Basic Count Plot 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 count plot displays the frequency of observations in each category of a categorical variable using vertical bars. Unlike a basic bar chart that requires pre-computed values, a count plot automatically counts occurrences from raw data. This makes it ideal for quick exploratory analysis of categorical distributions without manual aggregation.

Renders

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

Preview render from the Apache ECharts implementation.

Implementations

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