I live in the Outer Sunset, a neighborhood in SF with tons of mom and pop Asian restaurants. Many of these restaurants are extremely tasty but may not be able to compete against restaurants that have larger marketing spends or smarter social media presence. This project was an attempt to help such restaurants focus their limited resources in a smarter way.
Hypothesis: The number of “check-ins” at a restaurant has a relationship with various attributes of the restaurant’s profile.
Data:
DataSF: https://data.sfgov.org/Health-and-Social-Services/Restaurant-Scores-LIVES-Standard/pyih-qa8i
Foursquare Venues API: https://developer.foursquare.com/docs/responses/venue
Technologies Used:
Jupyter
Pandas
Numpy
Sklearn
Statsmodels
Full Report: https://docs.google.com/presentation/d/1-pyb9aULS9xuFMswVUQ_8P9gTSsWMMisT_5btSvznJo/edit#slide=id.g251697e114_0_82
Github Repo: https://github.com/manulohiya/checkin-predictor