We'll be working with R again. This time you practise visualising data, as seen in the previous lectures.
You can create documents and edit them directly in GitHub's web interface. This is a very convenient way of creating and editing the files. In most cases, as in this case, the preferred way of working is to edit the files on your own machine, in RStudio.
To get the files to your own computer, as discussed previously, use GitHub Desktop (which is now available in the Application Catalogue!).
If there are issues with GitHub Desktop on UCLan's network again the easiest workaround might be to copy and paste the R code between GitHub and RStudio, or even better: you work on your own machine where there shouldn't be any issues.
Once you are done be sure to commit your changes again (to save them to the repository) and to push them to GitHub (so that I can see the work you have done).
It's best if you Commit early, commit often - that way you can go back if you have made a mistake and I can see all the work you have done. It doesn't matter if your early commits contain mistakes.
Your tasks can be found in the R script file visualisation.R that is part of this repository. You have to work on these tasks by yourself. Do not work with others. These tasks will form part of assignment 1 part 2.
Working with other students might be interpreted as collusion on your part, see Assessment Handbook, 6.3.4 (p. 27)
Again, please work on these tasks in RStudio - not on the GitHub website. Pay attention to the autocomplete options RStudio is offering you and use them to explore how R commands work. Also, remember how useful the cursor keys and the Tab key can be. As shown previously, pressing F1 will bring up the documentation for the selected command in the Help tab.
Please don't forget to push your commit.