A quick and short post on parallel distance calculation in R using the mclapply() function from the parallel package. I'll use data from the Biobase and datamicroarray packages to illustrate.
I recently completed Data Manipulation in R with dplyr and realised that dplyr can be used to aggregate and summarise data the same way that aggregate() does. I wrote a post on using the aggregate() function in R back in 2013 and in this post I'll contrast between dplyr and aggregate().
It has been a quiet year of blogging since my 5th anniversary; there has only been 13 posts since. Though as I have mentioned before, I am using GitHub to share tutorials and some of my work. However, I will try to write at least twice a month, especially now that I have decided to learn more about tidyr, dplyr, and ggplot2.
This is my third post on learning R through the BetaBit package, which contains three mini games for learning R. I wrote about the first game, called proton, late last year and the second game, called frequon, a week and a half ago. The third game is called regression and it's much more statistical than the other two. I actually couldn't complete the last task of the game, so if you know how to approach it, please let me know!
Late last year I discovered proton, an educational game in R about processing data frames, via R-bloggers and had a go at it. I thought it was fun and educational; it was also the first time I tried to use the dplyr package. I recently learned that there are two more games produced by the same developer of proton. This post is on the frequon game.
Just last night I found this educational mini game written in R and decided to have a go at it:
— Dave Tang (@davetang31) December 5, 2015
I completed it but as I alluded to in my tweet, not in a very elegant manner. This post is on using the dplyr package in R to solve some of the problems. If you want to give the game a go first, then stop reading now.
The R Graphics Cookbook is an awesome book; it's so awesome that I bought the ebook after I bought the hardcopy because one copy of it wasn't enough. I haven't read the book in its entirety yet, but I thought I'll share with you some of the recipes in Chapter 13, which illustrates how to create miscellaneous plots in R.