← Japanchartlink · choropleth
Japan by: prefectures · municipalities
Map of Japan by prefecture, one number per prefecture
Also: Japan map by prefecture · 都道府県別の地図 · 日本地図 都道府県 · Japanese prefectures choropleth · map of Japan's 47 prefectures

Example: Population of Japan's 47 prefectures, 2025 — Preliminary counts from the 2025 Population Census, as of 1 October 2025, by prefecture. Tokyo, Kanagawa and Osaka lead; Tottori and Shimane are the least populated.
About this template
Data: one row per prefecture with its ISO 3166-2 code (JP-13 for Tokyo, JP-27 for Osaka) or its name, and a number. A prefecture with no row stays grey. The frame shows the four main islands and Okinawa; Okinotorishima and Minamitorishima sit outside it. Same design as the other country maps, so they sit side by side.
A choropleth map of the states, provinces or regions of Japan (ISO 3166-2 codes), each region filled by one number from your data (the "population" column). The view is cropped to longitude 122.9–146.1 and latitude 24–45.6.
A sequential colour scale from pale blue for the smallest values to deep navy blue for the largest; pinned to 500000 to 10000000, so values beyond the ends take the end colour and the colour bar says ≤ and ≥; a gradient colour bar below the map, with its labels underneath; values formatted in compact form (1.2k, 3.4M), 1 decimal; on a white canvas (#ffffff) with near-black text — a light theme; 0.6-unit hairline outlines between regions.
The title and description are left-aligned above the chart. Font: Inter (the default); a source line with a link sits at the bottom, with the chartlink badge in the corner.
Data: 2 columns — prefecture (string, "Prefecture (ISO 3166-2 code or name)"), population (number, "Population, 1 October 2025 census (preliminary)") — and 47 rows in the example "Population of Japan's 47 prefectures, 2025". Regions are named by ISO 3166-2 region codes or region names; a region with no row stays unfilled in grey, and an unknown code fails loudly with the nearest matches. Your data keeps the same column ids and every other setting comes from the template; an agent can change any of them.
Other looks of this template — dark (on a dark canvas): ast_299IcQWcIlV1ZmdkzsoDX; buckets (with the values in classes and a swatch legend): ast_0A40ZZf0NkDbOXlO7J2ns; editorial (in the editorial house style — serif type on paper, a green ramp): ast_70WdbINJLOz0RKbArafNn; categories (with a text category per region and a swatch legend): ast_rzi7cZO3BUL3cvIt0agPu; buckets-dark (with the values in classes and a swatch legend, on a dark canvas): ast_thcSRNPKQSfhuOuosjQFn; surroundings (with the land around the place drawn in grey): ast_VKJpnfRVWTbW1ckOGX6cg; categories-dark (with a text category per region and a swatch legend, on a dark canvas): ast_wUDHANjUnPGwIVH2Vqw1L; buckets-editorial (with the values in classes and a swatch legend, in the editorial house style — serif type on paper, a green ramp): ast_4s1cz8kzWOqDmBa6bhB90; dark-surroundings (on a dark canvas, with the land around the place drawn in grey): ast_y7z0h1dU5BAVMdNx3mnv8; buckets-surroundings (with the values in classes and a swatch legend, with the land around the place drawn in grey): ast_eqYgaOVYWUJp37Pn2EtT9; categories-editorial (with a text category per region and a swatch legend, in the editorial house style — serif type on paper, a green ramp): ast_nzMWHU09Tl0oIM4lMSJWn; editorial-surroundings (in the editorial house style — serif type on paper, a green ramp, with the land around the place drawn in grey): ast_oxpdd4n8rqcs6qwZOX6nD; categories-surroundings (with a text category per region and a swatch legend, with the land around the place drawn in grey): ast_hmkrGjbMqYmfZf71fnYly; buckets-dark-surroundings (with the values in classes and a swatch legend, on a dark canvas, with the land around the place drawn in grey): ast_EGF6EJ7GwrQUx1Ti5triO; categories-dark-surroundings (with a text category per region and a swatch legend, on a dark canvas, with the land around the place drawn in grey): ast_O1HFXFeM8g0YAnskMQZLR; buckets-editorial-surroundings (with the values in classes and a swatch legend, in the editorial house style — serif type on paper, a green ramp, with the land around the place drawn in grey): ast_kCM6eTJZc4WuiQOHB1MEn; categories-editorial-surroundings (with a text category per region and a swatch legend, in the editorial house style — serif type on paper, a green ramp, with the land around the place drawn in grey): ast_XSuoqnkifu7gFoVzOCkMM. On the page, switch with the toggles; an agent passes that id as the template instead.
Use it with your agent
Copy the prompt, paste it into Claude, ChatGPT, Cursor or any agent with the chartlink MCP server or API, and give it your numbers. It rebuilds this exact design with your data and hands back an embed, a PNG and a page.
The prompt in full
Data this template expects
| column id | type | in the example |
|---|---|---|
| prefecture | string | Prefecture (ISO 3166-2 code or name) |
| population | number | Population, 1 October 2025 census (preliminary) |
47 rows in the example. Your data keeps these column ids; everything else about the chart comes from the template.
For agents: the API call
POST https://chartlink.app/api/assets
{
"template": "ast_gKKaMR9mwWWfNLdhjrHA9",
"knobs": {
"theme": "light",
"dataType": "gradient",
"title": {
"text": "Your title"
},
"source": {
"text": "Where the numbers come from"
}
},
"data": {
"columns": [
{
"id": "prefecture",
"type": "string"
},
{
"id": "population",
"type": "number"
}
],
"rows": [
[
"…"
]
]
},
"publish": true
}The recipe (the template's settings)
{
"chart": {
"bounds": [
122.9,
24,
146.1,
45.6
],
"domain": [
500000,
10000000
],
"format": {
"kind": "number",
"compact": true,
"decimals": 1
},
"outline": {
"width": 0.6
},
"geography": "jp-regions"
},
"title": {
"text": "Population of Japan's 47 prefectures, 2025"
},
"preset": "map-light",
"source": {
"url": "https://www.stat.go.jp/english/data/kokusei/index.html",
"text": "Statistics Bureau of Japan, 2025 Population Census, preliminary counts (compiled table)"
},
"encoding": {
"value": {
"column": "population"
},
"region": {
"column": "prefecture"
}
},
"description": {
"text": "Preliminary counts from the 2025 Population Census, as of 1 October 2025, by prefecture. Tokyo, Kanagawa and Osaka lead; Tottori and Shimane are the least populated."
}
}map · choropleth · japan · prefectures · country-regions
Similar templates
- Map of Japan by municipality, one number per city, town, village or ward
- Map of Slovakia by municipality, one number per municipality
- Map of Switzerland by municipality, one number per municipality
- Map of Austria by municipality, one number per municipality
- Map of Romania by commune, one number per commune
- Map of Hungary by municipality, one number per municipality
- Map of Portugal by parish, one number per parish
- Map of Poland by municipality, one number per municipality
- All templates →