Meet the toolkit: programming

.title[
# Meet the toolkit: programming
]
.subtitle[
## STAT 4380
]
.author[
### Katie Fitzgerald, adpated from datasciencebox.org
]

---

layout: true
 
<div class="my-footer">

<a href="https://nova-stat-4380.netlify.app" target="_blank">nova-stat-4380.netlify.app</a>

</div>

---

## Course toolkit

.pull-left[
### .gray[Course operation]
.gray[
- nova-stat-4380.netlify.app
- Blackboard
]
]
.pull-right[
### .pink[Doing data science]
- .pink[Programming:]
  - .pink[R]
  - .pink[RStudio]
  - .pink[tidyverse]
  - .pink[Quarto]
]

---

## Learning goals

By the end of the course, you will be able to...

- gain insight from data

--
- gain insight from data, **reproducibly**

--
- gain insight from data, reproducibly **(with literate programming)**

--
- gain insight from data, reproducibly (with literate programming), **using modern programming tools and techniques**
---

# Reproducible data analysis

---

## Reproducibility checklist

Near-term goals:

- Are the tables and figures reproducible from the code and data?
- Does the code actually do what you think it does?
- In addition to what was done, is it clear *why* it was done?

Long-term goals:

- Can the code be used for other data?
- Can you extend the code to do other things?

---

## Toolkit for reproducibility

- Scriptability `$\rightarrow$` R

- Literate programming (code, narrative, output in one place) `$\rightarrow$` Quarto

- Sharability `$\rightarrow$` R Projects & GitHub

---

# R and RStudio

---

## R and RStudio

.pull-left[
<img src="img/r-logo.png" width="25%" style="display: block; margin: auto;" />
]
.pull-right[
<img src="img/rstudio-logo.png" width="50%" style="display: block; margin: auto;" />
]

- R is an open-source statistical **programming language**
- RStudio is a convenient interface for R called an **IDE** (integrated development environment), e.g. *"I write R code in the RStudio IDE"*
- At its simplest:*
 - R is like a car’s engine
 - RStudio is like a car’s dashboard

---

## R packages

- **Packages** are the fundamental units of reproducible R code. They include reusable R functions, the documentation that describes how to use them, and sample data1

- There are over 20,000 R packages available on **CRAN** (the Comprehensive R Archive Network)2

- We're going to work with a small (but important) subset of these!

2 [CRAN contributed packages](https://cran.r-project.org/web/packages/).
]

---

## Tour: R and RStudio

---

## A short list (for now) of R essentials

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

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

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

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

---

## R essentials (continued)

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

``` r
dataframe$var_name
```
]

- Object documentation can be accessed with `?`

``` r
?mean
```

---

## tidyverse

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

---

# Quarto

---

## Quarto

- **Quarto** and the various packages that support it enable R users to write their code and prose in reproducible computational documents
    + each time you render, the analysis is run from the beginning
- Quarto documents have a `.qmd` file extension
- Simple markdown syntax for text
- Code goes in chunks, defined by three backticks, narrative goes outside of chunks

---

## Tour: Quarto

---

## Environments

Remember this, and expect it to bite you a few times as you're learning to work 
with Quarto!

---

## Environments

``` r
x <- 2
x * 3
```
]

``` r
x * 3
```
]

---

## How will we use Quarto?

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

---

## What's with all the hexes?

.footnote[
Mitchell O'Hara-Wild, [useR! 2018 feature wall](https://www.mitchelloharawild.com/blog/user-2018-feature-wall/)
]

---

.your-turn[
.light-blue[.hand[Your turn: ]] ` AE 01 - UN Votes`
If you haven't already completed AE 01 - UN Votes,
- Go to our [Github repo ](https://github.com/kgfitzgerald/NOVA_STAT_4380/tree/main/assignment_templates) and navigate to AE > AE-01-unvotes.qmd
- Click to "Download raw file"
- Place the downloaded .qmd document in your STAT_4380 folder on your computer
- From inside your STAT_4380 RStudio Project, open and render the Quarto document `AE-01-unvotes.qmd`
- Complete the tasks in the "Try it out!" section
]