Scatter Plot with Marginal Distributions in Python, R, Julia and JavaScript

Source code in 15 libraries — Python: Altair, Bokeh, lets-plot, Matplotlib, Plotly, plotnine, Pygal, Seaborn; R: ggplot2; Julia: Makie.jl; JavaScript: Chart.js, D3.js, Apache ECharts, Highcharts, MUI X Charts.

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.

Renders

• Full-resolution render, light theme
• Full-resolution render, dark theme
• Interactive version, light theme
• Interactive version, dark theme

Preview render from the lets-plot implementation.

Implementations

• Scatter Plot with Marginal Distributions in Altair (Python)
• Scatter Plot with Marginal Distributions in Bokeh (Python)
• Scatter Plot with Marginal Distributions in lets-plot (Python)
• Scatter Plot with Marginal Distributions in Matplotlib (Python)
• Scatter Plot with Marginal Distributions in Plotly (Python)
• Scatter Plot with Marginal Distributions in plotnine (Python)
• Scatter Plot with Marginal Distributions in Pygal (Python)
• Scatter Plot with Marginal Distributions in Seaborn (Python)
• Scatter Plot with Marginal Distributions in ggplot2 (R)
• Scatter Plot with Marginal Distributions in Makie.jl (Julia)
• Scatter Plot with Marginal Distributions in Chart.js (JavaScript)
• Scatter Plot with Marginal Distributions in D3.js (JavaScript)
• Scatter Plot with Marginal Distributions in Apache ECharts (JavaScript)
• Scatter Plot with Marginal Distributions in Highcharts (JavaScript)
• Scatter Plot with Marginal Distributions in MUI X Charts (JavaScript)