Ridgeline Plot Generator - Free Online Joy Plot Chart Maker
Use Ridgeline Plot Generator - Free Online Joy Plot Chart Maker
All GotoKit tools run directly online, no download required.
Upload a fixed CSV template (series,x,value) to generate a ridgeline plot in the reference style: each series is layered along its own horizontal baseline with smooth non-overlapping peaks, a series name on the left of every row and a bottom dot legend. Light / dark canvas with PNG / SVG export.
About this tool
To compare the shapes of many distributions side by side, stacking them on one axis hides everything while splitting them apart kills comparison. A ridgeline plot seats each distribution on its own horizontal baseline like a row of overlapping hills, with enough air between rows that nothing is hidden, a series name on the left of every row and a dot legend below. Made for distribution shapes, group differences and how a distribution evolves over time.
- Export crisp PNG / SVG you can keep editing
- Multiple built-in themes, one-click switch
- Light and dark canvas support
- Free, no watermark, no limits
Compared with general charting workflows
| Aspect | This tool | Typical alternative |
|---|---|---|
| Visual direction | Optimized for a specific chart grammar | More general, but more setup |
| Export | Fast PNG/SVG export first | More formats, but heavier workflow |
| Best fit | Slides, landing pages, and social visuals | Building bespoke analytical charts from scratch |
Docs
What is a Ridgeline Plot?
A ridgeline plot (also called a joy plot or multiple area chart) displays several distributions or time series along their own horizontal baselines, layered vertically: every series keeps an independent baseline, peaks are drawn with smooth curves, and rows stay separated with visible gaps — stacked like rolling mountain ridges. It became popular in the data-visualization community (e.g. the ggridges package in R) and is now a favorite for data posters, science communication and social-media infographics thanks to its “multi-row comparison + layered beauty”. All rows share the same x-axis scale, each row is labeled on the left, and a horizontal dot legend at the bottom maps the colors.
Features
- Template-driven, WYSIWYG: download the CSV template, fill in your data and upload — no coding required
- Three-column long format: series,x,value (group name, horizontal value, non-negative value), up to 6 series and 400 rows; x ticks are built from all values in the data
- Layered vertical layout: every series is stacked along its own horizontal baseline; row pitch and peak height adapt to the number of series with non-overlapping white gaps
- Smooth mountain curves: flat fills without stroke, smoothly interpolated, reproducing the soft silhouette of the reference chart
- Left row labels: series name with a short tick line on the left of each row, vertically centered on the row baseline
- Adaptive axes: each row rounds its own maximum to a clean tick, with light / dark modes
- Multi-format export: high-resolution PNG (2x) and vector SVG downloads
- Local privacy: all data is parsed and rendered locally in your browser, never uploaded
Use Cases
- Data posters and science communication: layered cover charts for WeChat articles, data blogs and explainer videos
- Distribution comparison: exam score distributions of classes, hourly visitor flows, sales trends across products, displayed side by side
- Time-series stacking: multi-year monthly data, region indicator trends, comparing peak-valley rhythms under one shared x-axis
- Social-media infographics: polished data visuals for Xiaohongshu and Weibo matching trending aesthetics
- Reports and slides: eye-catching multi-layer area charts for quarterly reports and industry analysis
If you only need a single-series area trend, a plain area chart is enough; the ridgeline plot excels at “many series + shared x-scale + layered aesthetics”.
How to Use
- Click “Download CSV template” to get the sample file
- Fill in your data: series name in the first column, x value in the second, and the non-negative value in the third
- Click the upload area or drag the CSV file onto the page
- The layered ridgeline plot is generated instantly; switch light / dark mode
- Click “Download PNG” or “Download SVG” to save the chart
Data Format
| Field | Required | Description |
|---|---|---|
| series | Yes | Series / group name; identical names share the same row |
| x | Yes | Horizontal value (e.g. 0, 1, 2…26) that places each point |
| value | Yes | Non-negative value that drives the peak height |
Limits: up to 6 series and 400 rows; x and value must be numbers, value cannot be negative. Series are ordered from top to bottom as they appear in the CSV.
How to read this chart
Each row is a hill whose shape is that group’s distribution: the peak sits at the mode, a sharper peak means a tighter distribution and wider slopes mean more spread. Compare peak positions across rows to see whether centers shift between groups, and compare hill widths for dispersion. Rows that never overlap are a feature of the layout, not a rendering error.
About Gotokit
Gotokit provides simple, efficient and beautiful online tools. This ridgeline plot generator is powered by the ECharts rendering engine — no signup, ready to use, fully local data processing for your privacy.
FAQ
How is the long three-column series, x, value table organized?
The fixed format is a three-column long table: series,x,value. The first column is the series / group name (identical names share the same row), the second is the horizontal value, and the third is the non-negative value. Up to 6 series and 400 rows. Series are ordered from top to bottom as they appear in the CSV.
How are the x-axis ticks determined?
The x-axis is a category axis built from every x value that appears in the data, sorted numerically. The default sample shows integer ticks 0–26; when there are more than 30 x values, the tool automatically skips ticks to avoid crowding.
Is this chart tool better for slides, reports, or social visuals?
All three can work, but each needs a different emphasis. Slides care about legibility, reports care about structure and annotation, and social visuals care about density and style. Tune colors, labels, and export size for the destination.
When should I export PNG instead of SVG?
PNG is usually better for slides, chats, or social sharing, while SVG is better if you need to keep editing, scale for print, or embed the graphic in a design system. If the target platform does not support SVG, export a higher-resolution PNG.
How is this different from a general charting tool?
These tools are optimized for a specific visual grammar, so you can get to a strong result faster. General charting tools are more flexible across many chart families, but usually take more setup and styling work.
Can I use this tool on mobile phones or tablets?
Most tools work in modern mobile browsers, but complex charts, larger files, and precision drag-and-drop tasks usually feel better on desktop. If speed and control matter, desktop is the safer choice.
Is this tool better for one-off tasks or recurring workflows?
It is strongest for fast one-off tasks, quick verification, and temporary exports. If you need long-term automation, team collaboration, or deeper integration, you will usually pair it with desktop software, scripts, or a larger system.
How can I get a better result on the first try?
Start with the built-in example or with the smallest realistic sample you have. Once the format, layout, and export look right, switch to the full dataset or final asset. This is usually the fastest way to catch formatting issues early.
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