:money_with_wings: Determine where you can afford to live in Washington State based on a wage calculator
openseattle_greenlines
openseattle
Overview
Abstract
## GreenLines
One of the biggest problems for people making a specific wage in Seattle, is knowing where affordable places where to live. Rather than drawing redlines to show where the areas in Seattle are considered poverty level. We decided to make these same area and draw them green. We then added the feature to show based on hourly income and HUD rent data, the areas in Seattle that are considered affordable for rent.
Our app is live at [GitHub](http://codeforseattle.org/greenlines/). You can select and adjust your hourly wage (in dollars) to determine affordable housing districts in Seattle.
## Challenge and Approach
Our approach for satisfying this challenge was to:
- Utilize the 50% affordability rate (wage versus cost of rent) of low-income workers based on research performed by Zillow, [The Rent is Too Damn High](http://www.zillow.com/research/rent-affordability-2013q4-6681/).
- Show what areas in Seattle are considered affordable based on HUD and US Census GIS data
- Determine what ranges of hourly wages based on a 40 standard hour week schedule, can an individual afford to live in Seattle.
- Visualize it on a map and render it to be mobile compactable via app interface or mobile website
## Team Members
Our team is comprised of:
- [@loudest](https://github.com/loudest) - README.md writer, man who speaks softly and carries a big $15 sign.
- [@amiranda222](https://github.com/amiranda222) - Alexander the Great, The Master of All Things Digital
- [@dcbaron](http://github.com/dcbaron) - Has a 9 ol'clock shadow, our number crunching caffeine data junkie
## Technologies, APIs, and Datasets Utilized
We made use of:
- [Flask](http://flask.pocoo.org/) for filtering GIS data and JavaScript [gmap.js] (https://developers.google.com/maps/documentation/javascript/events) for client-side JavaScript mapping.
- [HUD Location Affordability Index](http://zillowhack.hud.opendata.arcgis.com/datasets/27b53ea69f98474eb002ac3b9c6b51eb_0) GIS data for rent and GIS data
## Contributing
In order to build and run our app:
1. [Deploying server-side code] backend/ are Python server side Flask to filter the wage filter for Seattle rent data.
2. [Running client-side code] / run it via HTML site
Our code is licensed under the [MIT License](LICENSE.md). Pull requests will be accepted to this repo, pending review and approval.
One of the biggest problems for people making a specific wage in Seattle, is knowing where affordable places where to live. Rather than drawing redlines to show where the areas in Seattle are considered poverty level. We decided to make these same area and draw them green. We then added the feature to show based on hourly income and HUD rent data, the areas in Seattle that are considered affordable for rent.
Our app is live at [GitHub](http://codeforseattle.org/greenlines/). You can select and adjust your hourly wage (in dollars) to determine affordable housing districts in Seattle.
## Challenge and Approach
Our approach for satisfying this challenge was to:
- Utilize the 50% affordability rate (wage versus cost of rent) of low-income workers based on research performed by Zillow, [The Rent is Too Damn High](http://www.zillow.com/research/rent-affordability-2013q4-6681/).
- Show what areas in Seattle are considered affordable based on HUD and US Census GIS data
- Determine what ranges of hourly wages based on a 40 standard hour week schedule, can an individual afford to live in Seattle.
- Visualize it on a map and render it to be mobile compactable via app interface or mobile website
## Team Members
Our team is comprised of:
- [@loudest](https://github.com/loudest) - README.md writer, man who speaks softly and carries a big $15 sign.
- [@amiranda222](https://github.com/amiranda222) - Alexander the Great, The Master of All Things Digital
- [@dcbaron](http://github.com/dcbaron) - Has a 9 ol'clock shadow, our number crunching caffeine data junkie
## Technologies, APIs, and Datasets Utilized
We made use of:
- [Flask](http://flask.pocoo.org/) for filtering GIS data and JavaScript [gmap.js] (https://developers.google.com/maps/documentation/javascript/events) for client-side JavaScript mapping.
- [HUD Location Affordability Index](http://zillowhack.hud.opendata.arcgis.com/datasets/27b53ea69f98474eb002ac3b9c6b51eb_0) GIS data for rent and GIS data
## Contributing
In order to build and run our app:
1. [Deploying server-side code] backend/ are Python server side Flask to filter the wage filter for Seattle rent data.
2. [Running client-side code] / run it via HTML site
Our code is licensed under the [MIT License](LICENSE.md). Pull requests will be accepted to this repo, pending review and approval.
Authoring entity
| Agency Name | Role | Affiliation |
|---|---|---|
| openseattle | owner | http://openseattle.org/greenlines/ |
Language
English
Methods, software and scripts
Software
| Name | Libraries or packages used |
|---|---|
| Python |
flask, os, json
|
| CSS | |
| JavaScript |
License
| Name |
|---|
| MIT License |
Metadata production
Producers
| Name | Role |
|---|---|
| GitHub Bot | bot |
Date of Production
01 December 2019