Now to practice writing code in the script editor and sourcing this code into the R console. Let’s display the help file for the function
mean. In your script type
help('mean') and source this code into the console. Notice that the help file is displayed in the bottom right window (if not then click on the ‘Help’ tab). Examine the different components of the help file (especially the examples section at the end of the help file).
The content displayed in the bottom right window is context dependent. For example if we write the code
plot(1:10) and source it into the R console the bottom right window will display this plot (don’t worry about understanding the R code right now, hopefully this will become clear later on in the course!).
Next, let’s practice creating a variable and assigning a value to this variable. Create a variable called
first_num and assign it the value
42. Click on the ‘Environment’ tab in the top right window to display the variable and value. Now create another variable called
first_char and assign it a value
"my first character". Notice this variable is now also displayed in the ‘Environment’ along with it’s value and class (
chr - short for character class).
Remove the variable
first_num from your environment using the
rm() function. Check out the ‘Environment’ tab to ensure the variable has been removed. Alternatively, use the
ls() function to list all objects in your environment.
Let’s see what happens if we assign another value to an existing variable. Assign the value
"my second character" to the variable
first_char you created in Q6. Notice the value has changed in the ‘Environment’. To display the value of
first.char enter the name of the variable in the console. Don’t to forget to save your R script periodically!
OK, let’s leave RStudio for a minute. Using your favourite web browser, navigate to the R-project website and explore links that catch your eye. Make sure you find the R manuals page and the user contributed documents section. Download any manuals that you think you might find useful (some are listed in the course manual) and save them on your computer (or USB drive).
OK, back to RStudio. Sometimes you may forget the exact name of a function you want to use so it would be useful to be able to search through all the function names. For example, you want to create a design plot but can only remember that the name of the function has the word ‘plot’ in it. Use the
apropos() function to list all the functions with the word plot in their name. Look through the list and once you have figured what the correct function is then bring up the help file for this function.
Another strategy would be to use the
help.search() function to search through R’s help files. Search the R help system for instances of the character string ‘plot’. See if you can figure out how to narrow your search by only searching for ‘plot’ in the
nlme package (hint: see the help page for
R’s working directory is the default location of any files you read into R, or save out of R. Although you won’t be reading in or exporting files just yet (that’s tomorrows job) it is useful to be able to determine what your current working directory is. So, figure out how to display your current working directory.
Let’s finish up by creating some useful directories in your Project directory. First use the
dir.create() function to create a directory called ‘data’. This is where you will save all the data files used throughout this course. Now create another directory called ‘output’ where you will save data files and plots you generate later on during the course. Use the
list.files() function to list the files in your directory. Can you figure out how to list the directories as well? (hint: see
?listfiles or Chapter 1.8 of the course book).
End of Exercise 1