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

Need a 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

Need a 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

Need a 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

Need a hint?

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