City of Boston - Data Analysis

Jan 2024 - May 2024

In collaboration with the City of Boston and my team’s client, Hope R., I helped lead a group of students in a comprehensive analysis of Boston's housing landscape.

The primary focus of this project was to investigate the impact of renovations on bedroom and living area changes, as well as to examine the demographic composition of affected neighborhoods.

Uncovering Insights Through Data

By leveraging a data-driven approach and using advanced analytical techniques, we uncovered some valuable insights that could inform policymakers and stakeholders in developing equitable and sustainable housing solutions.

You can access our full analysis code here, or view our report as well!

I had the privilege of leading a talented and dedicated team consisting of 4 members. As the team lead, my responsibilities included:

  • Organizing and managing our team's Trello board for efficient task allocation and tracking

  • Coordinating with the project manager and client to provide regular updates on our progress

  • Facilitating effective communication and collaboration among team members

Team Responsibilities and Leadership

Through our analysis, we arrived at several key takeaways:

  • Renovations, on average, do not result in a loss of bedrooms or living area

  • Changes in living area and bedroom count during renovations are largely independent

  • Neighborhoods such as Brighton (with a majority young, White population) and Dorchester (with a majority middle-aged, Black/African-American population) experienced significant housing market changes, though we can't conclude which specific demographics have been affected by these changes.

Detailed Outline of my Specific Contributions:

Investigating the impact of renovations on bedrooms and living areas.

  • Analyzing trends in the average number of bedrooms and living area per property over time

  • Exploring the correlation between changes in living area and bedroom count due to renovations

  • Conducting linear regression analysis to identify potential predictors of bedroom and living area changes

Examining the demographic composition of areas impacted by housing changes.

  • Mapping the modal age group, race, and household type per neighborhood

  • Analyzing the demographic breakdowns of significantly impacted neighborhoods like Brighton and Dorchester

  • Providing insights into the populations potentially affected by housing market shifts

Developing and contributing to the key Jupyter notebooks:

  • Variables_in_Property_Assesment-Yearly_Analysis.ipynb and Renovations&Bedrooms_Analysis.ipynb

  • Living Room Correlation.ipynb

  • Linear Regression on Bedrooms.ipynb

  • Updated_Heatmap notebooks

  • Organizing and compiling both the GitHub and Report

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