Skip to content
Python Central Hub

Pair Plots

Why pair plots?

Pair plots are a fast way to inspect:

  • Pairwise relationships between variables
  • Distributions on the diagonal
  • Group separation using huehue

They are great early in EDA.

Basic pairplot

pairplot
import seaborn as sns
 
penguins = sns.load_dataset("penguins").dropna()
 
sns.pairplot(penguins[[
    "bill_length_mm",
    "bill_depth_mm",
    "flipper_length_mm",
    "body_mass_g",
]])
pairplot
import seaborn as sns
 
penguins = sns.load_dataset("penguins").dropna()
 
sns.pairplot(penguins[[
    "bill_length_mm",
    "bill_depth_mm",
    "flipper_length_mm",
    "body_mass_g",
]])

Pairplot with hue

pairplot with hue
import seaborn as sns
 
penguins = sns.load_dataset("penguins").dropna()
 
sns.pairplot(
    penguins,
    vars=["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"],
    hue="species",
)
pairplot with hue
import seaborn as sns
 
penguins = sns.load_dataset("penguins").dropna()
 
sns.pairplot(
    penguins,
    vars=["bill_length_mm", "bill_depth_mm", "flipper_length_mm", "body_mass_g"],
    hue="species",
)

Tips

  • Pair plots can be slow for large datasets. Sample rows if needed.
  • Use huehue to check if groups separate naturally.

If this helped you, consider buying me a coffee ☕

Buy me a coffee

Was this page helpful?

Let us know how we did