General plots / Density and ridge plot
Your data stays in your browser: files are read and processed on your device, never uploaded to any server, and cleared when you close the page. Free, no sign-in.
A kernel density curve is a smoothed histogram: the area under it is 1 and its peaks mark where values concentrate. A ridgeline stacks groups vertically (ordered by median); overlaid curves share one set of axes.
The bandwidth sets the smoothness: too small creates spurious peaks, too large flattens real bimodality. The default is R’s bw.nrd0 rule, fine-tuned with the multiplier; in a ridgeline all groups share one bandwidth estimated from the pooled data so shapes are comparable.
Curves extend about three bandwidths beyond the data and are biased near hard boundaries for strictly positive data (counts, proportions); taking log10 first is usually better for such data.
The y-axis is probability density, not counts: curve heights are comparable between groups of very different size but do not show how many observations each group has.
Gaussian kernel density estimate (matches scipy.stats.gaussian_kde at the same bandwidth); bandwidth rules: Silverman (1986) bw.nrd0, Scott (1992).
Up to 30 groups.
Send us your data and research question and you will receive a written plan within 1 working day: analysis steps, parameter rationale, deliverables and timeline. Quoted per project.