R
is a powerful analytical language and contains a
number of useful packages for analyzing data.
RStudio
is a free and open-source integrated development
environment (IDE) for R. RStudio
provides comprehensive
facilities to R
programmers and is highly recommended in
this class.
R
We recommend installing the most recent version or R
(4.4.0 (called ‘Puppy Cup’) as of 2024-04-24). If you have had
installed R
already some time ago, we recommend
updating/reinstalling it to the most recent version. Use a link
below to launch download of R
installers (if the download
does not start, a fix may be to copy-paste the below link to your
browser):
For other operating systems, or if you prefer to access the download
link from the official website, visit https://cran.r-project.org/ and select
Download R for Linux
, Download R for macOS
or
Download R for Windows
based on which device you have.
Once the proper installation package has been selected, run the
package and follow the on-screen directions. This installation includes
the R
language and a graphical user interface (GUI). Rather
using the GUI, we recommend installing RStudio
- an
integrated development environment (IDE) that lets you interact with
R
with some added benefits.
RStudio
To install RStudio
, visit https://posit.co/download/rstudio-desktop/. The website
should look something like this:
Once on the website, scroll down and select the proper installation file for your platform (Windows, Mac, etc.). Open up the installer and follow the directions to install RStudio.
Note that your operating system may be too old to install the current version of RStudio. If this is the case try installing progressively older versions found here until it works. You will know if it worked if you try to open RStudio and you see an interface without a message about things going poorly.
When you open up RStudio
, it should look like this:
Click the top left button to create a new script:
RStudio
, should now look like this:
There are four main windows.
The console is the lower-left window where you can run lines of code and see the output.
The script window is the upper-left window where you can edit and write scripts or markdown documents. From the script window, you can run the current line of code in your script (or multiple lines if you highlight multiple rows) by pressing
CMD
+ Return
on MacCTRL
+ Enter
on WindowsThe workspace is the upper-right window where you can manage your data and variables and see previous commands entered (under the history tab).
The plots window allows you to see the output of
plots. On the other tabs, you can also look at directories, install
packages, and look at help files for various R
commands.
You can customize the look of your RStudio IDE in
Tools > Global Options...
.
If you run into trouble, check the following: - did you install the
correct version of software for your operating system? - Check that you
installed the version right for your type of system, (macOS
vs Windows
for example) - Check if maybe you need a
different version for the age of your system. First check that your
version of R was right - there are multiple versions for different
macOS
systems for example. You can check the apple icon
(top left corner) and “About This Mac” to learn more about the age of
your operating system. If your operating system is older (and you can’t
update it), try installing progressively older versions found here
until it works. You will know if it worked if you try to open RStudio
and you see an interface without a message about things going poorly.
Here you can see an example
of this. Unfortunately, the documentation is poor about what older
versions work for which operating systems.
R
packagesPackages are the fundamental units of reproducible R
code. They are collections of R
code that typically share
some common purpose. Examples:
dplyr
- package of functions for fast data set
manipulation (subsetting, summarizing, rearranging, and joining together
data sets);
ggplot2
- “R’s famous package for making beautiful
graphics”; allows to build multiple-layers, highly customizable
plots.
R
packageTo install an R
package, type in the
RStudio
console
install.packages("replace_with_package_name")
and press enter to execute the command.
Once a package is installed, to use its contents in current
R
session, we run in the RStudio
console the
command
library(replace_with_package_name)
(Note the difference in presence of the quotation mark in the two above commands.)
R
packageUse the above to install knitr
package. Execute the
library(...)
command to check if the package loads
successfully.
R
packages we will use in this
courseThis file contains a list of packages we will use for this course. You can install them one by one, or use the following code we prepared:
if (!requireNamespace("remotes", quietly = TRUE)) {
install.packages("remotes")
}
library(remotes)
install_github("jhur/jhur")