Mosaic Plot for Categorical Association Analysis 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 mosaic plot visualizes contingency tables by dividing a rectangular area into smaller rectangles whose areas are proportional to cell frequencies. This statistical visualization technique effectively shows relationships and associations between two categorical variables, making it easy to identify patterns, dependencies, and deviations from expected frequencies in cross-tabulated data.

Renders

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

Preview render from the MUI X Charts implementation.

Implementations

• Mosaic Plot for Categorical Association Analysis in Altair (Python)
• Mosaic Plot for Categorical Association Analysis in Bokeh (Python)
• Mosaic Plot for Categorical Association Analysis in lets-plot (Python)
• Mosaic Plot for Categorical Association Analysis in Matplotlib (Python)
• Mosaic Plot for Categorical Association Analysis in Plotly (Python)
• Mosaic Plot for Categorical Association Analysis in plotnine (Python)
• Mosaic Plot for Categorical Association Analysis in Pygal (Python)
• Mosaic Plot for Categorical Association Analysis in Seaborn (Python)
• Mosaic Plot for Categorical Association Analysis in ggplot2 (R)
• Mosaic Plot for Categorical Association Analysis in Makie.jl (Julia)
• Mosaic Plot for Categorical Association Analysis in Chart.js (JavaScript)
• Mosaic Plot for Categorical Association Analysis in D3.js (JavaScript)
• Mosaic Plot for Categorical Association Analysis in Apache ECharts (JavaScript)
• Mosaic Plot for Categorical Association Analysis in Highcharts (JavaScript)
• Mosaic Plot for Categorical Association Analysis in MUI X Charts (JavaScript)