Joy Payton
January 13, 2017
Deadbeat investor landlords (defined as owners who have 3 or more properties in property tax delinquency) are a real problem in Philadelphia. We've gathered data to help understand this problem from two sources:
We've organized this data into statistics by census tract, to understand the characteristics of neighborhoods with high levels of deadbeat investor delinquency. We used just one tax year, 2015.
Let's look at tax delinquency for all Philadelphia census tracts:
sum(PhillyHousing$InvestorDelinquentTaxTotal)
[1] 3533812
summary(PhillyHousing$InvestorDelinquentTaxTotal)
Min. 1st Qu. Median Mean 3rd Qu. Max.
16.21 3059.00 9865.00 13490.00 19090.00 87530.00
That's over $3.5m delinquency for 2015 alone! But some census tracts have very little delinquency, while others have quite a lot.
With the data at hand (housing characteristics, poverty and income, and tax delinquency), can we detect any relationships?
We can see by the correlation matrix that many explanatory variables influence each other, as well as predicting tax delinquency.
For that reason, it's a good idea for us to create a quick visualization Shiny web app that will allow us to plot any of those variables against each other.
For now, we're concentrating on discovering single-predictor models, so we'd like to generate plots like the one on the next slide: