R Hex Bowtie

If you were at rstudio::conf you may have seen me walking around with my conference badge and wondered what everything is.

My time as an RStudio Intern

I’ve had a lot of time to think about my time as an RStudio intern. When I do, I usually end up with a few words in my head before I’m flooded with (good) emotions and struggle with finding the words to convey my thoughts. The last time I tried to write something like this went a little like this. What I can say is this: whatever you thought it was like working at RStudio, is (probably) true.

Table of Model Results using kable and kableExtra

I’m at the R/Medicine conference (no it’s not a Reddit thing) and got to help Alison Hill with her R Markdown for Medicine workshop. One of the questions I got to tinker with was making tables used to report model results. One technique I learned while doing my MPH was to add variables to your model in blocks. It reduces the number of tests you need to perform, and is more meaningful than saying “I ran stepwise”.

R or Python, which One to Learn (First)?

I’ve been asked a few times lately about whether one should learn R or Python. Channeling David Robinson’s post, I’m writing a blog post about it. When you’ve written the same code 3 times, write a function When you’ve given the same in-person advice 3 times, write a blog post — David Robinson (@drob) November 9, 2017 The only definitive answer I have is if you’re planning to do web deveopment, and you’re somehow only picking between R and Python, pick Python (any of the Python web frameworks, Flask, Django, Pyramid, and then ask yourself why not JavaScript?

Inconsistencies with the == operator in R

One of the cool things about working on gradethis (grader need to be renamed) is that we end up doing things that aren’t common in R (i.e., grading and comparing code). I discovered an inconsistency with the == operator when comparing (long) R expressions. A quick primer on expressions In R, you can create an expression using the quote() function. This is essentially the code that R will execute.

New Website a la Blogdown!

I finally got everything moved over to blogdown with the Hugo Academic theme. Thanks so much to Allison Hill, who ran the summer-of-blogdown tutorial for us RStudio interns. The transition was pretty seamless. Mainly because I didn’t really have that much content to move over. The biggest change was I had to commout my categories tag in my YAML post headers becuase they were causing the site to not build.

RStudio internship week 2

The main topics and events of last week were: Much git. Metaprogramming and non-standard evaluation (NSE) in R Four 1-hour workshops by Allison Hill on the summer-of-blogdown moving things over from jekyll will take some time So many of the random things I’ve tinkered with in the past have come front and center. As an educator, I know seeing these things again make learning and understanding them easier.

And we’re off! RStudio internship week 1, complete.

I’m still pinching myself about being one of the RStudio interns this year. It’s an unbelievable opportunity and I’ve been half panicked and fighting imposter syndrome since the announcement was made in March. My meeting with Greg Wilson on Friday (2019-06-07) went something like this: Greg Wilson: How’s the internship going? Me: I’m panicked, but really excited. Greg Wilson: Good. That’s how interns should feel. I’m working on the grader package (with Garrett Grolemund and Barret Schloerke) which aims to check code against a solution.

rstatsnyc as told by @brookLYNevery1, @dataandme, and autographs

EDIT: I’ve added the notes from @dataandme and linked to people’s twitter and slides (if I found them). This is probably going to be an ongoing process… Another year and another talk at the NYC R Conference. As always, the conference was filled with excellent speakers (I’m biased here becuase I was one of them…), food, and people. Brooke Watson ( @brookLYNevery1) did a fantastic job illustrating and summarzing all of the talks.

Getting Started with Data Science and Analysis

I’ve been an instructor for Software-Carpentry (SWC) over a year now. It’s been a facinating experience and I’m proud to be a part of an open source movement promoting best practices. Typically when looking to start learing data science/analysis the first things people look up is something along the lines of: “learn python”, “free online r course”, “data science python”, “r jobs”, etc. Or scan through the coursera offerings. I’m a bit biased, but I think the SWC material is one of the best ways to just get familiar with the basics.