science 這項產品或功能目前處於預先發布階段,也就是正式發布前的版本。正式發布前的產品和功能僅提供有限支援,且正式發布前產品和功能的變更可能與其他正式發布前版本不相容。正式發布前產品/功能受到《
Google 地圖平台服務專屬條款》規範。詳情請參閱
推出階段說明。
註冊即可試用 Places Insights!
關於 Places Insights 資料
透過集合功能整理內容
你可以依據偏好儲存及分類內容。
在預覽版中,地點洞察提供 BigQuery 中的範例資料集,其中包含每個支援國家/地區的頂尖城市資料:雪梨 (澳洲)、聖保羅 (巴西)、多倫多 (加拿大)、蘇黎世 (瑞士)、柏林 (德國)、馬德里 (西班牙)、巴黎 (法國)、倫敦 (英國)、雅加達 (印尼)、孟買 (印度)、羅馬 (義大利)、東京 (日本)、墨西哥市 (墨西哥)、紐約市 (美國)。
每個範例資料集都旨在讓您試用地點洞察,評估產品的實用性和價值。
每個範例資料集都有專屬的訂閱項目,您必須分別訂閱。如要進一步瞭解如何訂閱商家資訊,請參閱「設定地點洞察」。
您可以根據地點類型、評分、營業時間、無障礙空間等各種屬性,從資料集中取得地點資料的匯總洞察資訊。
資料集結構定義
每個國家/地區的地點資料集結構定義都包含兩個部分:
舉例來說,如果您要處理西班牙 (ES) 的資料集,請同時參照核心結構定義和 ES 專屬結構定義。
品牌資料集的結構定義會定義三個欄位:
id
:品牌 ID。
name
:品牌名稱,例如「Hertz」或「Chase」。
category
:品牌的高階類別,例如「加油站」、「食品和飲料」或「住宿」。
預覽的範例資料
在預覽版中,每個國家/地區的資料集都包含頂尖城市的資訊。即使資料是針對單一城市,整個國家/地區的資料集結構定義仍相同。
資料集只包含該城市本身的資料,不含周邊都會區的資料。
其他注意事項
rating
和user_rating_count
資料是根據使用者評論計算出的統計資料。使用者評論未經 Google 驗證,但 Google 會檢查有無不實內容,一旦發現就會將其移除。
資料集可能不準確,且每月更新一次。
作者資訊相關規定
顯示地點洞察資料時,必須顯示必要的出處資訊。如要瞭解出處規定,請參閱「地點洞察政策」。
除非另有註明,否則本頁面中的內容是採用創用 CC 姓名標示 4.0 授權,程式碼範例則為阿帕契 2.0 授權。詳情請參閱《Google Developers 網站政策》。Java 是 Oracle 和/或其關聯企業的註冊商標。
上次更新時間:2025-09-06 (世界標準時間)。
[null,null,["上次更新時間:2025-09-06 (世界標準時間)。"],[],[],null,["In the Preview release, Places Insights provides a sample dataset in a BigQuery\ndata clean room which includes the data for a top city for each of the supported\ncountries: Sydney (AU), Sao Paulo (BR), Toronto (CA), Zurich (CH), Berlin (DE),\nMadrid (ES), Paris (FR), London (UK), Jakarta (ID), Mumbai (IN), Rome (IT),\nTokyo (JP), Mexico City (MX), New York City (US).\n\nEach sample dataset is intended to allow you to try out Places Insights so that\nyou can assess the usability and value of the product.\n| **Note:** For the Preview release, the brands data is only available for the United States sample dataset.\n\nEach sample dataset has its own data clean room that you must subscribe to\nseparately. For more information on subscribing to a clean room, see [Set up\nPlaces Insights](/maps/documentation/placesinsights/cloud-setup).\n\nThe datasets are designed for you to derive aggregated insights about places\ndata based on a variety of attributes such as place types, ratings, store hours,\nwheelchair accessibility, and more.\n\nSample dataset region location\n\nIn BigQuery, [datasets](https://cloud.google.com/bigquery/docs/datasets-intro)\nare stored in a specific region or multi-region\n[location](https://cloud.google.com/bigquery/docs/locations). A *region* is a\ncollection of data centers within a geographical area, and a *multi-region* is a\nlarge geographic area that contains two or more geographic regions.\n\nFor the Preview release of Places Insights, the sample datasets are stored in\nthe **`US` multi-region**.\n| **Note:** Because the Places Insights dataset tables are stored in the `US` multi-region, you cannot write query results to a table in another region, and you cannot join Places Insights tables with tables in another region.\n\nTo perform a join, you can create a replica of your data in the `US`\nmulti-region. For more information on dataset replication, see [Cross-region\ndataset replication](https://cloud.google.com/bigquery/docs/data-replication).\n\nDataset schemas\n\nThe places dataset schema for each country is comprised of two parts:\n\n- The [core schema](/maps/documentation/placesinsights/reference/core-schema) that is common to the datasets for all countries.\n- A [country-specific schema](/maps/documentation/placesinsights/reference/country-schema) that defines schema components specific to that country.\n\nFor example, if you are working with the dataset for Spain (ES), reference both\nthe core schema and the ES-specific schema.\n\nThe schema for the brands dataset defines three fields:\n\n- `id`: The brand ID.\n- `name`: The name of the brand, such as \"Hertz\" or \"Chase\".\n- `category`: The high-level category of the brand, such as \"Gas Station\", \"Food and Drink\", or \"Lodging\".\n\nSample data for Preview\n\nFor the Preview release, the dataset for each country contains information for a\ntop city. Even though the data is for a single city, the dataset schema is the\nsame for the entire country.\n\nThe dataset only contains data for the city itself. It does not contain data for\nthe surrounding metropolitan area.\n\nAdditional notes\n\nThe `rating` and `user_rating_count` data are statistics calculated using user\nreviews. User reviews are not verified by Google, but Google checks for and\nremoves fake content when it's identified.\n\nThe dataset may not be accurate and is refreshed monthly.\n\nAttribution requirements\n\nWhen displaying Places Insights data, you must display the required\nattributions. For attribution requirements, see [Policies for\nPlaces Insights](/maps/documentation/placesinsights/policies)."]]