Grouped-Color Rose Chart Generator

Grouped-Color Rose Chart Generator

Use Grouped-Color Rose Chart Generator

All GotoKit tools run directly online, no download required.

Drop a CSV file here or click to upload

Format: label,value,group (three comma-separated columns), up to 48 rows; group is optional (defaults to a single group)

Canvas style Light Show labels

All data is processed locally in your browser, never uploaded

About this tool

When a rose’s categories also carry a second dimension — region by product line, say — this chart colors each petal by its group, letting hues flow smoothly from one segment to the next so the ring itself reads like a pie of pies. Up to 48 petals with toggleable labels and light / dark canvases, built for grouped composition comparisons.

  • 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 Grouped-Color Rose Chart?

A grouped-color Nightingale rose chart is a polar bar chart where each sector has the same angle and the radius encodes the value. Unlike a standard rose chart, sectors are divided into color segments based on the group column: all sectors within the same group share one primary color, while different groups use different colors. This “segmented coloring” is ideal for showing “one metric across multiple categories,” such as sales comparison across regions or headcount distribution across departments.

Features

  • Grouped coloring: Automatically segments colors by the group column—same group, same color; different groups, different colors for clear visual grouping
  • Template-driven: Download the CSV template, fill in your data, and upload to generate—no visualization expertise needed
  • Up to 48 items: Supports up to 48 sectors with fixed angles and radius mapped to values
  • Label toggle: One-click to show or hide all sector labels—switch to a clean graphic for dense data
  • Light / dark modes: Adapts to different contexts (PPT, reports, web pages)
  • Multiple export formats: Download high-resolution PNG (2x pixel ratio) or vector SVG
  • Local privacy: All data is parsed and rendered locally in your browser, never uploaded to a server

Use Cases

  • Retail & e-commerce analytics: Compare sales across multiple regions (grouped by area) to quickly identify key markets
  • HR management: Show headcount distribution across departments (grouped by function) to support organizational optimization
  • Marketing: Analyze performance across channels (grouped by media type) to optimize budget allocation
  • Financial analysis: Display expense composition by category to identify cost priorities
  • Reports & presentations: Add professional grouped-comparison charts to PPT, data posters, and analytical reports

Steps

  1. Click “Download CSV template” to get the sample file
  2. Fill in your data following the format: label,value,group
  3. Click the upload area or drag a CSV file onto the page
  4. The grouped-color rose chart is generated automatically; toggle labels and light/dark mode to preview
  5. Click “Download PNG” or “Download SVG” to save

Data Format

FieldRequiredDescription
labelYesSector name
valueYesNumeric value (positive), used to compute sector radius
groupNoGroup name; blank defaults to a single group. Sectors in the same group share one color

Limits: Up to 48 rows; recommended no more than 6 groups (6-color palette, colors repeat beyond that).

How to read this chart

First count how many color groups there are, then compare petal lengths within each group. Segment boundaries are group boundaries; petals sharing a hue family belong together. To ask which group is biggest overall, compare summed arc lengths, not single petals.

About Gotokit

Gotokit is dedicated to providing simple, efficient, and beautiful online tools. This grouped-color rose chart generator uses the ECharts rendering engine, requires no registration, works out of the box, and processes all data locally to protect your privacy.

FAQ

How should the label, value and group columns be filled, and can group be left blank?

The fixed format is label,value,group; group is optional (defaults to a single group). Up to 48 rows.

Is there a limit on the number of groups?

The palette has 6 colors; we recommend no more than 6 groups. Colors repeat beyond that.

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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