Relational Plots in Seaborn – Scatter and Line Plots

Relational plots help you understand how two variables are related.
In Seaborn, the two main functions for this are:

• scatterplot(): Displays the relationship between two continuous variables using points.
• lineplot(): Shows trends or patterns between variables using lines.

Both are part of Seaborn's relational plotting tools.

• Scatter plot: Use when you want to explore how one variable changes with another without assuming a continuous relationship (e.g., height vs. weight).
• Line plot: Use when you want to show trends over an ordered sequence, such as time series data.

Copy
import seaborn as sns
import matplotlib.pyplot as plt

tips = sns.load_dataset("tips")

sns.scatterplot(data=tips, x="total_bill", y="tip")
plt.title("Scatter Plot of Total Bill vs Tip")
plt.show()

Copy
fmri = sns.load_dataset("fmri")

sns.lineplot(data=fmri, x="timepoint", y="signal")
plt.title("Line Plot of Signal over Time")
plt.show()

You can customize relational plots using parameters like hue, style, and size to add categories, patterns, or variable-sized points.