Regression Plots (lmplot, regplot)

Why regression plots?

Regression plots help you see:

• Trend direction
• Strength of relationship (visual)
• Outliers that affect the trend

diagram What regplot draws mermaid

  flowchart LR
  A["x, y columns"] --> B["Scatter every point"]
  A --> C["Fit a regression line
(linear by default)"]
  C --> D["Shade a confidence
band around the line"]
  B --> E["regplot figure"]
  D --> E

regplot combines a scatter plot with a fitted line and a shaded confidence band around it.

From the book

McKinney uses sns.regplot(x=\"m1\", y=\"unemp\", data=trans_data) to check the relationship between two macroeconomic series — “seaborn’s regplot method… makes a scatter plot and fits a linear regression line.” It’s a fast way to eyeball whether two numeric columns move together before building anything more formal.

regplot (axes-level)

regplot

import seaborn as sns
import matplotlib.pyplot as plt
 
tips = sns.load_dataset("tips")
 
plt.figure(figsize=(7, 4))
sns.regplot(data=tips, x="total_bill", y="tip")
plt.title("Tip vs total bill")
plt.tight_layout()
plt.show()

lmplot (figure-level, great for facets)

lmplot

import seaborn as sns
 
tips = sns.load_dataset("tips")
 
sns.lmplot(data=tips, x="total_bill", y="tip", hue="sex")

Visualize it

The line summarizes the overall trend; the shaded band shows how confident the fit is — narrower where data is dense, wider near the edges:

sketch Scatter plot with a fitted trend line p5.js Pause Restart

Dots are individual data points; the blue line is the fitted trend, with a soft confidence band around it.

Non-linear patterns

You can try polynomial fits.

Polynomial fit

import seaborn as sns
import matplotlib.pyplot as plt
 
tips = sns.load_dataset("tips")
 
plt.figure(figsize=(7, 4))
sns.regplot(data=tips, x="total_bill", y="tip", order=2)
plt.title("Quadratic trend")
plt.tight_layout()
plt.show()

Tips

• Regression plots show association, not causation.
• Outliers can heavily affect the fitted line.
• Use transformations (log) if relationships are multiplicative.

Next

Continue to Joint Plots to see the same scatter relationship alongside each variable’s own distribution.

🧪 Try It Yourself

Exercise 1 – Fit a Regression Line

pch.exerciseTag pch.exerciseTitle

Exercise 2 – Facet the Regression by Group

pch.exerciseTag pch.exerciseTitle

Exercise 3 – Try a Quadratic Fit

pch.exerciseTag pch.exerciseTitle