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China university patent statisticsNEW

China high-tech enterprise patent statisticsNEW

Digital economy patent application and authorization dataNEW

Patents and citation data of Little Giant and individual champion companiesNEW

Small giant and single champion enterprise design patent details table

Statistics on the entry and exit of Chinese industrial and commercial enterprisesNEW

Statistics on entry and exit information of Chinese partnershipsNEW

Basic information data of manufacturing industrial and commercial registered enterprisesNEW

Patent and citation data of A-share listed companiesNEW

Patent details of A-share listed companies
A-share listed companies' patent application details table
Details of Design Patents Authorized by A-share Listed Companies

Green patents and citation data of A-share listed companies

A-share listed companies green patent details table

Patent and citation data of Chinese industrial enterprisesNEW

Green patents and citation data of Chinese industrial enterprisesNEW

Details of Green Patents of Chinese Industrial Enterprises

Tax investigation of corporate patents and citation dataNEW

Cost of living data for global residentsNEW

China foreign trade index data

  The rapid development of the internet has profoundly transformed our lifestyles, with particularly notable impacts on consumer behavior. Consumers no longer rely solely on personal experience or merchant introductions for decision-making, but instead acquire substantial third-party evaluations and information through internet platforms. A store's reputation now predominantly stems from authentic consumer feedback rather than self-promotion. Consequently, internet rating systems have emerged as a new and widely influential form of consumption guidance.

  This comprehensive dataset covering national store review websites encompasses complete information from registered stores in over 400 cities nationwide, containing data from more than 40 million operational offline stores as of 2024. The dataset primarily consists of three components:

Basic Information: Name, alias, branch names, address, coordinates (latitude and longitude), telephone, classification, etc.
Detailed Information: Ratings, menus, pricing, reviews, group purchase/delivery information, business hours, etc.
Derived Information: Number of branches, recommended dishes, ranking lists, and other data generated through mining

  The national store review website dataset developed by CnOpenData includes 15 major categories such as automotive, shopping, attractions, education, hotels, cuisine, and lifestyle services. It covers critical store-related information along with high-quality consumption data and user evaluations, providing superior data resources for relevant research.


Data Description

Automotive data
Pet-related data
Shopping data
Home decoration data
Education data
Wedding services data
Tourist attraction data
Hotel data
Beauty services data
Culinary data
Parent-child services data
Lifestyle services data
Leisure entertainment data
Healthcare data
Fitness and sports data


Field Demonstration


Sample Data

Due to the extensive number of tables, this page displays partial examples. Please navigate to individual tables on the left for complete information.

Education Data

Tourist Attraction Data


Relevant Literature

  • Peng Chong and Jin Peizhen, 2022: "Consumer-oriented Streets: Micro Evidence of Road Density and Consumption Vitality", China Economic Quarterly 4.
  • Yang, X., Gao, Q., Duan, H. et al., 2024: "GHG mitigation strategies on China’s diverse dish consumption are key to meet the Paris Agreement targets", Nat Food 5, 365–377.

Data Update Frequency

Annual updates