{
 "generated_at": "2026-10-17T00:37:28+09:00",
 "data_through": {
  "crime": null,
  "accident": 2025
 },
 "source": [
  {
   "name": "警察庁 交通事故統計情報のオープンデータ",
   "publisher": "警察庁",
   "url": "https://www.npa.go.jp/publications/statistics/koutsuu/opendata/index_opendata.html",
   "license": "公共データ利用規約 第1.0版（PDL1.0）。警察庁ウェブサイト利用規約に従い、編集・加工した旨を記載する",
   "note": "人身事故のみ。tokeilab が町丁目・50m格子に集計・加工した"
  },
  {
   "name": "e-Stat 国勢調査 2020年 小地域（町丁・字等）境界・人口",
   "publisher": "総務省統計局",
   "url": "https://www.e-stat.go.jp/gis/statmap-search?page=1&type=2&aggregateUnitForBoundary=A&toukeiCode=00200521&toukeiYear=2020",
   "license": "政府標準利用規約（第2.0版）。出典を明記し、加工した旨を記載する",
   "note": "町丁目の人口・世帯数・重心"
  },
  {
   "name": "e-Stat 令和2年国勢調査 従業地・通学地による人口・就業状態等集計 第1-1表（昼間人口）",
   "publisher": "総務省統計局",
   "url": "https://www.e-stat.go.jp/stat-search/file-download?statInfId=000032214141&fileKind=0",
   "license": "政府標準利用規約（第2.0版）準拠（CC BY 4.0 互換）。出典を明記し、加工した旨を記載する",
   "note": "市区町村の昼間人口。市区町村の人口あたりの件数の分母（夜間人口と昼間人口の大きい方）に使った"
  }
 ],
 "license": "CC-BY-4.0",
 "license_notice": "CC BY 4.0, tokeilab。都道府県警察の犯罪オープンデータ、警察庁の交通事故統計情報のオープンデータ、警視庁の町丁別集計表、e-Stat 国勢調査を tokeilab が加工して作成。",
 "schema_url": "https://tokeilab.org/schema/safety/",
 "canonical_url": "https://tokeilab.org/safety/23447/",
 "language": "ja",
 "title": "愛知県武豊町の全国治安指数と犯罪・事故の件数",
 "data": {
  "city_code": "23447",
  "city_name": "武豊町",
  "pref_code": "23",
  "pref_name": "愛知県",
  "population": 9037,
  "n_units": 2,
  "lat": 34.828245,
  "lon": 136.906412,
  "data_through": {
   "crime": null,
   "accident": 2025
  },
  "crime_years": [],
  "crime_totals": null,
  "accident_totals": {
   "years": {
    "2019": {
     "accidents": 115,
     "deaths": 2,
     "injured": 143,
     "person_vs_vehicle": 17,
     "vehicle_vs_vehicle": 95,
     "single_vehicle": 3,
     "pedestrian": 17,
     "bicycle": 13,
     "night": 38
    },
    "2020": {
     "accidents": 103,
     "deaths": 0,
     "injured": 116,
     "person_vs_vehicle": 13,
     "vehicle_vs_vehicle": 87,
     "single_vehicle": 3,
     "pedestrian": 13,
     "bicycle": 19,
     "night": 29
    },
    "2021": {
     "accidents": 103,
     "deaths": 0,
     "injured": 118,
     "person_vs_vehicle": 9,
     "vehicle_vs_vehicle": 92,
     "single_vehicle": 1,
     "pedestrian": 10,
     "bicycle": 18,
     "night": 28
    },
    "2022": {
     "accidents": 92,
     "deaths": 2,
     "injured": 101,
     "person_vs_vehicle": 15,
     "vehicle_vs_vehicle": 76,
     "single_vehicle": 1,
     "pedestrian": 15,
     "bicycle": 19,
     "night": 26
    },
    "2023": {
     "accidents": 122,
     "deaths": 0,
     "injured": 143,
     "person_vs_vehicle": 21,
     "vehicle_vs_vehicle": 100,
     "single_vehicle": 1,
     "pedestrian": 21,
     "bicycle": 27,
     "night": 31
    },
    "2024": {
     "accidents": 95,
     "deaths": 1,
     "injured": 107,
     "person_vs_vehicle": 16,
     "vehicle_vs_vehicle": 79,
     "single_vehicle": 0,
     "pedestrian": 16,
     "bicycle": 20,
     "night": 30
    },
    "2025": {
     "accidents": 89,
     "deaths": 0,
     "injured": 103,
     "person_vs_vehicle": 15,
     "vehicle_vs_vehicle": 71,
     "single_vehicle": 3,
     "pedestrian": 15,
     "bicycle": 19,
     "night": 13
    }
   },
   "latest_provisional": true
  },
  "city_only": false,
  "tokyo": null,
  "n_units_pop": 2,
  "notes": [],
  "crime_types": [
   "ひったくり",
   "車上ねらい",
   "部品ねらい",
   "自動販売機ねらい",
   "自動車盗",
   "オートバイ盗",
   "自転車盗"
  ],
  "crime_columns": [
   "count_latest",
   "per_10k_latest",
   "rank_count",
   "rank_per_10k",
   "rank_shown",
   "change_2018_diff",
   "change_2018_ratio",
   "change_3y_diff",
   "change_3y_ratio",
   "evaluable"
  ],
  "ranks_note": "rank_count の母数は n_units、rank_per_10k の母数は n_units_pop。rank_shown=1 のときだけ順位を出す、evaluable=1 のときだけ増減を出す",
  "town_page_template": "https://tokeilab.org/safety/23447/<unit_code>/",
  "index": {
   "score": null,
   "reason": "no_crime_data",
   "crime_position": null,
   "accident_position": null,
   "crime_rate_10k": null,
   "accident_rate_10k": null,
   "crime_last_year": null,
   "accident_last_year": 2025,
   "window_years": 3,
   "n_scored": 1753,
   "size_adjusted": false,
   "denominator_population": 40531,
   "night_population": 43535,
   "day_population": 37528
  },
  "index_caveat": "窃盗の7種類（ひったくり・車上ねらい・部品ねらい・自動販売機ねらい・自動車盗・オートバイ盗・自転車盗）と人身事故の、人口あたりの件数から計算した指数です。暴行・傷害・性犯罪・詐欺などは含まれず、治安のすべてを表すものではありません。人口の多い都市の町は件数が多くなりやすく、点数が低く出る傾向があります。市区町村の点数は、昼間に人が多く集まる所に配慮して、夜間人口と昼間人口の平均で計算しています。",
  "index_reading": "index.score は 0〜100（高いほど人口あたりの件数が少ない側。全国の中での位置で、市区町村は夜間人口と昼間人口の平均で割った値）。null のときは index.reason（population_small | no_crime_data）。towns[].idx は町丁目の同じ指数（null は点数なし）",
  "towns": [
   {
    "unit_code": "234470070",
    "name": "大字東大高",
    "population": 3226,
    "crime": {},
    "accidents_latest": 3,
    "accidents_total": 56,
    "idx": null,
    "name_arabic": "大字東大高"
   },
   {
    "unit_code": "234470080",
    "name": "大字冨貴",
    "population": 5811,
    "crime": {},
    "accidents_latest": 11,
    "accidents_total": 68,
    "idx": null,
    "name_arabic": "大字冨貴"
   }
  ],
  "pref_url": "https://tokeilab.org/safety/23/",
  "map_url": "https://tokeilab.org/safety/map/?lat=34.828245&lon=136.906412&z=14"
 }
}