Cancer Incidence and Mortality across US Counties

UC Berkeley Data Analysis
Final Project

Utilizing Machine learning to build a dynamic table, react to user input using JavaScript and incorporate it into a web site using HTML, CSS and Bootstrap for Lung Cancer across the state of California. We will use our knowledge of Python to create the different datasets and then utilizing Tableau create various visualizations finally incorporating it into an interactive model on HTML format

Tableau Visaulizations

Background

MUA= Medically Underserved Area Index
Age adjusted Mortality Rate per 100,000 = death rate/population of county*100,000
Age adjusted Incidence Rate per 100,000= incidence rate/population of county*100,000

Goals

Cancer Mortality or Incidence and Medically Underserved Index per County
Cancer Mortality or Incidence and Demographic Data per County
Cancer Mortality or Incidence and Median Household Income per County

Our Team

Andrew

Leyzer

Amar

Henry

Robyn

ERD

<<<<<<< HEAD >>>>>> bf3de97e38e1f544272a7ed2c9da436086adf98e title="Our ERD">To explore our ERD click here.

About Us

Our team is a diverse, highly motivated, and communication focused group of free lance designers. We have focused on developing a project that creatively and succinctly depicts the relationships between cancer incidence, mortality, and the classification of medically underserved areas. We are Data Analytics enthusiasts and love working on complex data to clean make it simplified and presentable using Machine learning and web scraping with our skills in Java and Python

Our Skills

CSS

Bootstrap

HTML

JavaScript

Python

Git

Project Summary

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