{ "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/23111/", "language": "ja", "title": "愛知県名古屋市港区の全国治安指数と犯罪・事故の件数", "data": { "city_code": "23111", "city_name": "名古屋市港区", "pref_code": "23", "pref_name": "愛知県", "population": 143715, "n_units": 385, "lat": 35.105544, "lon": 136.856811, "data_through": { "crime": null, "accident": 2025 }, "crime_years": [], "crime_totals": null, "accident_totals": { "years": { "2019": { "accidents": 572, "deaths": 6, "injured": 694, "person_vs_vehicle": 48, "vehicle_vs_vehicle": 515, "single_vehicle": 9, "pedestrian": 49, "bicycle": 111, "night": 162 }, "2020": { "accidents": 553, "deaths": 8, "injured": 652, "person_vs_vehicle": 54, "vehicle_vs_vehicle": 490, "single_vehicle": 9, "pedestrian": 54, "bicycle": 137, "night": 157 }, "2021": { "accidents": 624, "deaths": 3, "injured": 740, "person_vs_vehicle": 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"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/23111//", "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": 154205, "night_population": 143715, "day_population": 164696 }, "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 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