Programming Background
R v. Other Programming Languages
Coming into this course, I had previous programming experience with the following programs/softwares: R, SAS, and SQL. I am also learning Python at the same time as I am taking this course. Personally, R is my favorite of these languages that I am familiar with. One of the main reasons is that the RStudio interface is the best of any interface I’ve used. It displays a ton of helpful information, but in such a way that it is not overwhelming, and everything feels very well organized. Additionally, I like that there are a myriad of packages available, most of which are pretty easy to use. Finally, I think that the syntax of R is simple once you get used to it. Something I miss about SAS is that I found it to be easier to clean and manipulate data than in R. In particular, I found it easier to detect problems in the dataset or improper data points using SAS. Although as I become more experienced with tidyverse/dplyr, I think I’ll come to find that both languages will be about the same level of difficulty. I found R to be neither easy nor difficult to learn. Firstly, the syntax is relatively simple, which makes picking up the language easy to begin with. However, the availability of so many packages can be a double-edged sword. On the one hand, having so many packages at your disposal means there is most likely a way to easily do what you’re trying to do. On the other hand, it can be hard to sift through the different options and determine which is the best for what you need (i.e., do I use base R or ggplot for this graph?). As an aside, it was easier for me to motivate myself to learn R due to the wide variety of baseball datasets that can be easily implemented into R. As a big baseball fan it made experimenting with the language more fun and interesting.
R Markdown Output
# setup code chunk
knitr::opts_chunk$set(fig.path = "../images/")
plot(iris)
library(rmarkdown)
rmarkdown::render(input = "2022-06-08-Programming-Background.Rmd",
output_format = "github_document",
output_dir = "../_posts/",
output_options = list(html_preview = FALSE)
)