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Zomato Online Ordering Insights
Data Science and Analytics
Tags and Keywords
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Free
About
This dataset presents a collection of Zomato restaurant data, suitable for data analysis and visualisation. It offers insights into restaurant attributes, their ratings, costs, and online ordering capabilities, serving as a valuable resource for understanding restaurant dynamics.
Columns
- name: The specific name of the restaurant. 'San Churro Cafe' is a frequently occurring name.
- online_order: A boolean field indicating if the restaurant facilitates online orders. Approximately 39% of restaurants accept online orders, while 61% do not.
- book_table: A boolean field indicating if table booking is available. Around 5% of restaurants offer table booking, whereas 95% do not.
- rate: The rating of the restaurant, typically presented out of 5, such as '3.8/5'. '3.8/5' is the most common rating. This field has 20 unique values.
- votes: The total number of votes or reviews a restaurant has received. Values in the dataset range from 0 to 4884, with an average of 265 votes.
- approx_cost(for two people): The estimated cost in Indian Rupees (Rs) for two individuals dining at the restaurant. Costs range from 100 to 950 Rs, with an average cost of 418 Rs.
- listed_in(type): Describes the primary type of establishment, such as 'Dining' or 'Cafes'. 'Dining' is the predominant type, accounting for 74% of entries.
Distribution
The dataset is provided in a CSV file format and has a file size of 6.46 kB. It is structured with 7 distinct columns and contains 148 valid records or rows.
Usage
This dataset is ideal for various applications including data analysis, data visualisation, and exploring characteristics of restaurants listed on Zomato. It can be effectively utilised with Python libraries such as Matplotlib and Seaborn for creating charts and extracting meaningful insights into restaurant operations and customer engagement.
Coverage
Information regarding the geographic location, specific time range, or demographic scope of the data is not available within the provided sources.
License
CC0 Public Domain
Who Can Use It
This dataset is particularly useful for data analysts, students, and programmers interested in gaining insights into the restaurant industry. It is also well-suited for beginners looking to practice data visualisation and data analytics techniques using real-world data.
Dataset Name Suggestions
- Zomato Restaurant Data
- Restaurant Analytics Dataset
- Zomato Online Ordering Insights
- Indian Restaurant Data
- Dining Establishment Data
Attributes
Original Data Source: Zomato Online Ordering Insights
QUALITY