It was a rainy, dark, fall afternoon in 2019. I sat in my room with nothing to do. Class was over, homework completed, and no major sports were on tv to consume my evening (it was Wednesday, still one more day until Thursday Night Football and the Timberwolves had the night off). I had been thinking of trying something new for a while now, and as I lie on my bed, staring at the ceiling, I figured it was time to turn this thinking into doing. There wasn’t a more perfect night for what I had planned so long to do, and I figured, “If not now, when?”. So, I opened my laptop, hopped on Youtube, and searched “Python tutorial”. I finally brought myself to it; I was going to learn how to code.
Fast forward a year and here we are. I code pretty much every day and plan to pursue a career out of it. I genuinely enjoy it and have done things I never thought I would be able to that one fall night when I felt like banging my head on the wall, struggling with python basics wondering what the heck I had just gotten myself into. I persisted, however, and gradually continued learning into the spring of 2020. I really hit my stride in terms of progression when COVID-19 took over the world. With nothing to do inside during quarantine, I dedicated myself to learning as much python as I could, which really helped the process. Conveniently, spring of 2020 was when my University introduced their new Computational Data Science (CDS) program, which motivated me even more. In fact, once I found out about this program I went straight to student services, dropped all four of my current classes (this was only the second day of the semester, thankfully) and reregistered for CDS classes to start my progress within the program. The timing really could not have been any better! I still have infinite room for growth as a programmer and am eager to learn more and more each day. Needless to say, I am pleased with my first year of progress and can’t wait for what’s to come!
I figured it would be fun to share my favorite projects during this first year of my coding expereince. I have so many ideas in my head and was fortunate enough cross a few off the list by turning those ideas into reality (online class and a shorter semester really helped with this 😂). So, without further ado, let’s get into it!
NFL Receiver Dashboard
For a long time now I have wanted to create a web app with the open source python framework, Streamlit. It’s an incredible software that makes creating data science and machine learning dashboards a breeze and even offers free hosting! My first Streamlit creation is an NFL Receiver Dashboard that runs analyses on any NFL wide receiver or tight end with at least 30 targets in the 2020 season. Player info, a game log, and six visualizations of various metrics are generated upon player selection, all of which are filterable by week! I really enjoyed this project and encourage anyone who is interested in creating a data web app to check out Streamlit.
My Twitter Account
Once I understood the basics of coding, I wanted to give myself some motivation to continue learning. With no summer job due to the pandemic, I wanted to make sure I made full use of my free time and really hone in on my python skills. Thus, I created a twitter account dedicated to sports analytics using python. I made it a summer goal of mine to post at least five times a week, which I ended up achieving! I still post very frequently and have even gained a small following that I am proud of. If you haven’t yet, make sure to check it out, and if you enjoy the content, give me a follow! I highly encourage anyone who is interested in coding to share their work as much as possible. Even if you aren’t confident in it, there are very helpful people that will provide feedback and give you tips. Also, it is great for archival purposes that may benefit you when looking for a job down the road. In fact, there are people in the sports analytics community that attribute their public work as one of the main reasons they landed a job. Only good things come from sharing your work, and it’s enjoyable to be a part of such a great community!
Python Data Science Tutorial using NFL Play-by-Play Data
“You never really learn something until you can teach it” is one of my favorite quotes. Being able to understand source material to both execute and explain it well enough to someone who doesn’t, in my opinion, is a clear pathway to mastery. Possessing the ability to go through a process in your own head, work out the kinks, and turn it into actionbable info is a signal you have truly learned the topic at hand. This was one of two main reasons I decided to create my own python tutorial. The other reason was I simply felt as though it was my due diligence, as I have benefitted from so much help, teaching, and open source when I was beginning with my coding journey. After some careful planning and brainstorming, I created a full on in-depth python data science tutorial using NFL play-by-play data that covers basic python syntax, exploratory data analysis (EDA), one-hot encoding, data visualization, creating a function, and more! I really enjoyed this project; it tested and solidified my knowledge on the topic and felt rewarding to share some open source code with the community, both of which were my two main objectives!
This website!
While not really a data science project in it of itself, I am pretty excited about this website! I think it’s a perfect place to aggregate all the data science work I have done to share with anyone who may be interested. This will be yet another incentive, like my twitter, to continue learning as much as I can in order to turn my ideas into reality.
There you have it, some of my favorite projects of the year! I’m definitely ready to move on from 2020, though, and am very excited to see what 2021 has to offer. Thanks for reading!
