WhereSIOUS (Where Should I Open Up Shop)

My project for the City of San Diego while a Insight DS Fellow in Fall 2016

Predicts future business success for a given location in San Diego based on information about that location.

templates/ - folder of HTML webpages
static/ - folder of stylesheets, images, icons, and data to be served to website
also contains some external Python scripts
run.py in the main folder above this one also helps run the Flask-based website

build_features_labels.ipynb - reads in cleaned data and labels and combines important info into CSV files
business_listings.ipynb - read in current SD businesses and mess with the data
housing_employment_income.ipynb - read in housing, employment, and income data from the census and output relevant info
lin_reg_training.ipynb - try to fit data with linear regression
parking_meters.ipynb - read in parking meter info and output useful numbers
population.ipynb - read in census population data and output relevant info
recheck_addresses.ipynb - use the Google Maps API to geocode addresses that failed the census geocoder

Name		Name	Last commit message	Last commit date
Latest commit History 50 Commits
wheresious		wheresious
.gitignore		.gitignore
README.md		README.md
build_features_labels.ipynb		build_features_labels.ipynb
build_features_labels2.ipynb		build_features_labels2.ipynb
build_features_labels3.ipynb		build_features_labels3.ipynb
business_listings.ipynb		business_listings.ipynb
heatmap.ipynb		heatmap.ipynb
housing_employment_income.ipynb		housing_employment_income.ipynb
lin_reg_plots2.ipynb		lin_reg_plots2.ipynb
lin_reg_training.ipynb		lin_reg_training.ipynb
lin_reg_training2.ipynb		lin_reg_training2.ipynb
lin_reg_training3.ipynb		lin_reg_training3.ipynb
parking_meters.ipynb		parking_meters.ipynb
population.ipynb		population.ipynb
recheck_addresses.ipynb		recheck_addresses.ipynb
run.py		run.py