Seaborn style with Matplotlib - Mini Project: Build & Apply

Seaborn Style with Matplotlib

📖 Scenario: You are working on a simple data visualization project. You want your charts to look nice and clean, similar to the style used by the Seaborn library, but you will use Matplotlib directly.

🎯 Goal: Create a Matplotlib line plot using the Seaborn style to make the chart visually appealing.

📋 What You'll Learn

Create a list of numbers representing data points

Set the Matplotlib style to 'seaborn'

Plot the data using Matplotlib's plot function

Display the plot with the style applied

💡 Why This Matters

🌍 Real World

Data scientists and analysts often want their charts to look professional and clear. Using styles like Seaborn's with Matplotlib helps make charts easier to understand and more visually appealing.

💼 Career

Knowing how to style plots is important for creating reports and presentations that communicate data insights effectively in many data science and analytics jobs.

1

Create the data list

Create a list called data with these exact values: [5, 7, 9, 6, 8].

Matplotlib

# Create a list called data with values [5, 7, 9, 6, 8]
# Your code here

Hint

Use square brackets to create a list and assign it to the variable data.

2

Set the Matplotlib style to seaborn

Import matplotlib.pyplot as plt and set the style to 'seaborn' using plt.style.use('seaborn').

Matplotlib

data = [5, 7, 9, 6, 8]
# Import matplotlib.pyplot as plt and set style to 'seaborn'
# Your code here

Hint

Use import matplotlib.pyplot as plt and then plt.style.use('seaborn') to apply the style.

3

Plot the data using Matplotlib

Use plt.plot(data) to create a line plot of the data list.

Matplotlib

data = [5, 7, 9, 6, 8]
import matplotlib.pyplot as plt
plt.style.use('seaborn')
# Plot the data list using plt.plot
# Your code here

Hint

Call plt.plot(data) to draw the line chart.

4

Display the plot

Use plt.show() to display the plot with the Seaborn style applied.

Matplotlib

data = [5, 7, 9, 6, 8]
import matplotlib.pyplot as plt
plt.style.use('seaborn')
plt.plot(data)
# Display the plot
# Your code here

Hint

Call plt.show() to open the plot window.

Practice

1. What does using plt.style.use('seaborn') do in Matplotlib?

easy

A. It resets all plot settings to Matplotlib defaults.

B. It changes the plot style to look like Seaborn's default theme.

C. It imports the Seaborn library for plotting.

D. It saves the current plot as a Seaborn file.

Solution

1. Step 1: Understand plt.style.use function

   This function sets the style for all plots that follow.

2. Step 2: Recognize 'seaborn' style effect

   Using 'seaborn' applies Seaborn's visual theme to Matplotlib plots.

3. Final Answer:

   It changes the plot style to look like Seaborn's default theme. -> Option B

4. Quick Check:

   Seaborn style = changes plot look [OK]

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

Common Mistakes:

• Thinking it imports Seaborn library
• Confusing style setting with saving files
• Assuming it resets to default Matplotlib style

2. Which of the following is the correct way to apply the Seaborn style in Matplotlib?

easy

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

B. plt.style('seaborn')

C. plt.use.style('seaborn')

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

Solution

1. Step 1: Recall the correct syntax for style setting

   The correct method is plt.style.use with the style name as a string.

2. Step 2: Check each option's syntax

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

3. Final Answer:

   plt.style.use('seaborn') -> Option D

4. Quick Check:

   Correct syntax = plt.style.use('seaborn') [OK]

Hint: Use plt.style.use('style_name') to set plot style [OK]

Common Mistakes:

• Using plt.style('seaborn') without .use
• Mixing order of style and use
• Incorrect method names or argument order

3. What will be the output style of the plot after running this code?

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

medium

A. A plot with a white background and grid lines.

B. A plot with a white background and no grid lines.

C. A plot with default Matplotlib style and no grid.

D. A plot with bright colors but no grid lines.

Solution

1. Step 1: Understand 'seaborn-darkgrid' style

   This style applies a white background with visible grid lines.

2. Step 2: Analyze the plot appearance

   Since plt.style.use('seaborn-darkgrid') is set, the plot will have a white background and grid lines.

3. Final Answer:

   A plot with a white background and grid lines. -> Option A

4. Quick Check:

   seaborn-darkgrid = white background + grid [OK]

Hint: Remember 'darkgrid' means white background with grids [OK]

Common Mistakes:

• Assuming no grid lines appear
• Confusing darkgrid with dark background styles
• Expecting default Matplotlib style

4. Identify the error in this code snippet that tries to apply Seaborn style:

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

medium

A. plt.show() is missing parentheses.

B. plt.style.use cannot be used before plt.plot.

C. Missing quotes around 'seaborn' in plt.style.use.

D. plt.plot requires two lists of equal length.

Solution

1. Step 1: Check the argument passed to plt.style.use

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

2. Step 2: Verify other parts of the code

   plt.plot has correct lists, plt.show() has parentheses, and style can be set before plotting.

3. Final Answer:

   Missing quotes around 'seaborn' in plt.style.use. -> Option C

4. Quick Check:

   Style name must be a string [OK]

Hint: Always put style names in quotes in plt.style.use [OK]

Common Mistakes:

• Forgetting quotes around style name
• Thinking plt.show() needs no parentheses
• Believing style must be set after plotting

5. You want to create a Matplotlib plot with Seaborn's 'whitegrid' style but only for one plot without affecting others. Which code snippet achieves this?

hard

A. with plt.style.context('seaborn-whitegrid'):
plt.plot(x, y)
plt.show()

B. plt.style.use('seaborn-whitegrid')
plt.plot(x, y)

C. plt.style.context('seaborn-whitegrid')
plt.plot(x, y)
plt.show()

D. plt.style.use('seaborn-whitegrid')
plt.plot(x, y)
plt.style.reset()

Solution

1. Step 1: Understand style context usage

   Using plt.style.context applies a style temporarily within the with block.

2. Step 2: Check each option for temporary style application

   with plt.style.context('seaborn-whitegrid'): plt.plot(x, y) plt.show() uses with plt.style.context('seaborn-whitegrid') to apply style only to that plot.

3. Final Answer:

   with plt.style.context('seaborn-whitegrid'): plt.plot(x, y) plt.show() -> Option A

4. Quick Check:

   Use plt.style.context for temporary style [OK]

Hint: Use with plt.style.context for one-time style [OK]

Common Mistakes:

• Using plt.style.use without resetting style
• Calling plt.style.context without with statement
• Assuming plt.style.reset() exists