So, I took a few weeks to get on-ramped with Pandas 0.23.0 and Python and am still learning the ropes. Though, I wanted to share some output. Namely, using the San Jose Open Data Portal, there were some good insights to be had from looking at economic data pushed out by the city for 2006-2016.
What did I do?
- Looked at unemployment rates across various housing prices (condos/townhomes & single-family homes) using ordinary-least-squares regression.
- Looked at, over time, labor force and housing price changes.
SJ Economic Changes, 2006-2016
Condo/Townhome prices vs. SJ Metro Unemployment
Single Family Homes prices vs. SJ Unemployment
What did I find? Namely, housing prices are increasing rapidly compared to labor change (i.e. job growth) in San Jose over the course of 2006-2016. Also, there’s a strong correlative relationship between something that we all take for granted and as obvious: increased housing prices in San Jose runs with lowered unemployment rates.
If you’d like to look at the data analysis done, here’s the GitHub repo. If you have any questions/comments/suggestions on more analysis, feel free to contact me via Twitter, GitHub, or LinkedIn.