Map

Maps are one of the fastest ways to explain geographic patterns in your data. In Columns, map rendering is automatic once a valid location field is detected.

Supported Maps

Columns currently supports:

1. Japan map: prefecture and city levels
2. US map: state, county, and ZIP/city levels
3. World map: country level
4. Europe map: country level

Available rendering styles:

• Spike
• Bubble
• Choropleth

Location Matching

Columns checks your key fields and matches them to known geographic identifiers.

US Map

Supported identifiers include:

1. State name (for example Washington)
2. State code (for example WA)
3. ZIP code (5-digit, for example 98033)
4. City name
5. County name
6. County FIPS (5-digit)
7. County FIPS (3-digit)

Reference files:

• states.json
• counties.json

tip

If you use FIPS codes, keep them as text to preserve leading zeros (for example 015).

Japan Map

Supported identifiers include:

1. Prefecture name (English or Japanese)
2. City name (English or Japanese)

Reference files:

• japan_prefectures.json
• japan_cities.json

Europe Map

Supported identifiers include:

1. Country name
2. ISO2 code (DE, FR, CZ)
3. ISO3 code (DEU, FRA, CZE)
4. UN numeric code (3-digit)
5. Common aliases (UK, Russia, etc.)

Reference file:

• europe_countries.json

World Map

Supported identifiers include:

1. Country name
2. Country code (for example USA, CHN)

Reference file:

• country_codes.json

Map Settings

When you click the map canvas, the map settings panel opens on the right.

Example of automatic state-level rendering:

Map settings panel:

World map example: Data example

Per-Capita Analysis

For US maps, you can normalize values by population using built-in per-capita options:

• per 1M
• per 100K
• per 1K

This is useful when density is more meaningful than raw totals.

More Examples

You can find community map stories on the Discover page.