I was recently working with Apple Podcasts charts data and was curious how much the charts change week-to-week. I am already scraping some Apple Podcasts charts already for a separate project, so I decided to look at the Science category for the US charts.
It turns out that the top few podcasts are fairly stable, but even just in the top 20, the podcasts change quite a bit.
I am working on a new guide for creating scatterplots with the Python Seaborn package and thought I’d use a Fortune 500 dataset for the examples. I was curious to see how revenue compares against the number of employees.
I discovered that Walmart and Amazon have 5x as many employees as the next companies, so I couldn’t even see most of the companies on the chart with them in it. I didn’t realize just how large their workforce is.
After removing them, I noticed a couple of interesting points:
CVS is grouped closer to the healthcare and tech companies than the retail companies
Exxon Mobil has extremely high revenue per employee, even higher than a lot of tech companies
Of course, revenue only reflects raw sales, and we’d have to look at profit and EBITA to really see where the differences are. But, it was still fun to explore with.