Meet the toolkit1 / 29

✉️ Accept your GitHub invitation

2 / 29

Agenda

Demo: A reproducible data analysis
R and RStudio
R Markdown
Git and GitHub
Recap

3 / 29

A reproducible data analysis

4 / 29

Let's talk about the Oscar nominations!

5 / 29

Recap: What did we just do?

Locate a repository on GitHub
Clone and open the project in RStudio
Run the analysis using R Markdown
Edit the analysis to exclude movie titles
Re-run the analysis using R Markdown

6 / 29

Toolkit

toolkit

Scriptability R
Literate programming (code, narrative, output in one place) R Markdown
Version control Git / GitHub

7 / 29

R and RStudio

8 / 29

What is R/RStudio?

R is a statistical programming language
RStudio is a convenient interface for R (an integreated development environment, IDE)
At its simplest:^➥
- R is like a car’s engine
- RStudio is like a car’s dashboard

➥ Source: Modern Dive

9 / 29

Let's take a tour - R / RStudio

Concepts introduced:

Console
Using R as a calculator
Environment
Loading and viewing a data frame
Accessing a variable in a data frame
R functions

10 / 29

R essentials

A short list (for now):

Functions are (most often) verbs, followed by what they will be applied to in parantheses:

do_this(to_this)
do_that(to_this, to_that, with_those)

11 / 29

R essentials

A short list (for now):

Functions are (most often) verbs, followed by what they will be applied to in parantheses:

do_this(to_this)
do_that(to_this, to_that, with_those)

Columns (variables) in data frames are accessed with $:

dataframe$var_name

11 / 29

R essentials

A short list (for now):

Functions are (most often) verbs, followed by what they will be applied to in parantheses:

do_this(to_this)
do_that(to_this, to_that, with_those)

Columns (variables) in data frames are accessed with $:

dataframe$var_name

Packages are installed with the install.packages function and loaded with the library function, once per session:

install.packages("package_name")
library(package_name)

11 / 29

tidyverse

tidyverse.org

The tidyverse is an opinionated collection of R packages designed for data analysis and data science.
All packages share an underlying philosophy and a common grammar.

12 / 29

tidymodels

tidyverse.org

tidymodels is an opinionated collection of R packages designed for modeling and statistical analysis.
All packages share an underlying philosophy and a common grammar.

13 / 29

R Markdown

14 / 29

R Markdown

Fully reproducible reports -- each time you knit the analysis is run from the beginning
Simple markdown syntax for text
Code goes in chunks, defined by three backticks, narrative goes outside of chunks

15 / 29

Let's take a tour - R Markdown

Concepts introduced:

Knitting documents
R Markdown and (some) R syntax

16 / 29

R Markdown help

R Markdown cheat sheet

Markdown Quick Reference
Help -> Markdown Quick Reference

17 / 29

Workspaces

Remember this, and expect it to bite you a few times as you're learning to work with R Markdown: The workspace of your R Markdown document is separate from the Console!

If I run the following in the console

x <- 2
x * 3

18 / 29

Workspaces

Remember this, and expect it to bite you a few times as you're learning to work with R Markdown: The workspace of your R Markdown document is separate from the Console!

If I run the following in the console

x <- 2
x * 3

All looks good, eh?

18 / 29

Workspaces

Remember this, and expect it to bite you a few times as you're learning to work with R Markdown: The workspace of your R Markdown document is separate from the Console!

If I run the following in the console

x <- 2
x * 3

All looks good, eh?

Then, if I add the following chunk in my R Markdown document

x * 3

18 / 29

Workspaces

Remember this, and expect it to bite you a few times as you're learning to work with R Markdown: The workspace of your R Markdown document is separate from the Console!

If I run the following in the console

x <- 2
x * 3

All looks good, eh?

Then, if I add the following chunk in my R Markdown document

x * 3

What happens? Why the error?

18 / 29

How will we use R Markdown?

Every assignment / report / project / etc. is an R Markdown document
You'll always have a template R Markdown document to start with
The amount of scaffolding in the template will decrease over the semester

19 / 29

Git and GitHub

20 / 29

How do we collaborate?

The statistical programming language we'll use is R
The software we use to interface with R is RStudio
But how do I get you the course materials that you can build on for your assignments?
- Hint: I'm not going to email you documents, that would be a mess!

21 / 29

Version control

We introduced GitHub as a platform for collaboration
But it's much more than that...
It's actually desiged for version control

22 / 29

Versioning

Lego versions

23 / 29

Versioning

with human readable messages

Lego versions with commit messages

24 / 29

Why do we need version control?

PhD Comics

25 / 29

Git and GitHub tips

Git is a version control system -- like “Track Changes” features from Microsoft Word on steroids. GitHub is the home for your Git-based projects on the internet -- like DropBox but much, much better).

26 / 29

Git and GitHub tips

Git is a version control system -- like “Track Changes” features from Microsoft Word on steroids. GitHub is the home for your Git-based projects on the internet -- like DropBox but much, much better).
There are millions of git commands -- ok, that's an exaggeration, but there are a lot of them -- and very few people know them all. 99% of the time you will use git to add, commit, push, and pull.

26 / 29

Git and GitHub tips

Git is a version control system -- like “Track Changes” features from Microsoft Word on steroids. GitHub is the home for your Git-based projects on the internet -- like DropBox but much, much better).
There are millions of git commands -- ok, that's an exaggeration, but there are a lot of them -- and very few people know them all. 99% of the time you will use git to add, commit, push, and pull.
We will be doing Git things and interfacing with GitHub through RStudio, but if you google for help you might come accross methods for doing these things in the command line -- skip that and move on to the next resource unless you feel comfortable trying it out.

26 / 29

Git and GitHub tips

Git is a version control system -- like “Track Changes” features from Microsoft Word on steroids. GitHub is the home for your Git-based projects on the internet -- like DropBox but much, much better).
There are millions of git commands -- ok, that's an exaggeration, but there are a lot of them -- and very few people know them all. 99% of the time you will use git to add, commit, push, and pull.
We will be doing Git things and interfacing with GitHub through RStudio, but if you google for help you might come accross methods for doing these things in the command line -- skip that and move on to the next resource unless you feel comfortable trying it out.
There is a great resource for working with git and R: happygitwithr.com. Some of the content in there is beyond the scope of this course, but it's a good place to look for help.

26 / 29

Let's take a tour -- Git / GitHub

Concepts introduced:

Connect an R project to Github repository
Working with a local and remote repository
Committing, Pushing and Pulling

There is just a bit more of GitHub that we'll use in this class, but for today this is enough.

27 / 29

Recap

28 / 29

Recap

Can you answer these questions?

What is reproducible data analysis, and why do we care?
What is version control, and why do we care?
What is R vs RStudio?
What is git vs GitHub (and do I need to care)?

29 / 29

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