Returns Distribution Histogram 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 histogram showing the distribution of financial returns (daily, weekly, or monthly) with a normal distribution overlay for comparison. This visualization is essential for risk analysis, allowing analysts to assess whether returns follow a normal distribution, identify fat tails indicating higher-than-expected extreme events, and measure asymmetry through skewness. Key statistics are displayed directly on the plot for quick interpretation.

Renders

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

Preview render from the Makie.jl implementation.

Implementations

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