Module 7 Assignment: S3 V.S. S4

 



As shown here, an S3 value is both simple to set up and can be used by the generic function "list()" (said function can be used to interpret data of various types, thus the generic label).  It does, however, require that a class be added afterwards should the programmer require it.


As we see here, S4 requires a bit more work in order to make a similar list. Unlike what we did for S3, S4 demands that the class for the list be set up before doing anything else, essentially ensuring it's part of the created list. The variables in the list being assigned individual slots is another difference it has with the S3 version, essentially allowing multiple inputs to be filtered into the same variable slot. Aside from the extra verboseness of S4, it's similar to S3 in almost every other way.

GitHub for code: https://github.com/Retrolovania/R_Programming/blob/main/Module%207.R


Comments

Post a Comment

Popular posts from this blog

Module 6: Our First Graph

Image
 Rather than use base R syntax for making a chart, I opted instead to use ggplot2, as it provides more options and is something I'm much more comfortable with and understand better. This graph showcases the price trend of a certain video game over time since its release in 2007. Over time, the price per copy has fallen, and then steadily rose during the pandemic years. While Stephen Few argues for the notion that correlation does not equal causation, I believe the pandemic could certainly be theorized as a contributing factor for the sharp increase in price per copy.
Read more

LIS 4317 Final Project: R Chart showing Game Price changes over time

Image
 For this final project, I remembered the concept of used game prices tending to increase over time, especially older ones (more than 15 years old or so). With the lack on any decent visually-based references to measure the change in time these prices have had, I took it upon myself to make my own. Since no database I could find contained price listings, I obtained my own using PriceCharting.com. I selected a few random games released for the Nintendo GameCube, and recorded the price listing for "loose" games (only the disc). I then compiled all of the prices into an Excel CSV and imported it into RStudio. For clarification, the games I chose were (from left to right): Sonic Classics Collection Need For Speed: Most Wanted Shrek: Extra Large SpongeBob Squarepants: Battle For Bikini Bottom Lego Star Wars: The Video Game Super Monkey Ball TimeSplitters 2 Turok: Evolution Geist Batman: Dark Tomorrow Donkey Kong Jungle Beat I then made a ggplot function that would allow me to easi...
Read more

Final Project: DescribeR v1.0.0

 After some time, I'm thrilled to finally release the source code for my first ever R package. Alongside the first three functions I described in the original description file, I've also added an additional interactive_heatmap function that can create heatmaps of correlating numerical data in a given dataset. It's my hope that this package will make exploratory analysis easier for those dealing with unfamiliar sets of data, leaving more time to figure out more advanced uses for said data. GitHub repository for DescribeR: https://github.com/Retrolovania/DescribeR
Read more