Using Scoped dplyr verbs

Introduction Over the past several months, I have really started to increase the amount that I have been using scoped dplyr verbs. For those of you who don’t know about these functions, they are handy variants to the normal dplyr verbs, such as filter, mutate, and summarize, that allow you to target multiple columns or all of your columns. These functions allow for you to save yourself time and typing when you want to apply either one or multiple functions to more than one column, a group of columns, or to all of your columns.

Tracking Joey Wendle's rookie season with gganimate

Introduction This past weekend I got the chance to go to the Tampa Bay Rays vs Cleveland Indians game. This game was a ton of fun, made even more exciting for me - and by the end of the game, the people in my section - because my brother-in-law’s brother (does that make him my brother-in-law too? No one ever knows for sure…), Joey Wendle, plays for the Rays! In case you haven’t been paying attention, Joey has been having a MASSIVE rookie season.

Create a dynamic number of UI elements in Shiny with purrr

Introduction purrr is an incredibly powerful package that has greatly enhanced my R programming abilities. purrr has applications in pretty much any situation. One of the most useful situations, IMHO, is in the creation of a dynamic number of shiny UI elements. This can be extremely useful if you want to be able to create a dynamic number of ui elements (whether that be inputs or outputs) based on either user selection or the data being used.

PCA in a tidy(verse) framework

Introduction The other day, a question was posted on RStudio Community about performing Principal Component Analysis (PCA) in a tidyverse workflow. Conveniently, I had literally just worked through this process the day before and was able to post an answer. While most questions and answers are good as they are on forum sites, I thought this one might be worth exploring a little more since using the tidyverse framework makes PCA much easier, in my opinion.

Creating, Writing, Querying, and Modifying SQL Database from R using odbc, dbplyr, and DBI

Introduction Recently, I have been building shiny apps for work. The app that I am currently working on is an interface to a database for storing information about laboratory samples being collected. In addition to building the shiny app for my coworkers to interact with the database, I also was tasked with creating and building the database. I have never build a SQL database from scratch, but luckily the odbc and the DBI packages make it fairly straight foreward.

Exploring English Premier League Historical Match Results

Introduction I was listening to Jeff Atwood’s interview on the podcast Developer on Fire and he said something that struck home with me. It was along the lines of, “The best time to start blogging is yesterday.” I have been considering starting a blog about #rstats but had been putting it off because of any number of reasons. But after listening to his interview, I decided now was as good of a time as any.