Part 10 Lab 1: Getting started with RStudio, Git, and Markdown

In this lab you will do 4 things:

  1. Get acquainted with RStudio and customize it to your liking.
  2. Practice writing a document with Markdown.
  3. Practice using some basic functions in R.
  4. Make a GitHub repository to save and share your work.

10.1 Part 1: Set up R and RStudio

First, install two packages we will use a lot in class:

  1. tidyverse
  2. palmerpenguins

Next, customize some RStudio settings:

  1. Click Tools → Global Options… 1. On the first page, under Workspace:
    • Uncheck Restore .RData into workspace at startup
    • Set Save workspace to .RData on exit to Never
      1. Under History:
    • Uncheck Always save history (even when not saving .RData)
      1. Click the Advanced button at the top. Under Other:
    • Check Show .Last.value in environment listing

Now, adjust the appearance of RStudio to your liking:

  1. In the Pane Layout window, you can rearrange RStudio’s 4 panes.
  2. In the Appearance window, you can change your font size, code typeface, and RStudio color scheme. - I use the Tomorrow Night Bright color scheme.
  3. In the Code window, you can change various ways about how code is inserted and shown. Change 3 settings from their defaults:
    • On the Editing page, under General, check Use native pipe operator |> (requires R 4.1+)
    • On the Editing page, under Execution ,set Ctrl/Cmd+Enter executes to Multiple consecutive R lines
    • On the Display page, check Rainbow parentheses
  4. In the RMarkdown window, you can change how RMarkdown is shown while you edit it. - Uncheck Show output inline for all RMarkdown documents.

Go ahead and customize your RStudio appearance (color theme, font, etc.) and pane layout to whatever you find appealing. You can always come back and change these later until you find a setup you like.

10.2 Part 2: Make a README.md file with Markdown

In RStudio, make a Markdown file from the File menu. Save this file with the name README.md. README should be in all caps. This file will be the introduction to your class GitHub repo. Use it to introduce yourself and practice your Markdown skills.

The beginning of the README should contain a very brief description as to what the repository is (a sentence or two), so that a visitor landing on the repository can orient themselves. You should also help the visitor navigate your repository (in whatever way you think is most appropriate).

Then, introduce yourself briefly.

When writing your README, be sure to showcase at least five functionalities of GitHub-flavored markdown. The markdown cheatsheet might help here, or, the Help menu in RStudio will bring up a Markdown Quick Reference at any time.

Here’s a sample README file that goes way above and beyond what I’m looking for (aside from describing the repo).

10.3 Part 3: Practice some R fucntions

In RStudio, make an R script file from the File menu. In this file, you will explore the palmerpenguins::penguins dataset.

Use some R functions to explore this data frame a bit. For example, what is the general structure of the dataset? How many rows does it have? How many colums? What are the descriptive statistics for some of the important variables?

You should: 1. Demonstrate the use of at least three functions. 2. Write code comments with # describing what the functions you are using do.

Save your R script with a useful name, such as lab01_exploring-penguins.R.

10.4 Part 4: Make a GitHub Repository for your work

On GitHub.com, make a new repository called “progdata-class”. As you make it, do the following:

  1. Give your repo a useful description.
  2. Make it Public.
  3. Check “Add a README file”
  4. Check “Add .gitignore” and select “R” from the dropdown.
  5. Clone your repo to the GitHub Desktop app.

If you are using a Mac anywhere, also do this: 6. In RStudio, open the .gitignore file. Add “.DS_Store” (no quotes) to the end of the file. Save the file and commit the change.

Now, add your files for this lab to your repo and commit them. Remember, commit early, commit often! Make small changes at a time. Write a useful commit message for each commit.

  1. Add your README.md file and commit it.
  2. Add your data exploration R script to a folder called “Lab 1” and commit it.
  3. Add any other scripts or files you made in class to the Lab 1 folder as well.
  4. Push your changes up to GitHub.

Finally, copy a link to your repo to the thread on the class Teams.