← Tokyochartlink · choropleth
Tokyo by: special wards
Map of Tokyo by ward, one number per ward
Also: Tokyo map by ward · 東京23区 地図 · map of Tokyo's 23 wards · Tokyo special wards choropleth · Tokyo ku map

Example: Population of Tokyo's 23 wards, 2025 — Population on 1 January 2025 by special ward, from the Basic Resident Register. Setagaya, Nerima and Ōta are the largest; Chiyoda, the seat of government, the smallest.
About this template
Data: one row per ward with its code (13104 for Shinjuku (新宿区), 13113 for Shibuya (渋谷区)) or its name, and a number. A ward with no row stays grey. Codes are the 5-digit municipal codes 13101–13123; the Japanese ward name (世田谷区) matches. Same design as the other city maps, so they sit together.
A choropleth map of the regions of the "tokyo-wards" geography, each region filled by one number from your data (the "population" column).
A sequential colour scale from pale blue for the smallest values to deep navy blue for the largest; pinned to 50000 to 800000, 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 — ward (string, "Ward (code or name)"), population (number, "Population, 1 January 2025") — and 23 rows in the example "Population of Tokyo's 23 wards, 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_j2UMgaDZZgi6hGEFDRz9u; buckets (with the values in classes and a swatch legend): ast_0R3mjXe7LBjjVsJY3V6G3; editorial (in the editorial house style — serif type on paper, a green ramp): ast_ttY74zcd1T79AiEQMbzKd; categories (with a text category per region and a swatch legend): ast_U8A9ICoCWahr7LfRbqKxI; buckets-dark (with the values in classes and a swatch legend, on a dark canvas): ast_LWyBj2q3dvlUnRA7ripVr; surroundings (with the land around the place drawn in grey): ast_cI6d8ZqXK8s221b6USxnx; categories-dark (with a text category per region and a swatch legend, on a dark canvas): ast_dEicCHPhW0U6dw17f4Edj; buckets-editorial (with the values in classes and a swatch legend, in the editorial house style — serif type on paper, a green ramp): ast_HdQfpnCy6HnuS33RmHU1z; dark-surroundings (on a dark canvas, with the land around the place drawn in grey): ast_zwnWv2snWjapIi6NbAfHg; buckets-surroundings (with the values in classes and a swatch legend, with the land around the place drawn in grey): ast_TyUtTd7rgzKhGRA8fwu07; 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_OTLyUlJVyj72cOhvaJzxR; editorial-surroundings (in the editorial house style — serif type on paper, a green ramp, with the land around the place drawn in grey): ast_S8NHmWLL4C41YV51DUFmb; categories-surroundings (with a text category per region and a swatch legend, with the land around the place drawn in grey): ast_w1pdJRpIFSPIBJb5s6hvm; 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_967R05NpXtKKak26OSsdR; 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_lvuSMAKJnLTfSAvBn8K4E; 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_aNgj1agpPvJlC90oOC1At; 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_32uV7YqqWVTbUOHdqFLh6. 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 |
|---|---|---|
| ward | string | Ward (code or name) |
| population | number | Population, 1 January 2025 |
23 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_ItfBYKH2053Kzo5QcWrI5",
"knobs": {
"theme": "light",
"dataType": "gradient",
"title": {
"text": "Your title"
},
"source": {
"text": "Where the numbers come from"
}
},
"data": {
"columns": [
{
"id": "ward",
"type": "string"
},
{
"id": "population",
"type": "number"
}
],
"rows": [
[
"…"
]
]
},
"publish": true
}The recipe (the template's settings)
{
"chart": {
"domain": [
50000,
800000
],
"format": {
"kind": "number",
"compact": true,
"decimals": 1
},
"outline": {
"width": 0.6
},
"geography": "tokyo-wards"
},
"title": {
"text": "Population of Tokyo's 23 wards, 2025"
},
"preset": "map-light",
"source": {
"url": "https://www.soumu.go.jp/menu_news/s-news/01gyosei02_02000389.html",
"text": "MIC Japan, Basic Resident Register population, 1 January 2025"
},
"encoding": {
"value": {
"column": "population"
},
"region": {
"column": "ward"
}
},
"description": {
"text": "Population on 1 January 2025 by special ward, from the Basic Resident Register. Setagaya, Nerima and Ōta are the largest; Chiyoda, the seat of government, the smallest."
}
}map · choropleth · tokyo · wards · city · city-districts
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