RashmiMariyappa_Chicago_Video.mp4

Project Summary:

Chicago is divided into 77 official community areas. When most people think about the city they group these community areas by larger location: the North, West, and South sides of the city. Another way Chicago is commonly talked about is in terms of racial segregation with community areas grouped by racial composition. I was interested in ignoring location and racial community identities to see unconventional ways in which these 77 community areas could be grouped, and what commonalities may not be immediately apparent.

Additionally, it seems everywhere you look in Chicago there is a construction crane for new buildings. I also wanted to use the data collected to see what community features are driving building permits in the city.

Steps Involved:

• Constructing my own data set using data various sources including the City of Chicago data portal, DePaul Institute for Housing Studies, Chicago Metropolitan Agency for Planning, and Trulia.
• Data Cleaning and Exploration
• Clustering Community Areas by 311 Requests
• Clustering Community Areas by "Green" Attributes
• Using a Random Forest Model to Determine Community Area Features Driving New Construction Over Renovation
• Evaluating the Random Forest Model to Assess the Quality of the Variable Importance Results
  
  

Files Uploaded:

1. "RashmiMariyappa_1_Chicago_Video"
   This is a video presentation providing an overview of the project, analysis, and conclusions. It is embedded in the ReadMe above.
   
   
2. "RashmiMariyappa_2_Chicago_Report"
   This file is a report providing an overview of the project, analysis, and conclusions.
   
   
3. "RashmiMariyappa_Chicago_Code"
   The R code used for the project