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Living Wage Calculator: Abstract

Role(technical)

Role(creative)

Sole Engineer and Designer:
  • UI/UX Designer
  • Data Collection/ Web Scraping
  • Data Analytics
  • Data Visualization
  • Cloud Architect
  • Software Architect
  • Lead Developer
  • Cloud SysOps(active)

Motivation

Living Wage - a bipartisan topic that still somehow acts to bifurcate groups of people who should be united. I believe that through personalized education which normalizes a living wage based on location based real-time living cost data, this bifurcation can be eliminated and people united. This application was an exploration of that theory.

Creative Direction and Educational Strategy:
  • Set goals for user education
  • Living Wage Research
  • Developed education strategies based on data availability
  • Define Goals and Direction

Vision

Create an engaging tool for education that the non-profit one fair wage can use for outreach on location at public events.

Identifying state, county, marital status and dependent information we dynamically generate data and graphs that quickly educate the public about their unique position in the economic environment.

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Living Wage Calculator: Introduction

infograph

1/ Collect

  • Collect a million values relating to 3000 different locations
  • 160k graph iterations generated
  • 500k unique communicable data points organized

2/ Create

Create four dynamic graphs, 16 dynamic data points communicated for specific educational goals.

3/ Educate

Educate the public at events, rallies, and on the street. Users sign petition and sign up for outreach.

Living Wage Calculator: Discussion

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Dynamic Data

based on user's: state, county, dependence, & partner status

first dynamic screen in living wage Calculator

Basic Annual Living Expenses by Category

  • 54,000 uniquely generated iterations.
  • Budgeted annual expenses(@ living wage) based on user input
  • Goal: Take abstract concept [living wage measured per hour] and visualize it by expense. When calculating a living wage this is what is budgeted
Graph Basic Annual Living Expenses by Category

Living Wage Calculator: Technical Details

Cloud Architecture

Cloud infra
Cloud infra

Cloud Tech Stack

Chaperone App Tech Stack

App Features

  • Redundant, highly available Ec2 servers running Ubuntu Server
  • AWS Auto-Scaling used for failover and scaling
  • Lambda Serverless infrastructure used for burst processing: media formatting and release form generation
  • Nginx running on Ec2 as reverse-proxy

Wage Calculator App

Chaperone App Tech Stack

App Features

  • Mobile Application/Web application programmed in React Native and React
  • Connect to ec2 servers in cloud for user data upload
  • Redundant local storage for offline modes, error logging and user upload confirmation

Data Science Stack

Chaperone App Tech Stack

Stack Implementation

  • Use Python, Python Requests, Beautiful Soup, Jupyter Notebook,to extract data from university, government, and market websites. Implemented Pandas to store and extrapolate data.
  • Use Numpy, Matplotlib, and Seaborn to calculate, format and visually represent relevant data.
  • Use the combination of Python with all prior named libraries to automate the entire process and generate over 300,00 graphs and 400,000 values for programmatic access.

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