{
 "generated_at": "2026-10-16T11:05:14+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"
  }
 ],
 "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/23108/",
 "language": "ja",
 "title": "愛知県名古屋市瑞穂区の町丁目ごとの犯罪・事故の件数",
 "data": {
  "city_code": "23108",
  "city_name": "名古屋市瑞穂区",
  "pref_code": "23",
  "pref_name": "愛知県",
  "population": 108332,
  "n_units": 344,
  "lat": 35.125642,
  "lon": 136.936721,
  "data_through": {
   "crime": null,
   "accident": 2025
  },
  "crime_years": [],
  "crime_totals": null,
  "accident_totals": {
   "years": {
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     "accidents": 347,
     "deaths": 0,
     "injured": 425,
     "person_vs_vehicle": 31,
     "vehicle_vs_vehicle": 315,
     "single_vehicle": 1,
     "pedestrian": 31,
     "bicycle": 98,
     "night": 85
    },
    "2020": {
     "accidents": 268,
     "deaths": 1,
     "injured": 309,
     "person_vs_vehicle": 23,
     "vehicle_vs_vehicle": 245,
     "single_vehicle": 0,
     "pedestrian": 23,
     "bicycle": 86,
     "night": 62
    },
    "2021": {
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     "deaths": 0,
     "injured": 346,
     "person_vs_vehicle": 32,
     "vehicle_vs_vehicle": 266,
     "single_vehicle": 2,
     "pedestrian": 32,
     "bicycle": 85,
     "night": 75
    },
    "2022": {
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     "deaths": 2,
     "injured": 332,
     "person_vs_vehicle": 39,
     "vehicle_vs_vehicle": 247,
     "single_vehicle": 5,
     "pedestrian": 39,
     "bicycle": 86,
     "night": 61
    },
    "2023": {
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     "deaths": 2,
     "injured": 324,
     "person_vs_vehicle": 36,
     "vehicle_vs_vehicle": 220,
     "single_vehicle": 5,
     "pedestrian": 36,
     "bicycle": 72,
     "night": 61
    },
    "2024": {
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     "deaths": 1,
     "injured": 384,
     "person_vs_vehicle": 30,
     "vehicle_vs_vehicle": 290,
     "single_vehicle": 2,
     "pedestrian": 30,
     "bicycle": 96,
     "night": 73
    },
    "2025": {
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     "deaths": 1,
     "injured": 374,
     "person_vs_vehicle": 34,
     "vehicle_vs_vehicle": 279,
     "single_vehicle": 4,
     "pedestrian": 34,
     "bicycle": 99,
     "night": 85
    }
   },
   "latest_provisional": true
  },
  "city_only": false,
  "tokyo": null,
  "n_units_pop": 52,
  "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": [
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   "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/23108/<unit_code>/",
  "towns": [
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    "crime": {},
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   },
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   },
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   },
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   {
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