A look into School Profile Information for the school year of 2016/2017.
Data set from Chicago Data Portal School profile information for all schools in the Chicago Public School district for the school year 2016-2017.
Filter conditions used:
A look into the primary crime type of WEAPONS VIOLATION from Chicago’s crime dataset on data.cityofchicago.org. Primary Type of weapons violation includes such descriptions as; DEFACE IDENT MARKS OF FIREARM, POSS FIREARM/AMMO:NO FOID CARD, RECKLESS FIREARM DISCHARGE, UNLAWFUL POSS OF HANDGUN, and others.
Multifamily public housing development visualizations by unit count/neighborhood for multifamily property types, and a word cloud of the most popular management companies. The data is from data.cityofchicago.org
The affordable rental housing developments listed below are supported by the City of Chicago to maintain affordability standards.
Out of curiosity in seeing Comcast’s political influence in Illinois over time, I parsed the 650,775mb file called Receipts.txt. Below is a bar chart of yearly recorded donation totals from 2000 through 2015-08.
Not being very politically oriented, I wanted to somehow relate the donations to candidates. But in the form of the available data, it appears Donors make contributions to Committees, and Committees support a Candidate. But I do not know if Candidates and Committees are a One to One relationship at the time of typing this.
Parsing the text file called CmteCandidateLinks.txt, I related the Committee Id with the candidate Id. Parsing the text file called Candidates.txt I relate the Candidate Id to the Candidate name.
Lots of candidate duplicates per donation entry. Majority of Committees represent the same candidate under different ids, while some committees represent multiple candidates. Example here:
So I decided to distribute each donation amount between a potential multitude of candidates. I did this by dividing each donation by the number of candidates which belong to the committee recipient. From that, I got this list of Comcast’s Top Illinois Candidates.
I came across an interesting data set while browsing datacatalog.cookcountyil.gov. It can be found here. Judging by the title, it appears to be healthcare costs for the month of June in the year of 2012. There is no description, or any additional information I could find about it. The data contains a department code, a number of employees, and a total cost. It looks like this:
I was curious, so I took the average cost of employee count (Cost / Emp num), per department. I correlated the department numbers to labels from an alternative dataset also found on cook county’s data catalog.
My experiment resulted in two bubble charts.
Greater than 40 Employees
Greater than 40 Employees and less than 1,000
And now here’s the second chart processed with Google’s Deep Dream