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 Ep3 1] Packages HowTo install into RStudio  2] Dataframes Introduction to dataframes 3] Scripts in R Introduction to scripts in RStudio 4] If statements in R Introduction to If statements in R 5] Cleaning data in R Introduction to cleaning data in R 7] Shiny 

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