I wanted to see whether evictions are on the rise in Massachusetts. I also wanted to learn how to scrape from Tableau visualizations in cases where it's otherwise not possible to download the data.
I found that evictions have spiked in MA this year. Hard-hit communities include Fall River, Holyoke, Springfield, Pittsfield and New Bedford, where evictions and money order judgments are disproptionately high.
I used the following data sets for the state of Massachusetts:
by location eviction orders since 2020
#by location eviction orders since 2022
I used Tableauscraper and for loops to go through the data, get worksheet names and then save the .csv files to a folder. I then analyzed the data using Excel pivot tables for the simple analysis of finding communities with the biggest counts of eviction orders and money judgments. I added Census population data , cleaned the data and used V Lookup to match communities with populations. I was unable to match every community with population data -- partly because the state data had a breakdown for Boston neighborhoods.
A section about what new skills, approaches, etc you used, or where you grew the most during the project
I gained new skills in web scrapign and working in Github to find tools created by other users and modifying them to suit my own purposes. I have gained more confidence in how to use for loops to iterate through data and find what I need. I'll be able to use this code to scrap data from other Tableau visualizations.
A section about things you tried to do or wanted to do but did not have the skills/time (but if you have more time you might do)
I want to use MySQl or R to analyze and clean the data next time. I used Excel because I thought it would be straightforward, but I think I would have saved more time using SQL. I'd like to scrape data from Apartments.com for reporting on the rental market in MA next.
Link to Github project: here