Mostly a dumping ground for snippets wrt moving around in the environment and getting comfy. Probably a bit terse if you've not used RStudio before, but super handy if you're jogging your memory, like me!
||execute the currently selected code|
||list all objs defined in current wrkspace. Handy!!|
||load a library named 'pkg'. Note lack of quotes.|
||install package named 'pkg'.|
||install R lib from github project named 'p' from github user 'u'. Of course, this requires that the 'devtools' package be already installed.|
||remove object X from environment|
||remove all objects from the environment|
||nuke everything incl all hidden objs|
||See documentation for a library named 'pkg'|
||see the help file for a command named 'foo'|
||Just see what arguments a func named 'foo' takes. Useful!!|
||garbage collect unused memory|
||restart the whole damn R session :o)|
The following are equivalent; they both print out a variable named 'x':
There are also:
These print the first or last n entries of data held in a variable x.
There is also
str(x), which shows you the structure of the object (named 'x', for example). This is SUPER handy and is easily the most useful function when you are wading about knee-deep in complex data structures.
class(x) for the type of object. The function class prints the vector of names of classes an object inherits from. It can also be set, but we won't get into that here.
So this link is a beautiful thing. It describes how to set up config files for your R project! Relies on
config.yml files that can be set up for different environments and gives you a singular file to
You can specify which configuration is currently active by setting the RCONFIGACTIVE environment variable. The RCONFIGACTIVE variable is typically set within a site-wide Renviron or Rprofile (see R Startup for details on these files).
Simply brill, if you ask me.
Besides opening and running a file manually, you can 'source'an R file from any location and execute it inline:
# note: check getwd() first... cos this path is relative source("the/path/to/theFile.R") # how to set the working directory to that of the currently running file setwd(getSrcDirectory())
Hope this helps other people also tinkering with R. I plan to tinker with Python too... but I'm not super interested in python proper, so I might go straight to Jupyter notebooks and work my way down from there...