Create an account and secure it

Head to https://www.digitalocean.com/ and create an account. You have to provide a credit card, but you won’t be charged anything, and you’ll get $100 credit.

Once you are all logged in to Digital Ocean, go to Account > Security > SSH keys. Create a new key and paste your key info (from the last step) into the box. Give it a meaningful name that describes the user and computer it applies to (i.e., Henry_MacBookProKey).

Add a port for RStudio

Go to Manage > Networking > Firewalls > Create Firewall Add a new rule for TCP and change the Port Range to 8787.

You are now ready to safely create your computer!

Access your droplet from your local computer

From Mac Terminal or other command line, log into your Digital Ocean computer:

ssh root@<the.ip.address.that.digital.ocean.gave.you>

You’ll need to say you trust the new connection and enter your SSH password from step 1.

Next, install a bunch of missing stuff:

apt-get update

sudo apt-get install curl build-essential libcurl4-gnutls-dev libxml2-dev libssl-dev libgdal-dev libproj-dev xorg libx11-dev libglu1-mesa-dev r-cran-rgl

Docker will allow you to install pre-made computer images for a variety of topics. Here we will install RStudio and the tidyverse packages. If you just want vanilla RStudio (without tidyverse), change “tidyverse” into “rstudio” throughout.

snap install docker

docker pull rocker/tidyverse:latest

Replace your_password with a real password of your own choosing

sudo docker run -d -p 8787:8787 -e PASSWORD=your_password --name rstudio rocker/tidyverse

Start RStudio

docker start rstudio

RStudio is now running, but invisibly. To see it, go to: http://the.ip.address.that.digital.ocean.gave.you:8787 and login: username: rstudio password: whatever you used in the last step to replace your_password.

Set your Global Preferences, Themes, Pane Layouts, etc.

I like the Merbivore or Dracula themes.

For Pane Layout, I love this layout (and so do most folks who see it):

Source   |   Console
------------------------
History  |   Everything else

Install packages you use often

Here’s my list:

install.packages(c("here", 
                  "ggthemes",
                  "scales",
                  "ggmap",
                  "plotly",
                  "forecast",
                  "treemapify",
                  "dbscan",
                  "rmarkdown",
                  "flexdashboard",
                  "maptools",
                  "treemap", 
                  "ggtern"))

Create a New Project (File > New Project > New Directory > New Project)

Set up the folder structure how you like it. Here is how I usually set mine up:

MyProject/
├── docs/
├── data/
      ├── raw
      ├── processed
├── cleaning/
├── analysis/
├── output/
├── drafts/

• docs is where I keep info about the experiment, a data dictionary, etc;
• data holds the raw data (if it isn’t on the web or a server);
• cleaning contains R scripts that take raw data and generate processed data;
• analysis contains R scripts that take processed data and do something with it;
• output is where figures and completed documents go. If I ever truly get to where my entire document is in RMarkdown, I’ll probably end there.
  
• But I’m still pretty Word-centric, so I still have a drafts folder where Word documents live.

If you organize your Projects like this, then you may be interested in the here package. It helps make your projects as portable to other systems as possible. For example, you could say write_xlsx(mydata, here("output", "myfile.xlsx")) and you don’t need to know where output is. It is just ‘here’, in your current project, no matter what drive or system it is on. In this case, here(“output”) means MyProject/output. here("data", "raw") is a link to my raw data folder.