Project Title

• Mapping the Spatial and Temporal Patterns of Bedbug Complaints in New York City

Project Description

• Willem Helf and I developed a spatial heatmap of bedbug complaints using data found on NYC 311 complaints. This project showcased the in-depth collaboration required to develop a reproducible project. 

Methods

• We collected the bedbug dataset from NYC Open Data, then began filtering for the time period we wanted to focus on. We began to analyze the spatial and temporal patterns of the complaints. We identified that complaint correlation was associated with communities that could make the call to address an infestation. All our work is available on a GitHub repository for viewing.
  
  

My Role

• I was tasked with locating the datasets and setting up the groups' Google Drive to bounce ideas off one another asynchronously. I then took on the task of focusing primarily on writing the final reports, knowing I wanted to highlight the strengths I could bring to the group: writing.

Learning Outcome Achieved: Research

• I researched bedbug complaints reported in the 311 Open Data alongside my groupmate. We approached this qualitative research with the idea that there would be a correlation between 311 complaints and the location of the call. And there was a correlation, simply put, well-off areas were afforded the resources to call in complaints. After constructing our GitHub repo and organizing our findings, I wrote our Data Management Plan with the hope that it can be reproduced by others.

Rationale

• This inclusion in my portfolio demonstrates my ability to maintain a research investigation, recognizing that it may change along the way. I was able to hand off data sets to my group member. The important aspect of this project was knowing I was learning new skill sets from the collaboration, such as API calls, and building out a GitHub repo for reproducibility.