Like many of us, I’ve tried to maintain a somewhat active blog enumerating what I’ve been working on, and what I’ve been thinking about.
Despite being reasonably successful at writing posts on a regular interval, I’ve been somewhat unimpressed with the quality of my writing.
I’ve been working on a configuration management project recently, and as a consequence have been working regularly with YAML. It’s a very capable markdown language, but it gets unwieldy very quickly.
I’ve come up with a hacky - yet, in my mind, pretty awesome - ‘solution’ to cut down on YAML bulk and allow for some pretty surprising templatization of data.
So, in early June when I first had the inking of an idea to do this project, I jumped head first into the world of realtime data aggregation and visualization, and had a really great time.
Over the past few years, GamesDoneQuick has become quite a livestream phenomena as a biannual charity livestreams of games from throughout the history of video games. I love watching these streams, and because of the unique dataset, was interested in the relationships between games, platforms, release years, and the current speedrun ‘time-to-beat’. With SummerGamesDoneQuick 2016 rapidly approaching, I decided it’d be a good time to make some visualizations.
Being a Python nerd, I started my data visualization with an Jupyter notebook and a generous application of matplotlib.
I’ve been a long-time listener of podcasts. I used to listen to tons of NPR Podcasts like “This American Life”, “Car Talk”, and “Wait Wait Don’t Tell Me”. When I was in high school, I didn’t have a ton of ‘listening time’ as I was usually either in front of my computer, or in my car, where I could listen to NPR live.
Now, in college, I have lots of walking ‘commute’ time, and podcasts have reentered my media consumption pattern - in a big way. I regularly listen to 20+ podcasts, which seams kinda nuts. But, it’s really an efficient way of keeping up with the news. Also, I moderate the number of podcasts to the number of hours I have walking throughout the week. I don’t like having podcasts sit in my queue for more than a few days, and I don’t like running out of podcasts, so I’ve reached an equilibrium with the ones I’m subscribed to. (You do the math on what that means as far as how much I walk each week…)