Given the massive number of history changing events that have happened in the last 12 months many people have found themselves asking just this question. This project aims to provide a simple way for people to find cities in the US that fit a given set of criteria to live in.
Proposed Datasets:
- Movehub: https://www.kaggle.com/blitzr/movehub-city-rankings?select=movehubcostofliving.csv
- National Parks Data - https://www.latlong.net/category/national-parks-236-42.html
- Numbeo: https://www.numbeo.com/api/doc.jsp
We will use this data to compare cities across the US with respect to cost of living, consumer prices, crime rates, education, and other factors. We will then recommend to the user the best places that they may want to consider for a future place to live based upon their input criteria weighted by cost of living in each location.
We will use a sequential database based upon city name as the primary key. We will use a reference table which will contain the locations of each city to be placed on the map. Our flask server will communicate with the front end webpage which will take the user’s filtering preferences in order to generate the correct city names.
server.py: Flask app which renders the html and communicates with the PostgreSQL database
static/js: Folder which contains the javascript code which is called by the html. The main function of the javascript is to take filtering data from the user, send these filters to the Flask server, then place the cities on the map, in the table, and on the interactive plot.
qol_db/: Folder which contains python files which commnicate with the database with the user input filters.
clean_data.py: All requests to the Numbeo website functions for cleaning the data and storing the db.
index.html: Rendered html for the main page which displays all of our javascript created elements and contains the plots for user input.