Read Chapter 1 to help you complete the questions in this exercise. We’ll also bounce occasionally to Chapter 2 for a few questions where links will be provided.
# at the beginning of
every line to let R know this is a comment. See Section 1.10 for a little
more detail.
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). See
Section 2.5 of the
Introduction to R book for more details on using the help functions.
The content displayed in the bottom right window is context
dependent. For example if we write the code plot(1:10) in
our script and then 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. Take a look at Section 2.2 of the
Introduction to R book for further information on how to do this or if
you prefer watch the Objects in
R video. 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. Use the code
rm(first_num) to do this. 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 (see Section 2.5.1 of the
Introduction to R book). Look through the list and once you have figured
what the correct function is then bring up the help file for this
function (Hint: the function name probably has the words ‘plot’ and
‘design’ in it!).
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’. Take a look at Section 2.5.1 for more
information. Also, 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 help.search()).
help.search("plot")
??plot # shortcut for help.search function
help.search("plot", package = "nlme")
R’s working directory is the default location of any files you read into R, or export from R. Although you won’t be importing or exporting files just yet (that’s tomorrows job) it’s useful to be able to determine what your current working directory is. So, read Section 1.7 of the Introduction to R book to introduce yourself to working directories and figure out how to display your current working directory.
Let’s finish up by creating some additional useful directories in
your Project directory. If you’ve followed the Data
instructions
when downloading datasets for this course you will already have a
directory called data in your Project (if you didn’t then
take a look at the instructions under Data
to create
this directory). Now let’s create another directory called
output where you’ll save data files and plots you generate
later on during this course. This time, instead of clicking on the ‘New
Folder’ icon in RStudio we’ll create a new directory using R code
directly in the R console (you can also interact with your computer’s
operating system in all sorts of useful ways). To do this use the
dir.create() function to create a directory called
output (See Section 1.8 of the
Introduction to R book for more details). If you fancy it, you can also
create a subdirectory in your output directory called
figures to store all your fancy R plots for your thesis.
You can list all the files in your directories using the
list.files() function. Can you figure out how to list the
directories as well? (hint: see ?listfiles or Section 1.8 of the course
book).
End of Exercise 1