An Analysis of BoardGameGeek Data — Introduction Sophisticated “Euro” boardgames are a big hobby these days, and a far cry from old Uno and Monopoly. Often more like economic simulations, these modern board games demand parsing many complex choices, and efficiently using resources, usually to amass “victory points” before the end. But Euros aren’t static: they’ve changed…

Misconceptions About Working In Data — Data work is a stable, respectable professional field, with pretty decent pay in exchange for staring at a glowing box much of each day. But before you dive in, be realistic about what it isn’t. Things you might think, and the reality… “I’ll do a bootcamp and some Kaggle competitions, and then I’ll be a data scientist!” No one will hire you. Those two-week training…

I actually haven’t interviewed that many times. I feel like half the time I get the job, and the other half of the time it’s a horrendous situation I’ve been lucky to dodge. Well, this post is about that second half. The things interviewers say… 1. Loyal employees never leave. I drove to the nearest…

Go Beyond Coding To Be Useful And Employed — People obsess over what bootcamps to join, the hottest ML algorithms, and which SaaS products to use. But the technicalities of data science/analysis are just one piece of the work. I would list at least these six skills: Back-End Coding. This is handling the pipelines of data, i.e. the data…

Nice write-up of this position, Erik. I'm of the same persuasion. I've seen the same thing in the R world, between different dialects. I even wrote a piece comparing one approach (the “tidyverse”) to a kitchen full of gadgets — v. using a chef knife (data.table). I also saw something similar when I worked in graphic design. There were tool people, who loved add-ons for Photoshop that would save them 10 seconds each, but cost them 2 hours to update and implement in total; versus the people who would just wing it with the tools included, and not worry.

Are dashboards dead? Kind of. Which I think makes them undead. No, they're not dead: because people keep asking for them, and other people keep making them. Yes, they're dead, because they rarely get used: most dashbaords are requested, made, published, and then never accessed again. Users love the idea of dashboards: that they'll have control, and can get all kinds of insights. But most data are too complex to understand without analysis -- more than you cna do in an interactive dash. So to answer any serious question, you're back to ad-hoc reporting. Which is fine. Dashboards have their uses -- it's just far fewer uses than we sometimes imagine.

A Generic Class System for Fantasy Games — Flexibility with constraints. That’s what I find fun and to generate the most creative ideas. So I’ve created a generic system for fantasy classes. (Just remember, half the fun of old D&D games was making your character!) Each character has three slots to use, assigning each a class archetype from…

A First Lesson in R Commands For the Non-Programmer — If you haven’t done a lot of programming, learning R can be pretty intimidating. But it’s easier if you focus on fundamentals, and slowly build up your skills through practice. Here I’ll give a short lesson on the most basic things you can do in R. This post is adapted…

So Students Can Face Real-World Data Problems — Last year I started teaching a six-week R programming course at a university, and I have another available online on Udemy, So You Need to Learn R. I thought long and hard about how to teach R. Here’s what I came up with. Beginners I wanted a course that beginners could…