And we are back. After a weekend where most of top players were out in Stockton for the OTB Open, there is some movement in the top tens, but nothing too wild. (If you are a data science type, I used some beautiful soup, pandas, SQL… y’know. Stuff like that. And, no, I didn’t use them well. I tried though. […]
(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 […]
So about a week ago, this dude Mckay Johns started popping up on my social media feeds talking about sports, and analytics, and sports analytics, and stuff like that. My mind started racing… and here we are. A bunch of days with minimal sleep and an angry girlfriend later… power rankings. (Disc golf talk incoming… if you have arrived here […]
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 […]
Ok. Back to work on the capstone for Learn SQL Basics for Data Science (via Coursera). I’m trying to look at the connections between a country’s population and economic metrics and success in the olympic games. I’ve collected all the data, gave it a quick look, and now it’s time to dig in. (If you want to see how I […]
So we’ve come to the last course in the Learn SQL Basics for Data Science specialization from UC-Davis (via Coursera), the capstone project. Here we supposedly take what we learned during the other courses and make something. Really, though, in the early days of this course I’m still learning a lot. So I’m writing this series of posts as a […]