Style sheets (ggplot, seaborn, dark_background) in Matplotlib - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to apply the 'ggplot' style to matplotlib.

Matplotlib

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

Drag options to blanks, or click blank then click option'

Aggplot

Bseaborn

Cdark_background

Dclassic

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'seaborn' instead of 'ggplot'.

Forgetting to call plt.style.use().

The 'ggplot' style is applied using plt.style.use('ggplot').

2fill in blank

medium

Complete the code to apply the 'seaborn' style to matplotlib.

Matplotlib

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

Drag options to blanks, or click blank then click option'

Aclassic

Bggplot

Cseaborn

Ddark_background

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'ggplot' instead of 'seaborn'.

Not importing matplotlib.pyplot as plt.

Use plt.style.use('seaborn') to apply the seaborn style.

3fill in blank

hard

Fix the error in the code to apply the dark background style correctly.

Matplotlib

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

Drag options to blanks, or click blank then click option'

Adark_background

Bdarkbackground

CDark_Background

Ddarkbackground_style

Attempts:

3 left

💡 Hint

Common Mistakes

Using camel case or missing underscore.

Using a style name that does not exist.

The correct style name is 'dark_background' with an underscore and all lowercase.

4fill in blank

hard

Fill both blanks to create a plot with 'seaborn' style and a title 'My Plot'.

Matplotlib

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

Drag options to blanks, or click blank then click option'

Aseaborn

Bggplot

CMy Plot

DPlot Title

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing up style names.

Forgetting to put the title string in quotes.

Use plt.style.use('seaborn') and set the title with plt.title('My Plot').

5fill in blank

hard

Fill both blanks to create a plot with 'ggplot' style, plot data, and label the y-axis as 'Value'.

Matplotlib

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

Drag options to blanks, or click blank then click option'

Adark_background

BValue

Cggplot

Dseaborn

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong style name.

Not setting the y-axis label correctly.

Apply the 'ggplot' style with plt.style.use('ggplot') and label the y-axis with plt.ylabel('Value').

Practice

1. What does the plt.style.use('ggplot') command do in matplotlib?

easy

A. It changes the plot style to look like ggplot2 from R.

B. It creates a new plot with ggplot data.

C. It saves the plot as a ggplot file.

D. It resets the plot style to default.

Solution

1. Step 1: Understand plt.style.use()

   This function sets the style for all plots that follow.

2. Step 2: Recognize 'ggplot' style

   The 'ggplot' style mimics the look of the ggplot2 library from R, changing colors and grid lines.

3. Final Answer:

   It changes the plot style to look like ggplot2 from R. -> Option A

4. Quick Check:

   Style 'ggplot' changes plot appearance [OK]

Hint: Remember: plt.style.use sets the plot's look [OK]

Common Mistakes:

• Thinking it creates or saves plots
• Confusing style setting with data loading
• Assuming it resets style

2. Which of the following is the correct way to apply the 'dark_background' style in matplotlib?

easy

A. plt.style.use('dark_background')

B. plt.use.style('dark_background')

C. plt.style('dark_background')

D. plt.set_style('dark_background')

Solution

1. Step 1: Recall the syntax for applying styles

   The correct function is plt.style.use() with the style name as a string.

2. Step 2: Check each option

   Only plt.style.use('dark_background') matches the correct syntax: plt.style.use('dark_background').

3. Final Answer:

   plt.style.use('dark_background') -> Option A

4. Quick Check:

   Correct syntax is plt.style.use('style_name') [OK]

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

Common Mistakes:

• Using plt.style() instead of plt.style.use()
• Swapping method order like plt.use.style()
• Using non-existent plt.set_style()

3. What will be the background color of the plot after running this code?

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

medium

A. White background with black grid lines

B. Black background with white grid lines

C. Gray background with no grid lines

D. Blue background with colored grid lines

Solution

1. Step 1: Identify the style used

   The code uses plt.style.use('dark_background'), which sets a dark theme.

2. Step 2: Understand dark_background style

   This style sets the plot background to black and grid lines to white or light colors for contrast.

3. Final Answer:

   Black background with white grid lines -> Option B

4. Quick Check:

   'dark_background' means dark plot background [OK]

Hint: dark_background style means black background [OK]

Common Mistakes:

• Assuming default white background
• Confusing grid line colors
• Thinking dark_background changes data colors only

4. Identify the error in this code snippet:

import matplotlib.pyplot as plt
plt.style.use('seaborn')
plt.plot([1, 2, 3], [3, 2, 1])
plt.show()

It raises an error: AttributeError: module 'matplotlib.pyplot' has no attribute 'style'

medium

A. plt.plot() is used incorrectly

B. The style name 'seaborn' is misspelled

C. matplotlib version is too old and lacks style module

D. plt.show() is missing parentheses

Solution

1. Step 1: Understand the error message

   The error says plt has no attribute 'style', meaning the style module is missing.

2. Step 2: Check possible causes

   This usually happens if matplotlib version is old and does not support style sheets.

3. Final Answer:

   matplotlib version is too old and lacks style module -> Option C

4. Quick Check:

   AttributeError on plt.style means old matplotlib [OK]

Hint: AttributeError on plt.style means update matplotlib [OK]

Common Mistakes:

• Assuming typo in style name
• Blaming plt.plot() syntax
• Forgetting plt.show() needs parentheses

5. You want to create two plots side by side: the first with 'ggplot' style and the second with 'seaborn' style. Which code correctly applies different styles to each subplot?

hard

A. plt.style.use('ggplot')
plt.subplot(1, 2, 1)
plt.plot([1,2])
plt.subplot(1, 2, 2)
plt.plot([2,1])
plt.style.use('seaborn')
plt.show()

B. plt.subplot(1, 2, 1)
plt.plot([1,2])
plt.subplot(1, 2, 2)
plt.plot([2,1])
plt.style.use(['ggplot', 'seaborn'])
plt.show()

C. plt.subplot(1, 2, 1)
plt.style.use('ggplot')
plt.plot([1,2])
plt.subplot(1, 2, 2)
plt.style.use('seaborn')
plt.plot([2,1])
plt.show()

D. with plt.style.context('ggplot'):
plt.subplot(1, 2, 1)
plt.plot([1,2])
with plt.style.context('seaborn'):
plt.subplot(1, 2, 2)
plt.plot([2,1])
plt.show()

Solution

1. Step 1: Understand style application scope

   plt.style.use() sets global style, affecting all plots after it.

2. Step 2: Use plt.style.context() for local styles

   To apply different styles to subplots, use plt.style.context() as a context manager around each plot.

3. Step 3: Check options

   Only with plt.style.context('ggplot'): plt.subplot(1, 2, 1) plt.plot([1,2]) with plt.style.context('seaborn'): plt.subplot(1, 2, 2) plt.plot([2,1]) plt.show() uses plt.style.context() correctly to apply different styles to each subplot.

4. Final Answer:

   Use plt.style.context() blocks for different subplot styles. -> Option D

5. Quick Check:

   Use style.context() for local style changes [OK]

Hint: Use plt.style.context() to apply styles locally [OK]

Common Mistakes:

• Using plt.style.use() multiple times globally
• Trying to pass list of styles to plt.style.use()
• Not using context manager for local styles