It was a normal morning in red zone Cambodia. I heard that police checkpoints were becoming more numerous, even stopping food delivery drivers. I would need to think about this soon. Especially as I was short on mixers. Cocktails by the pool weren’t as nice when your cocktail was a coffee mug of cheap vodka. I also should have done […]
(Data Science people: I did this with pandas and SQL in a Jupyter notebook. You can take a look at my github. It ain’t pretty though. The graphs below were matplotlib) (All data used in creating these rankings is publically available at pdga.com) Disc Golf Fans… It was a weekend where the best in the land were spread out across […]
Man I learned a lot doing this project. So… more stuff I learned (or re-learned), when making my disc golf power rankings happen (part 1 is here)… So I have a list of lists, how do I get the name of list instead of its contents? So, for some reason I wanted to make a list of lists of the […]
Ok. Maybe that’s a disingenuous title. Basically I sat in the darkness of my apartment, while my girlfriend wondered what was wrong with me, and typed stuff into a jupyter notebook. Then I commented that out and typed something else. Then I gave my screen a dirty look. Then I realized I typed a period instead of an underscore. Repeat. […]
Cornhole, the sport of midwestern American tailgaters, has arrived in Cambodia, kinda. (If you don’t know what I’m talking about, meaning you’re in that 80% of my two-person readership [Haven’t gotten to stats yet in my Coursera classes], check out https://www.playcornhole.org/pages/rules for info about the glorious sport of cornhole.) A bar I frequent now has some boards that are getting […]
Writing this a good bit late but whatevs… So as my Learn SQL Basics for Data Science Specialization (UC Davis, Coursera) began to wind down, it came time to decide, what’s next? I realized that I really like SQL. And even though not all the classes in the Learn SQL Specialization were wonderful (looking at you Spark), I decided I […]
So, when we left off we were looking at population, GDP per capita, and urbanization metrics. Nothing jumped out except the urbanization… (tl;dr the first five posts in this series… I’m looking at connections between population and economic metrics and country success at the olympics. To start at the beginning, check out part 1.) (Standard warning in all my posts. I’m […]
Ok. So I have my main working tables, Athletes and Countries, (finally) done… (tl;dr the first four posts in this series… I’m looking at connections between population and economic metrics and country success at the olympics. To start at the beginning, check out part 1.) (Standard warning in all my posts. I’m a beginner. Nothing below should be taken as the […]
OK. So I just figured out what to do about countries being called different names across datasets are two Congos are now “Congo (Kinshasa)” and “Congo (Brazzaville)”. I worry though, I’ll have to deal with this issue again… (tl;dr the first three posts in this series… I’m looking at connections between population and economic metrics and country success at the […]
And back to work. When we left off I had just built the Countries DATAFRAME… (tl;dr the first two posts in this series… I’m looking at connections between population and economic metrics and country success at the olympics. To start at the beginning, check out part 1.) (Standard warning in all my posts. I’m a beginner. Nothing below should be […]