Maps

Maps plot data as points, regions, or text on a geographic base map. Count uses OpenStreetMap for the base layer.

There are two ways to map data:

• Points — when each row has its own latitude and longitude.
• Regions — when each row corresponds to an area (a country, a US state, a UK local authority, a custom polygon, …).

You can see sample data and Map visuals in this canvas.

Creating a map

To add a map to the canvas, either:

• In the control bar at the bottom of the canvas, open the Visual group, choose Map, then click on the canvas to place it.
• Press G, then click anywhere on the canvas to place it.

Point template

When each row of your data has a coordinate, use the Point template.

Region template

When each row of your data corresponds to an area, use the Region template. Region marks have a Source setting that controls where the shape comes from:

• Official boundaries — Count looks up the shape for you from a built-in dataset (e.g. UK Local Authorities, US Counties). You only need to provide the boundary's name or code.
• Custom geometry — you provide the shape yourself as a GeoJSON or WKT string in your data.

Official boundaries

Official boundaries let you draw regions on the map without having to ship geometry in your data. Count keeps an up-to-date library of administrative boundaries published by official sources — Natural Earth, the US Census Bureau, Eurostat GISCO, the UK ONS, and more — and resolves them at render time from a name or code in your column.

This is usually what you want when your data already has a familiar identifier like a country name, a US state code, a ZIP code, or a UK local authority code.

Getting started

1. Add a Geo mark to your map layer.
2. In the right-hand panel, set Source to Official boundaries.
3. Pick a Dataset (e.g. Countries, US Counties, UK Local Authorities).
4. Drag the column that identifies each region onto the Region field.

That's it — Count fetches the matching shapes and draws them. Rows whose value doesn't match any boundary in the dataset are skipped silently, so you can keep working without cleaning the data first.

Matching rules

Count tries to be forgiving about how your identifiers are spelled. Each dataset uses one of two matching modes:

• Aliases — matches against the boundary's canonical code as well as a curated list of common names and aliases, and is tolerant of differences in case, punctuation, and accents. So Côte d'Ivoire, Cote d'Ivoire, and the ISO code CIV all resolve to the same country.
• Canonical only — matches against the boundary's official code only. Used for datasets where there is no meaningful "common name" (e.g. census tracts, output areas).

The mode is fixed per dataset — see the table below.

Examples

Available datasets

Global

United States

All US datasets use the US Census Bureau's TIGER/Line files and key off the GEOID.

Europe

Sourced from Eurostat GISCO.

United Kingdom

UK datasets are sourced from the Office for National Statistics Open Geography, Scottish Government Open Data, and NISRA Open Data.

Custom geometry

If your data already contains polygon definitions — or if you need a boundary that isn't covered by the official datasets — set Source to Custom geometry and drop a column of GeoJSON or WKT onto Region.

POLYGON((-0.13 51.50, -0.13 51.52, -0.10 51.52, -0.10 51.50, -0.13 51.50))

{ "type": "Polygon", "coordinates": [[[-0.13, 51.50], [-0.13, 51.52], [-0.10, 51.52], [-0.10, 51.50], [-0.13, 51.50]]] }