Population across Asia, country by country
The most populous continent as a choropleth, with the two extremes — China and India against the smaller states — handled by the ramp rather than flattening everything into one colour.
Start an editable copy with this data and your current map styling.
What to look at
- A magma ramp on a dark basemap, so the dense end reads as heat rather than as a darker version of the same colour.
- Country outlines are drawn in the basemap colour, which keeps a hundred borders from turning into a black mesh.
- China and India hold more than half the continent between them, so the ramp is doing real work rather than decorating.
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 |
|---|---|---|
| region | text | India |
| population_millions | number | 1428 |
Rebuild it with your own data
- 1
Get your GeoJSON file ready
The example fields are region, population_millions. 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
Graphite 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 choropleth use?
- This example illustrates GeoJSON data. The live preview uses GeoJSON geometry. MapCrafter reads GeoJSON 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 2 columns: region, population_millions. 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?
- Natural Earth 5.1.2 country and territory boundaries (50m plus 10m small territories). World Bank 2023 population, with Natural Earth population estimates where no World Bank row exists; observation year is shown in each popup.
More choropleth maps examples
Gallery (314)- GeoJSONPopulation across Europe, country by countryA continent cut from the same world boundary set, filled from a two-column table. Countries the table has no row for stay grey, so a gap in the data is visible rather than filled in.
- GeoJSONPopulation across South AmericaCountries and territories across the continent, filled by population. A small enough set that every shape is legible at once, which makes it a good demonstration of a choropleth with no outliers to hide behind.
- GeoJSONPopulation across OceaniaPacific countries and territories spread across a vast ocean, which is the case that shows why a region map needs a camera of its own rather than a fit to its bounds.
Last updated 2026-10-22