Vacation Location

Inspiration

We wanted a program that would enable homeowners to plan for the future and buy houses that would sustain their market value.

What it does

We developed a program that is able to indicate whether a given county is suitable for buying a house based on previous natural disaster data in the area as well as home costs during a given time frame. The program retrieves the first natural disaster that occurred in the given county and time frame and also retrieves data about housing costs between a year before and after the natural disaster occurred in monthly intervals.

How we built it

We used Svelte for the front-end and Flask for the backend. In Svelte, we utilized Google Maps' API to display a map. In the map, we added markers to indicate natural disasters that occurred in a given county during a given time span. The markers were labeled with the name of the natural disasters and were clickable to show the user data on housing costs of houses in the specified area and time frame. Using Flask, we utilized Zillow's housing cost API as well as the U.S. Census' counties API to get the counties of every state and a typical house cost for a given county during a certain time frame.

Challenges we ran into

Some challenges we ran into were learning how to use the Google Maps API, finding comprehensive datasets suitable for use, correctly parsing and packaging data, integrating Flask with Svelte, making sure files had access to other necessary files by changing directories and paths, and making sure that versions of python were consistent.

Accomplishments that we're proud of

Implementing an interactive map using the Google Maps API, creating a marker on the Google Maps API based on a user's input for location, making the marker able to be clicked and open a pop up with information, accurately parsing through databases for necessary information by using SQLite3, and retrieving data from 12 months before and after a natural disaster's date.

What we learned

We learned how to use the Google Maps API, how to pull data from databases and parse through that data, how to integrate Flask and Svelte, how to create a clickable marker that appears on the map, how to manipulate and send the data from the back-end Flask server to the front-end Svelte server and have that data appear to the user.

What's next for Vacation Location

Some next steps include adding more categories that help to indicate whether a location is fit for a vacation house such as income data, education data, and crime data for a given county during a given time frame.

Built With

• css
• fema-database
• flask
• google-maps
• html
• javascript
• json
• pycharm
• python
• query
• sqlite
• svelte
• us-county-census-database
• vscode
• zillow-database