In this tutorial we are going to cover setting up each lab. This involves making projects, packages and R Markdown documents.
In this class, we will be using R-Projects:
This is incredibly useful - it means that if you switch from R-Cloud, to the lab computers, to your laptop, all you have to do is to move the folder and everything will just work. Equally, its easy to compare labs.
Learn more here.
We will cover how to make projects for R studio cloud and desktop in the set up below.
Everything should now be installed. If not, go back to Tutorial 2.
IMPORTANT! If you haven’t already, on an easy to access place on
your computer, make a folder called GEOG364. This is where ALL your labs
are going to live.
Now everything is installed, open R-studio (NOT R!).
Steps 3-7 are shown graphically in the figure below.
New Project New Directory, then
New ProjectCreate Project
R will change slightly. If you look at the top of the screen in the title bar, it should say something like GEOG364-Lab1-PROJECT - R Studio.
The Files tab should have gone to your project folder. Essentially, R-Studio is now “looking” inside your Lab 1 folder, making it easier to find your data and output your results.
How to check you are in a project
If you want one, final check, try typing this into the console (INCLUDING THE EMPTY PARANTHESES/BRACKETS), press enter and see if it prints out the location of Lab 1 on your computer. If not, talk to an instructor.
OK, let’s imagine that you get halfway through your lab and your computer dies. How do you get back to your Lab work? Try this now. Close down R-Studio.
To reopen a lab:
DO NOT RE-OPEN R-STUDIO!
Instead navigate on your computer to your GEOG364/GEOG364-Lab1-PROJECT folder.
Double click on the GEOG364-Lab1-PROJECT.RProj file.
This will reopen R for that specific lab, so you can continue where you left off. It means you can also open several versions of R studio for multiple labs, which can be very useful in staying sane
Go to this webpage. https://login.posit.cloud/login You can get here from any web-browser, You do not need a special computer.
When you log in, you should see a dashboard like this.
The Cloud dashboard
YOU SHOULD MAKE A NEW PROJECT FOR EACH LAB.
You make a new project by clicking the button on the top right. You can open different projects in different tabs on your browser. You can also go back to the work-space at any time.
On the cloud this is very easy, just go back to https://posit.cloud/content/yours
Let’s say you want to switch to the desktop but save your progress. Or you want to submit your work to Canvas!
To switch to desktop, download/install the desktop version using the tutorials here. Then make a new project using the instructions above.
Either way:
On the R-Studio Cloud website; inside your project, go to the files tab (next to Projects/Help in one quadrant. You will see a list of files, one with the file type .Rmd (your code) and one with .html(the website you made when you pressed knit). Look at the red circle in the pic below
Click the check-box to the left of the .RmD file
Look just above at the Files quadrant settings menu. Click the blue “more” cogwheel icon. (see diagram). You might need to make R-Studio full screen to see it, it cuts off if the window is too small.
Now click Export This will download the file
REPEAT FOR THE HTML (you can do them together but it exports as a zip)
Submit both files on Canvas or put them in your project file.
Downloading the files
Sometimes you want to put your code into R-Studio Cloud, for example if for one week you don’t want to bring your laptop.
Make a project for the lab on the cloud as above, then click the
upload button inside your project in the files tab and
upload your files. You will only need the .RmD file and any data
files.
This is zoomed in to your files quadrant
You will be greeted by three panels:
If you wish to learn more about what these windows do, have a look at this resource, from the Pirates Guide to R: https://bookdown.org/ndphillips/YaRrr/the-four-rstudio-windows.html.
If you have used R before, you might see that there are variables and
plots etc already loaded. It is always good to clear these before you
start a new analysis. To do this, click the little broom symbol in your
environment tab.
Some of the default R settings are worth changing to make life smoother. We do this in the main global options menu.
You only have to do this once! Follow the arrows in this figure (sections explained below).
There are two places you might find this menu:
On the main options screen (see figure above), I suggest:
UNCLICK “Restore most recently opened project at startup”
UNCLICK “Restore .RData into workspace on startup”
Set “Save workspace to .RData on” exit to Never
UNCLICK “Restore previously open source documents on startup”
Note, yours will probably show a different default working directory.
OPTIONAL: You can also click the appearances menu item to change how
the screen looks (see the figure above). For example, maybe you
concentrate better with a dark background or with pink font.
OPTIONAL: Like me, you might find you like the different quadrants in
a different order. To change this, look at the Panes layout menu item
(you can also get here via the View menu,then
/Panes/Pane Layout) I tend to like the console to be top
left and scripts to be top right, with the plots and environment on the
bottom - but this is personal choice.
As described earlier, we program in R by typing a series of commands. R is open source and anyone can create a new command. Over the last 20 years,tens of millions of new custom commands have been created.
Commands tend to be grouped together into collections called
Packages or Libraries (two names for the same
thing). For example, one package contains the complete works of
Shakespeare; another allows interactive website design; another allows
advanced Bayesian statistics. There is a package for literally
everything and there are now over 20,000 packages available. You can see
a selection here: https://cran.r-project.org/web/packages/available_packages_by_name.html
A close analogy is your phone: There are millions of
apps available from banking, to 50 different calendar apps. You don’t
have every app in the world installed on your phone - and you don’t have
every app you do download running at the same time. Instead you
download the apps that you think you will need (occasionally downloading
a new one on the fly) - and when you need to use an app, you click on it
to open.
This is exactly the same in R. To access the commands in a package we need these two steps:
This is like going to the app store to get a new app. Just like you only go to the app store once, this is a one-off for each package. NOTE! For R studio cloud online, you might have to do this for each project.
You can also use a command to install a new package:
DO NOT INCLUDE ANY INSTALL.PACKAGES COMMANDS IN YOUR FINAL
SCRIPT. ALWAYS TYPE/RUN THIS COMMAND IN THE CONSOLE WINDOW. The
command means “go to the app store” and download a package. You don’t
want to do this when pressing knit.
Please install the rmdformats package onto your computer/the cloud. You will need this in the nest step.
Sometimes R will ask you if you want to install binaries or other
things. IT WILL ASK YOU THIS QUESTION THROUGH “SPEAKING” IN THE CONSOLE.
It expects you to type yes or no, and to press enter to continue. Try
yes, if it doesn’t work (esp xfun), try no.
Sometimes R-Studio might want to restart when downloading packages
and occasionally gets confused. If it keeps asking, press cancel, close
R-studio, reopen and try again. If it really doesn’t want to work, open
the R program itself and run in the console there (or talk to Dr G)
Just as going to the app store doesn’t check your credit-card balance or make an Instagram post, simply downloading a package from the app-store doesn’t make the commands immediately available. For that you need to load it (just as you click on a phone app to open it).
I will tell you which packages you need for each lab, but if R tells you it wants a package, then install it AND load it.
This can be done with the library() command.
For example, this command loads the full works of Shakespeare from the the bardr package. (https://www.rdocumentation.org/packages/bardr/versions/0.0.9). If you want to try this, you might need to first install bardr using the instructions above.
ADVANCED: Sometimes several packages name a command the same word and you want to specify which package you want to use.
You can do this using the :: symbol. For example, this command forces the computer to use the ‘dplyr package’ version of filter.
If you have managed to load a package successfully, often nothing happens - this is great! It means it loaded the package without errors.
Hard to tell. So I suggest running the library command TWICE! This is because many packages will print “friendly messages” or “welcome text” the first time you load them.
For example, this is what shows up when you install the tidyverse package. The welcome text is indicating the sub-packages that tidyverse downloaded and also that some commands now have a different meaning.
Tidyverse install messages
To find out if what you are seeing is a friendly message or an error, run the command again. If you run it a second time and and nothing happens, then you’re fine.
This will be your lab report. Remind yourself of what Rmarkdown is using Tutorial 1, here https://rmarkdown.rstudio.com, or via this short video
In the past, you used to have to know a lot of computer commands to get markdown documents to work. Every month it seems to get easier, and there are now a load of professional templates available.
The ones we are going to use are from the package
rmdformats. Have a look at the templates here: https://juba.github.io/rmdformats/. If none of these
appeal, google RMarkdown templates for more.
Install the package rmdformats using the packages
tutorial above.
Go to the File menu on the top left, then click New File - R-Markdown. If this is your first time ever, it might ask to download some packages to be able to do this. Say yes. Eventually a window will open up:
Click “From Template” and select a template of your choice. Click here to see what different templates look like:
https://juba.github.io/rmdformats/
If you don’t see any templates, you needed to have installed the rmdformats package (see above). There are many packages containing different templates. You can see which package each template belongs to below (red). You should also be running your project - so it should auto save your file to your lab 1 folder.
It will ask you to name your file. Give it a relevant name including your email ID, like Lab-2_hlg5155. Press OK.
A new file should appear on your screen.
Essentially, we have some space for text, some space for code, and a space at the top of the file where we can add information about themes/styles etc called “YAML”.
Each grey code area is called a “code chunk”. To run the code inside it, click the little green arrow on the top right.
Depending on the template, your file might contain some friendly text to explain what is going on. Read through it, then you are welcome to delete it from the after the lower — onwards.
It is MUCH easier to edit markdown documents in the new visual mode. Essentially instead of having to remember text short cuts like * for bold, you can edit the text part as though you were using a word processor. NOTE HEADERS where it says “Normal”, this allows you to make auto tables of contents.
Code chunks are mini consoles where you can run R commands. We will talk more about them in the next tutorial.
On the top right there are a suite of buttons for adding a new code chunk, running code etc. The green one adds a new code chunk. To run an individual code chunk you will press the green arrow on its top right e.g.
The file on your screen isn’t the finished article. To see how it
will look as a final version, we need to “knit” it. Go to the top of the
.Rmd file, find the knit button. Press it (you might have
to first save your script if you haven’t already, then press it
again)
You should see that the Markdown tab “builds” your document and you get an output as a website. The html should also be saved into your project folder.
For example, from my other class, here is a file with markdown and knitted output.
