We were interested in a topic that's closely related to us, so we
adopted the data set "College tuition, diversity, and pay" from
Kaggle. This dataset is pretty clean and comes in 5 separate CSV
files, and we think it would be easy to do for our mini project 2. As
we were discussing the focus of our visualization, we reached the
consensus that we are really interested in a couple of aspects:
tuition cost, salary after graduation (i.e. early career), salary in
mid career, and the impact of school rankings and geographical
locations. Next, we put our focus in making the visualizations of our
selected topics. Hope you find it interesting!
Here are some notes from the source website:
"Historical averages from the National Center for Education Statistics
(NCES) - spanning the years 1985 - 2016. Tuition and fees by
college/university for 2018-2019, along with school type, degree
length, state, in-state vs out-of-state from the Chronicle of Higher
Education. Diversity by college/university for 2014, along with school
type, degree length, state, in-state vs out-of-state from the
Chronicle of Higher Education. Example diversity graphics from
Priceonomics. Average net cost by income bracket from
TuitionTracker.org. Example price trend and graduation rates from
TuitionTracker.org Salary potential data comes from payscale.com."