if key in params)
print(count)

A 3

B 4

C 2

D 1

💡 Hint

Count how many keys in custom_style exist in mpl.rcParams.

All 4 keys in the custom style dictionary are valid matplotlib rcParams keys, so all 4 are applied.

🔧 Debug

advanced

Identify the error in custom style sheet usage

What error will occur when running this code?

Matplotlib

import matplotlib.pyplot as plt
import matplotlib as mpl

custom_style = {
    'lines.linewidth': 'thick',
    'axes.titlesize': 14
}

mpl.rcParams.update(custom_style)
plt.plot([1, 2, 3], [1, 4, 9])
plt.title('Test Plot')
plt.show()

A No error, plot shows with thick lines.

B KeyError because 'lines.linewidth' is not a valid rcParam.

C TypeError because 'lines.linewidth' expects a number, not a string.

D ValueError because 'axes.titlesize' must be a string, not an integer.

💡 Hint

Check the expected data type for lines.linewidth.

The lines.linewidth parameter expects a numeric value (float or int). Passing the string 'thick' causes a TypeError.

❓ visualization

advanced

Effect of custom style on grid appearance

Which option best describes the grid appearance after applying this custom style?

Matplotlib

import matplotlib.pyplot as plt
import matplotlib as mpl

custom_style = {
    'grid.color': 'green',
    'grid.linestyle': ':',
    'grid.linewidth': 2
}

mpl.rcParams.update(custom_style)
plt.plot([1, 2, 3], [1, 4, 9])
plt.grid(True)
plt.show()

A The grid lines are green, dotted, and thick.

B The grid lines are green, dashed, and thin.

C The grid lines are blue, dotted, and thick.

D The grid lines are blue, solid, and thin.

💡 Hint

Look at the grid.color, grid.linestyle, and grid.linewidth values.

The style sets grid color to green, linestyle to dotted (':'), and linewidth to 2 (thick).

🧠 Conceptual

expert

Understanding custom style sheet priority

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

Matplotlib

import matplotlib.pyplot as plt
import matplotlib as mpl

mpl.style.use('seaborn-darkgrid')
custom_style = {
    'lines.color': 'purple',
    'lines.linewidth': 1
}
mpl.rcParams.update(custom_style)
plt.plot([1, 2, 3], [1, 4, 9])
plt.show()

A The code will raise an error because multiple styles are used.

B The line color will be the seaborn default because it has higher priority.

C The line color will be blue because matplotlib defaults override styles.

D The line color will be purple because the custom style overrides the seaborn style.

💡 Hint

Consider the order of mpl.style.use() calls and which style is applied last.

Styles applied later override earlier ones. The custom style is applied after seaborn, so its settings take priority.

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