Elbow Curve for K-Means Clustering 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.

An elbow curve visualizes the relationship between the number of clusters (k) and within-cluster sum of squares (inertia/distortion) in K-means clustering. The plot helps identify the optimal number of clusters by finding the "elbow point" where adding more clusters yields diminishing returns in reducing inertia. This is a fundamental diagnostic tool for unsupervised learning parameter selection.

Renders

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

Preview render from the Plotly implementation.

Implementations

• Elbow Curve for K-Means Clustering in Altair (Python)
• Elbow Curve for K-Means Clustering in Bokeh (Python)
• Elbow Curve for K-Means Clustering in lets-plot (Python)
• Elbow Curve for K-Means Clustering in Matplotlib (Python)
• Elbow Curve for K-Means Clustering in Plotly (Python)
• Elbow Curve for K-Means Clustering in plotnine (Python)
• Elbow Curve for K-Means Clustering in Pygal (Python)
• Elbow Curve for K-Means Clustering in Seaborn (Python)
• Elbow Curve for K-Means Clustering in ggplot2 (R)
• Elbow Curve for K-Means Clustering in Makie.jl (Julia)
• Elbow Curve for K-Means Clustering in Chart.js (JavaScript)
• Elbow Curve for K-Means Clustering in D3.js (JavaScript)
• Elbow Curve for K-Means Clustering in Apache ECharts (JavaScript)
• Elbow Curve for K-Means Clustering in Highcharts (JavaScript)
• Elbow Curve for K-Means Clustering in MUI X Charts (JavaScript)