Distribution
Raincloud plot
Combines a density silhouette, individual observations and a summary such as a box plot.
- Plot
- Distribution
- Comparison
What it answers
What do observations, distribution shape and summary show together?
- Shape
- Half-density, points and summary
- What it shows
- Individual variation, centre, spread and potential modes.
Example
The question
How are task completion times spread for the old and new checkout?
Seconds to complete checkout, raincloud plot (illustrative)
Illustrative data. It belongs to no company.
When to use it
Use it when
Showing raw-data transparency with distribution context.
Avoid it when
Very dense point layers or unsupported density estimates from tiny samples.
How to read it
Read points first, then the summary and half-density.
Note
A composite of several marks.
The data you need
- Layout
- Long table
- Fields
- Group: text; Value: number
- One row is
- One raw observation belonging to a group. What is the grain?
- Rules
- Retain individual observations and group labels. State weighting and missing-data rules.
- Optional
- For box plots only, some tools accept Group,Q1,Median,Q3,WhiskerLow,WhiskerHigh plus separate outliers. Other distributions usually need raw data.
- Preparation
- Keep raw numeric observations, group them if needed and handle missingness explicitly. Choose bins, bandwidth or summary conventions as appropriate to this specific plot.
- Units
- The measurement axis retains its original unit. Frequency uses observations; normalised frequency divides by group sample size; density also depends on interval width.
Worked example
Values 10,12,12,18,23. Show five points, a median marker at 12 and a half-density. The points make the actual sample size explicit.
| Group | Value |
|---|---|
| A | 10 |
| A | 12 |
| A | 18 |
| B | 11 |
| B | 23 |