[scatter-marginal] Scatter Plot with Marginal Distributions

[MarkusNeusinger]

Plot Request

Scatter plot with marginal histograms or KDE on axes showing the distribution of each variable.

Use Cases

• Exploring bivariate relationships
• Understanding individual distributions
• Statistical analysis

Expected Features

• Main scatter plot in center
• Marginal histograms/KDE on top and right
• Aligned axes

[claude]

✅ Spec ID: scatter-marginal

Rationale: Combines scatter plot with marginal distributions (histograms/KDE) on axes, a distinct visualization pattern commonly used in statistical analysis that extends the basic scatter plot.

This is a valid and useful plot type for exploring bivariate relationships while simultaneously viewing the univariate distributions of each variable. No duplicate or similar spec exists in the repository.

[github-actions]

✅ Specification Ready: scatter-marginal

PR: #2014

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specification.md

scatter-marginal: Scatter Plot with Marginal Distributions

Description

A scatter plot enhanced with marginal distribution plots (histograms or kernel density estimates) on the top and right axes. This composite visualization simultaneously shows the bivariate relationship between two variables in the central scatter plot while displaying each variable's univariate distribution along its respective axis. It provides a comprehensive view of both the joint and marginal distributions in a single figure.

Applications

• Exploring the correlation between two continuous variables while understanding their individual distributions in exploratory data analysis
• Visualizing feature relationships in machine learning datasets to identify skewness, multimodality, or outliers
• Analyzing measurement data in scientific research where both the relationship and the distribution characteristics matter

Data

• x (numeric) - Independent variable values plotted on the horizontal axis
• y (numeric) - Dependent variable values plotted on the vertical axis
• Size: 50-1000 points recommended for clear visualization of both scatter and distributions
• Example: Random bivariate data with correlation to demonstrate typical patterns

Notes

• Main scatter plot should be positioned in the lower-left with marginal plots aligned on top and right
• Marginal plots can be histograms, KDE curves, or both overlaid
• Axes of marginal plots must align with the main scatter plot axes
• Consider using subtle colors for marginal distributions to not distract from the main scatter plot
• Points should have moderate transparency (alpha ~0.6-0.7) to reveal density patterns

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Next: Add approved label to merge this specification to main.

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🤖 spec-create workflow

[MarkusNeusinger]

✅ Closed with 9/9 implementations in repo (scatter-marginal)