S04E08: R for Data Science - Chapters 4, 6, and 8

I – Brief Code Club Introduction

Organizers

• Michael Broe – Evolution, Ecology and Organismal Biology (EEOB)
• Jessica Cooperstone – Horticulture & Crop Science (HCS) / Food Science & Technology (FST)
• Stephen Opiyo – Molecular & Cellular Imaging Center (MCIC) - Columbus
• Jelmer Poelstra – Molecular & Cellular Imaging Center (MCIC) - Wooster
• Mike Sovic – Infectious Diseases Institute AMSL - Genomics Lab

Code Club practicalities

• In-person (Columbus & Wooster) and Zoom hybrid

• Mix of instruction/discussion with the entire group, and doing exercises in breakout groups of up to 4-5 people.

• When doing exercises in breakout groups, we encourage you:

  • To briefly introduce yourselves and to do the exercises as a group
  • On Zoom, to turn your cameras on and to have someone share their screen (use the Ask for help button in Zoom to get help from an organizer)
  • To let a less experienced person do the screen sharing and coding

• You can ask a question at any time, by speaking or typing in the Zoom chat.

• You can generally come early or stay late for troubleshooting but also for questions related to your research.

Some more notes:

• We recommend that you read the relevant (part of the) chapter before each session, especially if the material in the chapter is new to you.

• We try to make each session as stand-alone as possible. Still, if you missed one or more sessions, you would ideally catch up on reading those parts of the book, especially when we split a chapter across multiple sessions.

• We record the whole-group parts of the Zoom call, and share the recordings only with Code Club participants.

New to Code Club or R?

Take a look at these pages on our website:

• Computer setup for Code Club
• Resources and tips to get started with R
• List of all previous Code Club session topics

II – The R for Data Science book (R4DS)

This excellent book by Hadley Wickham (also author of many of the R packages used in the book!) and Garret Grolemund, has a freely available online version that is regularly updated and contains exercises. It was originally published in 2016.

The book focuses on the so-called "tidyverse" ecosystem in R. The tidyverse can be seen as a modern dialect of R. In previous Code Clubs, we have often –but not always!– been doing things “the tidyverse way” as well.

For today’s chapters, The R4DS exercises I think are not so good, so I’ve replaced some and added some of my own.

III – R4DS Chapter 4

In the first two R4DS exercises for this chapter, the message is that R does not handle typos so make sure you spell things correctly.

Exercise 3: take a look at the RStudio keyboard shortcuts by clicking Tools > Keyboard Shortcut Help, or you can press Alt + Shift + K on a PC.

IV – R4DS Chapter 6

glimpse(cars)

library(tidyverse)

glimpse(cars)#> Rows: 50
#> Columns: 2
#> $ speed <dbl> 4, 4, 7, 7, 8, 9, 10, 10, 10, 11, 11, 12, 12, 12, 12, 13, 13, 13…
#> $ dist  <dbl> 2, 10, 4, 22, 16, 10, 18, 26, 34, 17, 28, 14, 20, 24, 28, 26, 34…

#> Error in library(tidyverse) : there is no package called ‘tidyverse’

install.packages("tidyverse")
library(tidyverse)

IV – R4DS Chapter 8

library(tidyverse)

ggplot(diamonds, aes(carat, price)) + 
  geom_hex()

ggsave("diamonds.pdf")

write_csv(diamonds, "diamonds.csv")