Styling and themes in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to set the default style to 'ggplot' using matplotlib.

Data Analysis Python

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'

Aclassic

Bseaborn

Cggplot

Ddark_background

Attempts:

3 left

💡 Hint

Common Mistakes

Using a style name that is not installed or misspelled.

Forgetting to import matplotlib.pyplot as plt.

The plt.style.use() function sets the style for matplotlib plots. 'ggplot' is a popular style that mimics the ggplot2 style from R.

2fill in blank

medium

Complete the code to apply the 'seaborn-darkgrid' style to the plot.

Data Analysis Python

import matplotlib.pyplot as plt
plt.style.use('[1]')
plt.plot([10, 20, 30], [1, 4, 9])
plt.show()

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

Aseaborn-darkgrid

Bseaborn-white

Cfivethirtyeight

Dbmh

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'seaborn-dark' instead of 'seaborn-darkgrid'.

Not calling plt.show() to display the plot.

The 'seaborn-darkgrid' style adds a dark grid background to plots, improving readability.

3fill in blank

hard

Fix the error in the code to set the style to 'bmh'.

Data Analysis Python

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

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

Ause

Bset_style

Cstyle

Dapply

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-existent method like 'set_style' or 'apply'.

Calling plt.style as a function instead of using the 'use' method.

The correct function to set a style in matplotlib is plt.style.use().

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each style name to its description length.

Data Analysis Python

styles = ['ggplot', 'bmh', 'seaborn-darkgrid']
descriptions = {style: len(style) for style in styles if style [1] '[2]'}

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

Astartswith

Bendswith

Cgg

Dgrid

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'endswith' instead of 'startswith'.

Using the wrong substring to filter styles.

The code filters styles that start with 'gg' and creates a dictionary with style names and their length.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps style names to their uppercase form if they contain 'dark'.

Data Analysis Python

styles = ['ggplot', 'bmh', 'seaborn-darkgrid']
result = {style: style[1]() for style in styles if '[2]' [3] style}

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

A.upper

Bdark

Cin

D.lower

Attempts:

3 left

💡 Hint

Common Mistakes

Using '.lower()' instead of '.upper()'.

Using '==' instead of 'in' to check substring presence.

The code checks if 'dark' is in the style name and maps it to its uppercase version.

Practice

1. What is the main purpose of using styling and themes in data visualization?

easy

A. To change the data values automatically

B. To increase the size of the dataset

C. To speed up data processing

D. To make charts look better and easier to understand

Solution

1. Step 1: Understand the role of styling in charts

   Styling and themes improve the visual appeal and clarity of charts.

2. Step 2: Identify the correct purpose

   They help viewers understand data better by making charts clearer and more attractive.

3. Final Answer:

   To make charts look better and easier to understand -> Option D

4. Quick Check:

   Styling improves chart clarity [OK]

Hint: Styling improves look and clarity of charts [OK]

Common Mistakes:

• Confusing styling with data processing
• Thinking styling changes data values
• Assuming styling increases dataset size

2. Which of the following is the correct way to apply a style named 'ggplot' using matplotlib in Python?

easy

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

B. plt.style('ggplot')

C. style.use('ggplot')

D. plt.use.style('ggplot')

Solution

1. Step 1: Recall matplotlib style syntax

   The correct syntax to apply a style is plt.style.use('style_name').

2. Step 2: Match the correct option

   plt.style.use('ggplot') matches this syntax exactly for 'ggplot'.

3. Final Answer:

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

4. Quick Check:

   Use plt.style.use('style') to apply style [OK]

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

Common Mistakes:

• Using plt.style('style') without .use
• Calling style.use without plt prefix
• Incorrect method order like plt.use.style

3. What will be the effect of running this code snippet?

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

medium

A. A line plot with seaborn-dark style applied

B. A line plot with default matplotlib style

C. Syntax error due to wrong style name

D. No plot will be shown

Solution

1. Step 1: Understand plt.style.use('seaborn-dark')

   This line sets the plot style to 'seaborn-dark', changing colors and grid style.

2. Step 2: Analyze the plot commands

   plt.plot creates a line plot, plt.show displays it with the applied style.

3. Final Answer:

   A line plot with seaborn-dark style applied -> Option A

4. Quick Check:

   Style changes plot look [OK]

Hint: plt.style.use sets style before plotting [OK]

Common Mistakes:

• Assuming default style is used after plt.style.use
• Thinking style name causes syntax error
• Expecting no plot to show without plt.show

4. Identify the error in this code that tries to apply a style and plot data:

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

medium

A. plt.plot arguments are reversed

B. Wrong style name 'dark_background'

C. Missing parentheses in plt.show call

D. plt.style.use should be called after plt.plot

Solution

1. Step 1: Check plt.show usage

   plt.show is a function and needs parentheses to execute.

2. Step 2: Verify style name and plot arguments

   'dark_background' is a valid style, and plot arguments are correctly ordered.

3. Final Answer:

   Missing parentheses in plt.show call -> Option C

4. Quick Check:

   plt.show() needs parentheses to display plot [OK]

Hint: Always call plt.show() with parentheses [OK]

Common Mistakes:

• Forgetting parentheses on plt.show
• Assuming style name is invalid without checking
• Thinking plot arguments order causes error

5. You want to create a bar chart with a style that uses a dark background and grid lines. Which code snippet correctly applies the style and plots the data?

import matplotlib.pyplot as plt
data = [5, 7, 3]
labels = ['A', 'B', 'C']
# Choose the correct code to apply style and plot

hard

A. plt.bar(labels, data)
plt.style.use('dark_background')
plt.show()

B. plt.style.use('dark_background')
plt.bar(labels, data)
plt.show()

C. plt.style.use('ggplot')
plt.bar(labels, data)
plt.show()

D. plt.style('dark_background')
plt.bar(labels, data)
plt.show()

Solution

1. Step 1: Apply style before plotting

   Style must be set before plotting to affect the chart appearance.

2. Step 2: Check style name and plotting method

   'dark_background' is the correct style for dark theme with grid lines; plt.bar plots bar chart correctly.

3. Step 3: Verify plt.show() usage

   plt.show() is called with parentheses to display the plot.

4. Final Answer:

   plt.style.use('dark_background') plt.bar(labels, data) plt.show() -> Option B

5. Quick Check:

   Set style before plot, use plt.show() [OK]

Hint: Set style before plotting, call plt.show() with () [OK]

Common Mistakes:

• Setting style after plotting
• Using plt.style instead of plt.style.use
• Forgetting parentheses on plt.show