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Zomato Reviews and Restaurant Attributes
Product Reviews & Feedback
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About
This collection of Zomato reviews data is tailored for robust data analytics projects. The information captures detailed metadata and customer feedback regarding restaurants and cafes primarily located in Bengaluru, India. It serves as an excellent resource for performing crucial data preparation tasks, including cleaning, removing redundancies, and handling missing values. Furthermore, the dataset enables advanced exploration, supporting visualisation tasks such as analysing table booking rates versus ratings, identifying optimal restaurant locations, and classifying different restaurant types. It provides the foundation necessary for machine learning applications, specifically regression analysis like Linear, Decision Tree, and Random Forest models.
Columns
- url: The specific web address for the restaurant listing.
- address: The physical location or address of the establishment.
- name: The trading name of the cafe or restaurant.
- online_order: A boolean field indicating if the restaurant accepts orders placed online.
- book_table: A boolean field indicating the availability of table booking services for dine-in customers.
- rate: The customer rating assigned to the establishment (note: approximately 15% of values are missing).
- votes: The total number of votes the restaurant has received.
- phone: The primary contact details for the restaurant.
- location: The general area or region where the establishment is located (e.g., BTM, HSR).
- rest_type: The classification of the cafe (e.g., Quick Bites, Casual Dining).
- dish_liked: A description of the most frequently liked dish at that cafe (note: approximately 54% of values are missing).
- cuisines: The specific type of food or cuisine served by the restaurant.
- approx_cost(for two people): The estimated cost for a meal for two individuals, typically ranging from 40 to 6,000 Rupees.
- reviews_list: A list of reviews provided by customers.
- menu_item: A list of items available on the restaurant's menu.
- listed_in(type): The category under which the restaurant is listed (e.g., Delivery, Dine-out).
- listed_in(city): The specific city sub-area the restaurant is listed within (e.g., Koramangala 7th Block).
Distribution
The data is provided in a single CSV file named
zomato.csv. The file size is 574.07 MB and it contains 17 columns. The structure holds 51,717 total records. The data quality is high with most columns having 100% valid records, though fields like rate and dish_liked contain significant missing values.Usage
Ideal applications include conducting extensive exploratory data analysis, performing data cleaning and transformation workflows, and developing visualisations to illustrate market trends. Specific use cases involve determining the most popular restaurant chains in Bengaluru, analysing the relationship between restaurant type and customer rating, modelling the cost distribution, and studying customer sentiment through the
reviews_list column. It is also suitable for building predictive models using regression techniques to forecast outcomes such as restaurant rating or vote count.Coverage
The dataset focuses geographically on the city of Bengaluru, India. Coverage is specific to different locations and zones within the city, such as BTM and HSR. The scope covers various aspects of the food service industry, including restaurant types (like Quick Bites, Casual Dining) and service types (such as Delivery and Dine-out). Details regarding the specific time range of data collection are not available.
License
CC0: Public Domain
Who Can Use It
- Data Scientists and Machine Learning Engineers: Utilising the data for building and training regression models to predict performance metrics.
- Market Researchers: Analysing customer reviews and sentiments to understand market needs and preferred cuisine types.
- City Planners/Restaurant Entrepreneurs: Identifying successful locations and restaurant types by studying location density, ratings, and cost correlations.
- Students and Educators: Learning fundamental data cleaning, data visualisation, and exploratory analysis techniques.
Dataset Name Suggestions
- Bengaluru Zomato Restaurant Performance Metrics
- Indian Food Service Data Analysis Project
- Zomato Reviews and Restaurant Attributes (Bengaluru)
- Food Delivery and Dine-out Business Metrics
Attributes
Original Data Source: Zomato Reviews and Restaurant Attributes
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