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Restaurant Ratings and Prices India
Product Reviews & Feedback
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset details over 27,000 Indian restaurants, providing a rich collection of information including their names, ratings, pricing, delivery times, and various cuisine types [1]. It offers a valuable resource for understanding the landscape of the Indian restaurant industry, covering aspects from customer satisfaction to operational details and regional culinary focuses. The data can be instrumental for market analysis and trend identification within the food service sector [1].
Columns
- restaurant_name: The unique name of the restaurant. There are 21,958 unique restaurant names across the 27,700 valid entries [2].
- rating: The average rating of the restaurant, ranging from 2.4 to 4.9. The average rating is approximately 3.92, with a standard deviation of 0.35 [2, 3].
- average_price: The typical price range for a meal at the restaurant, with values from 10 to 800. The mean average price is around 174, with a standard deviation of 86.7 [3, 4].
- average_delivery_time: The estimated average delivery time for the restaurant, in minutes, ranging from 6 to 190. The average delivery time is approximately 33.4 minutes, with a standard deviation of 10.1 [4].
- south_indian_or_not: A binary indicator (0 or 1) denoting whether the restaurant primarily serves South Indian cuisine. Approximately 13% of the restaurants are categorised as South Indian [4, 5].
- north_indian_or_not: A binary indicator (0 or 1) denoting whether the restaurant primarily serves North Indian cuisine. Approximately 42% of the restaurants are categorised as North Indian [5].
- fast_food_or_not: A binary indicator (0 or 1) denoting whether the establishment is a fast food restaurant. Approximately 36% of the restaurants are categorised as fast food [5].
- street_food: A binary indicator (0 or 1) denoting whether the restaurant focuses on street food. Approximately 18% of the restaurants offer street food [6].
- biryani_or_not: A binary indicator (0 or 1) denoting whether the restaurant serves Biryani. Approximately 18% of the restaurants serve Biryani [6].
- bakery_or_not: A binary indicator (0 or 1) denoting whether the establishment is a bakery. Approximately 10% of the restaurants are categorised as bakeries [6, 7].
All listed columns have 27,700 valid entries with no missing values [2-7].
Distribution
This dataset is typically provided in a CSV (Comma Separated Values) format [8]. It contains over 27,000 records of Indian restaurants, specifically 27,700 valid entries across all detailed columns [1, 2]. The file size is 1.38 MB [1]. It includes 10 of the 11 original columns [1]. The number of rows or records is consistently 27,700 across the detailed column descriptions [2-7].
Usage
This dataset is highly suitable for data visualisation, exploratory data analysis, and various analytical tasks related to the food service industry in India [1]. Ideal applications include:
- Analysing restaurant performance based on ratings and pricing.
- Identifying popular cuisine types and their distribution across India.
- Studying delivery time trends and their impact on customer satisfaction.
- Market research for new restaurant ventures or expansion into specific culinary segments.
- Developing predictive models for restaurant success or customer preferences.
Coverage
The dataset focuses exclusively on Indian restaurants across India [1]. Information on the specific geographic locations (e.g., cities, states) is implied by "location" but not explicitly detailed in terms of breakdown [1]. There is no specific time range mentioned for the data collection, nor any notes on data availability for particular demographic groups or years within the provided details.
License
CC0: Public Domain
Who Can Use It
This dataset is ideal for:
- Data Analysts and Scientists: For performing exploratory data analysis, building machine learning models, and generating insights into the Indian restaurant market.
- Market Researchers: To understand trends in restaurant ratings, pricing strategies, and popular cuisines across India.
- Restaurant Owners and Entrepreneurs: To conduct competitive analysis, identify market gaps, and inform business strategies for new or existing establishments.
- Academics and Students: For research projects related to economics, consumer behaviour, urban studies, or culinary trends in India.
- Software Developers: To build applications that require comprehensive restaurant data, such as food delivery apps or restaurant discovery platforms.
Dataset Name Suggestions
- Indian Restaurant Performance Data
- India Dining Trends Dataset
- Indian Food Service Analysis
- Restaurant Ratings and Prices India
- Cuisine and Delivery Data India
Attributes
Original Data Source: Restaurant Ratings and Prices India
QUALITY