A tree inventory as a categorical point map
Point data coloured by species category. Categorical colour is the hardest palette to get right: two categories that look alike are not a cosmetic problem, they are two categories the reader will merge into one.
Start an editable copy with this data and your current map styling.
What to look at
- Graduated circles show each simulated reading while colour retains the observation category.
- Stroke colour comes from the basemap, so markers sit in the scene at any zoom.
- Popups show only the first few columns rather than every field in the file.
Source columns
These fields describe the example data. CSV and Excel use first-row headers; GIS formats store geometry and feature properties. Required geometry depends on the map type.
| Column | Type | Example |
|---|---|---|
| id | text | OBS-0142 |
| category | text | Type A |
| reading | number | 48.2 |
Rebuild it with your own data
- 1
Get your CSV file ready
The example fields are id, category, reading. For CSV or Excel, put headers in the first row. GIS files carry geometry and feature properties. Prepare any grid, catchment or route geometry before import.
- 2
Drop it into the studio
MapCrafter detects the geometry, counts the features, and shows the layers it found.
- 3
Style the imported layer
Pick which column drives colour, and which drives size or width where relevant.
- 4
Pick a basemap theme
Ivory is used here. 15 other basemaps are available, including official OpenFreeMap styles. Switch using Layers & basemap.
- 5
Share or export
Publish a link, embed the map, or export a PNG at print resolution.
Questions about this example
- What file format does this graduated circles use?
- This example illustrates CSV data. The live preview uses GeoJSON geometry. MapCrafter reads CSV directly, along with Excel, CSV, KML, KMZ, GPX, GeoJSON, TopoJSON and zipped Shapefile. No conversion step and no desktop software.
- What columns does the source data need?
- The file used here has 3 columns: id, category, reading. For tabular imports, supply coordinate columns, WKT or GeoJSON geometry, or address columns for an explicit geocoding step. Polygon and line files carry their geometry separately from these attributes.
- Can I use my own data with this map type?
- Yes. Open the studio, drop in your file, and MapCrafter detects the geometry and applies a starting style. Then style the layer and choose which property drives colour, size or width. The studio can render a point heatmap, but grids, routes and catchment polygons must be prepared before import.
- Can I export or share the finished map?
- Each map can be published to a short share link, embedded in another page with an iframe, or exported as a print-resolution PNG. The cleaned-up geometry can also be exported as GeoJSON. All of that is available on the free tier.
- Where does the data in this example come from?
- Positions scattered around real Zürich coordinates with a seeded offset; categories are synthetic.
More pin maps examples
Gallery (314)- CSVFour hundred inspections across New YorkA dense point layer on a dark basemap, where marker opacity and stroke width do the work that colour cannot. Past a few hundred markers, the marks must be translucent or the map becomes a solid mass.
- GeoJSONBike stations across LondonA GeoJSON FeatureCollection with properties used directly. GeoJSON is the one format that already speaks the renderer’s language, so the only real decision left is how to style it.
- CSVAir quality monitoring in BerlinClassified diamond markers encode a numeric reading, which is often more useful than a raw number alone. Converting a continuous measurement into bands is a modelling decision, so the thresholds belong on the map, not buried in a spreadsheet.
Last updated 2026-10-22