New Data Variables for Canadian Commercial Line Insurance

Goal:

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The overall aim of the project is to create new variables for Canadian businesses by leveraging different external data sources.

Data Source Chosen

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The data source chosen for this project is Opentable.com

Techframework Used

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The code is written in Python language

Installation Required

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• Chromedriver
• Selenium
• Pandas
• Numpy
• BeautifulSoup
• Time
• os
• webdriver_manager.chrome
• multiprocessing

List of variables extracted from restaurants on Opentable

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• Name of Restaurant
• URL of Opentable.com
• Booked: number of times booked today via Opentable
• Rating
• Review Count: total number of reviews
• Price Range
• Cuisine
• Address, Google Address, location
• cross street
• neighborhood
• public transit
• hours of operation
• phone number
• website
• cuisines
• dining style
• dress code
• parking details
• payment options
• additional
• food,service, ambience, value rating
• Noise Level
• Top Tags, Loved for
• No. of Photos
• cleaning & sanitizing, protective equipment, screening, physical distancing
• executive chef
• entertainment
• menu
• catering
• private party facilities, private party contact

Data Processing

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• Alcohol available: look for 'bar','beer','cocktails','wine' and 'corkage' in additional column of restauratant
• Wheelchair access: look for 'wheelchair'
• Outdoor seating: look for 'outdoor'
• Fireplace: look for 'fireplace'

Functions Included

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• main
• listings
• getinfo
• combine

Input Required

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• location id of Opentable.com
• cuisine id of Opentable.com

listings() function

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• scrape all restaurant names of urls of given cuisine and location
• will loop up to 10 times as Opentable has max 10 pages of results for each query

getinfo() function

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• scrape info of the restaurant giving the url from main

combine() function

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• combine all csv of the same region to a single csv