2] Cleaning Data: To remove a column ‘col’ in a dataframe ‘data’ using null, the command is:
data$col <- NULL
How to apply hash strings (a series of unreadable text) to replace important data e.g. full names. https://cran.r-project.org/web/packages/openssl/vignettes/crypto_hashing.html
3] For Loops:
The code I discussed
For (i in 1:10){
commands to be written here in a series of lines
}
4] Vectorisation: The explanation of apply (and related commands like ‘lapply’) I used is here https://www.guru99.com/r-apply-sapply-tapply.html
This week I discuss a new Moodle project and how I’ve been using R to process and visualise students use of educational materials.
Part 1] A New Problem
What is Moodle? Note that my University doesn’t use the latest version of Moodle.
Part 2] Acquiring data
How to download logs from Moodle
Part 3] General Points about R from the project
See ‘Scripts’ in this chapter
Part 4] Plot_ly
Examples of using Plotly with r, this free online text book teaches more about how to use Plotly
Shownotes R from Scratch Ep2
1] Variables – What is a variable?
2] Vectors – Vectors in R Tutorial
3] Projects (.RPROJ files) Using Projects in R
5] Code versus RStudio – Writing code in RStudio
6] Sankey Diagrams in R
Shownotes R from scratch ep1
I’m Richard Treves, @Trevesy on twitter
Part 2:
Other R podcasts mentioned: Credibly Curious, The R-Podcast
Part 3:
RStudio download, RStudio tutorials
Part 4:
Wikipedia on R statistical features, Free R textbook