Final Project Repository for CSP-571: Data Preparation and Analysis
Project Goal: Find relationship between (inspection data and Yelp reviews) and whether or not a restaurant needs a food inspection.
Structure of the Repository:
To see the data we worked on, click here.
To see the code we used, click here.
- Olugbenga Abdulai
- Vaibhav Ramesh Kunkerkar
- Rahul Maramreddy
- Rishab Panyam
- Nicholas Saveas
Restaurants are a great place to relax, eat, or meet up with some friends, but they can also be a source for infectious food, faulty equipment, and many other health and safety hazards; poorly maintained and poorly staffed restaurants can pose a threat to the well being of those who eat there. In order to prevent this, the US Food and Drug Administration cooperates with state governments to make sure the food establishments are safe for all citizens by performing food inspections. Food inspections are government mandated health and safety checks that ensure a restaurant is up to date with the most recent health standards and regulations (Food Establishment Regulations, 2019).
Las Vegas is a bustling city in Southern Nevada with thousands of restaurants, which means thousands of potential health and safety violations. The Southern Nevada Health District is a governing body which creates and enforces the rules and regulations for the food establishments in Las Vegas (Food Establishment Inspection Process, 2018). Currently, they perform health inspections at a minimum of once per year and assign restaurants a grade ranging from “A” to “C”. Those who receive a grade lower than A will be reinspected in the next 15 days (Grade Cards FAQs, 2018).
The current food inspection process is done at random (Food Establishment Inspection Process, 2018), but there are clues from the people who dine there that the restaurant is in need of an inspection. Yelp, a crowd sourced review forum, contains reviews for food establishments, which, if combined with municipal food inspection data from the Southern Nevada Health District, can yield powerful insights to improve the efficiency of the inspection process.
The goal of this project is to predict the potential number of violations for a food establishment and use this information to prioritize which restaurants pose the most risk and hence should be inspected first. From a more impact-driven perspective, we aim to catch more violations per inspection than the current average with our model and by extension, reduce health risk. We plan to achieve this by analyzing review data from Yelp datasets combined with Las Vegas inspection data. With supplementary data such as weather and demographic data, we can derive even deeper insights as to how climatic conditions and demographic information (e.g. average income in a town) may influence compliance with regulations of food establishments. Insights from such analysis can improve the efficiency of the Las Vegas food inspection process, and if deemed successful, can be extended to other municipalities across the country.
https://docs.google.com/document/d/1w-LSiae4_tRLNMnLZENf1jWiFXP_9tq4ScAD8FhnRMA/
https://docs.google.com/document/d/1DCchORF93azwe97bItrNXb1GRt5IfqUVMVMywQXtWLc/
https://docs.google.com/document/d/1tt0rZ0FXRpEaTN2M2c90hwfx0_93ehBiuTwqAZDQIrw/