The Boston Housing Crisis

An exploration into the optimal subsidization strategy and PUMS dataset for Boston Area

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Inspiration

Kirk has read about the scarcity of affordable housing in the Boston area, and we set out to explore potential fix to ameliorate the problem.

What it does

There are several components:

  1. we analyzed mathematically the optimal way to distribute Affordable Housing benefits to the underprivileged

  2. we uses pandas to filter and analyze data in the 2013-2017 PUMS dataset (167315 entries of household listings in Massachusetts)

  3. we sampled the household data to simulate a distribution and collects results on the geographical distribution of the dispersion of funds

How we built it

Python

Challenges we ran into

We have occasional conflicting views regarding to where the project leads, and it was hard to resolve them

We also attempted to distribute the workload evenly, but the division of labor created chaos because we have expertise in entirely different fields

Accomplishments that we're proud of

We were able to do math, yay!

We were also able to learn a lot regarding to database processing and information summary.

What we learned

The Boston Housing Authority is taking the correct method of distributing Affordable Housing benefits

What's next for The Boston Housing Crisis

If we have time, we will revise the code because the current code is written by somebody who has just learned Python and has a very poor organization.

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