2.2 Best practise and variable naming conventions

Some quick best practice tips:

• Best practice suggests that you should not assign meaningless names to variables; give a variable a succinct but meaningful name that will be of value to understand which information you have saved.
  • df may be an obvious name for a data.frame, but phenotypeDf or phenotype.df may be more memorable later on in your analysis.
  • you can use camelCase (or camelNotation), underscore (_) or fullstop (.) for variable names in R.

• You can create thousands of variables in your R workspace but are they all necessary? It is worthwhile performing housekeeping on your data collection if you are creating many variables.

• If you have many variables in your R workspace then you may not be using the most ideal method to store your data. Consider data structures like data.frame and lists to better structure your data.

• RStudio allows you to remove all objects from your workspace by using the Clear button in the Environment tab as an alternative to the command: rm(list=ls()). (You can follow this with the gc() function for garbage collection to further ensure that memory has been freed up.)