R Markdown: An Incomplete History

name: title
class: top hide-count center
layout: true

.talk-title[
# R Markdown
]

<div class="talk-band left">
<div class="talk-author f-zilla">Garrick Aden-Buie</div>
<div class="talk-twitter code">&commat;grrrck</div>
</div>
<div class="talk-band right">
<div class="code">Toronto Data Workshop</div>
<div class="code">2021-02-11</div>
</div>

---

## .pink.f-pompiere.absolute.w-100.left-0.animated.bounceInUp[R's Secret Ingredient]

---

## .pink.f-pompiere.absolute.w-100.left-0.animated.bounceOutUp.faster[R's Secret Ingredient]

## .pink.f-pompiere.absolute.w-100.left-0.animated.bounceInUp[R's Special Sauce]

---

## .pink.f-pompiere.absolute.w-100.left-0.animated.bounceOutUp.faster[R's Special Sauce]

## .pink.f-pompiere.absolute.w-100.left-0.animated.bounceInUp[An Incomplete History]

---

## .pink.f-pompiere.absolute.w-100.left-0.animated.bounceOutUp.faster[An Incomplete History]

## .pink.f-pompiere.absolute.w-100.left-0.animated.bounceInUp[Stuff I'm Working On and Want To Show Off]

---
layout: false

# About Me

.f2[
&#x1F44B; Hi, I'm **Garrick Aden-Buie**
]

.f2[
&#x1F426; [&commat;grrrck](https://twitter.com/grrrck)
]

.f2[
&#x1F9D1;&#x200D;&#x1F4BB; [garrickadenbuie.com](https://garrickadenbuie.com)
]

.f2[
&#xAE;&#xFE0F; [RStudio](https://rstudio.com): [.code[gradethis]](https://github.com/rstudio-education/gradethis), [.code[learnr]](https://github.com/rstudio/learnr)
]

---
background-image: url('https://source.unsplash.com/2LJ4rqK2qfU')
background-size: cover
background-position: center center
background-repeat: no-repeat
layout: false
class: right top

# What is R Markdown?

(wrong answers only)

.can-edit.f-pen.f2[
one
two
]

---
class: pv0 ph3 middle

<div class="f1 lh-title f-zilla">
.b[Break Free From Plastic] engaged 14,734 volunteers in
55 countries to conduct 575 brand audits.
These volunteers collected 346,494 pieces of plastic waste.
</div>

---
class: pv0 ph3 middle

<div class="f1 lh-title f-zilla">
.b[Break Free From Plastic] engaged .hl[14,734] volunteers in
.hl[55] countries to conduct .hl[575] brand audits.
These volunteers collected .hl[346,494] pieces of plastic waste.
</div>

---
class: bg-gray middle hide-count

.f1.f-zilla.white[
A brief history of<br/>
.code.f2[rmarkdown]
]

---
class: fullscreen hide-count

---
class: fullscreen hide-count

---
class: bg-gray middle hide-count

.f1.f-zilla.white[
A brief history of<br/>
_literate programming_
]

---
layout: true

<img src="assets/img/knuth.jpg" class="absolute bottom-0 right-1 knuth" height=300>
.side-foot-note[Donald Knuth]

.footnote[[Literate Programming](https://www.cs.tufts.edu/~nr/cs257/archive/literate-programming/01-knuth-lp.pdf)]

---

.f-typewriter.f3.lh-title[
Let  us  change  our  traditional  attitude
to  the  construction  of  programs:

__Instead  of__  imagining  that  our main task
is to __instruct a computer what to do__,
let us concentrate rather on
__explaining to human beings__
what we want a computer to do.
]

---

.f-typewriter.f3.lh-title[
I  was coerced like everybody else into
adopting the ideas of structured programming,
because I couldn’t bear to be found guilty of
writing **unstructured programs**.

Now I have a chance to get even ...
surely nobody wants to admit
writing an **illiterate program**.
]

---

.f-typewriter.f3.lh-title[
This language and its associated programs
have come to be known as **the WEB system**.

I  chose  the  name **WEB** partly because
it  was  one  of the  few three-letter
words of English that  hadn’t
already been applied to computers.
]

---
class: middle faded-knuth

.footnote[[Literate Programming](https://www.cs.tufts.edu/~nr/cs257/archive/literate-programming/01-knuth-lp.pdf)]

???

A WEB user writes a program that serves as the source language  for  two  different  system  routines.   (See  Figure  1.)   One  line  of  processing  is  called weaving the web;  it  produces  a  document  that  describes  the  program clearly and that facilitates program maintenance. The other line of processing is called tangling the web; it  produces  a  machine-executable  program.   The  program and its documentation are both generated from the same source, so they are consistent with each other.

---
class: faded-knuth

.f-typewriter.f3[
The result of the program will be to produce a list of the first thousand prime numbers...
]

.f-typewriter.f4[
〈Program to print the first thousand prime numbers 2〉≡
.b[program] .i[print_primes] (.i[output]);
&nbsp;&nbsp;.b[const] *m* = 1000;
&nbsp;&nbsp;〈Other constants of the program 5〉
&nbsp;&nbsp;.b[var]〈Variables of the program 4〉
&nbsp;&nbsp;&nbsp;&nbsp;.b[begin]〈Print the first *m* prime numbers 3〉;
&nbsp;&nbsp;&nbsp;&nbsp;.b[end].
]

---
class: faded-knuth

.f-typewriter.f3[
We shall proceed to fill out the rest of the program by making whatever decisions seem easiest at each step.

So let's come up with a list of prime numbers.
]

.f-typewriter.f4[
〈Print the first .i[m] prime numbers 3〉≡
&nbsp;&nbsp;〈Fill table .i[p] with the first .i[m] prime numbers 11〉
&nbsp;&nbsp;〈Print table .i[p] 8〉
]

---
class: faded-knuth

.f-typewriter.f3[
Now that the appropriate auxiliary variables have been introduced,
the process of outputting table .i[p] almost writes itself.
]

.f-typewriter.f4[
〈Print table .i[p] 8〉≡
&nbsp;&nbsp;.b[begin] .i[page_number] <- 1; .i[page_offset] = 1;
&nbsp;&nbsp;.b[while] .i[page_offset] &leq; .i[m] .b[do]
&nbsp;&nbsp;&nbsp;&nbsp;.b[begin]〈Output a page of answers 9〉;
&nbsp;&nbsp;&nbsp;&nbsp;.i[page_number] <- .i[page_number] + 1;
&nbsp;&nbsp;&nbsp;&nbsp;.i[page_offset] <- .i[page_offset] + rr * cc;
&nbsp;&nbsp;&nbsp;&nbsp;.b[end];
&nbsp;&nbsp;.b[end];
]

---
layout: false

---
class: bg-gray middle hide-count

.f1.f-zilla.white[
A brief history of<br/>
_literate programming_<br/>
in R
]

---
layout: true
class: no-margins

# sweave

---
background-image: url(assets/img/rotary-phone.jpg)
background-size: cover
background-position: center center

---

```latex
\documentclass{article}

\usepackage{amsmath}
\usepackage{amscd}
\usepackage[utf8]{inputenc}

\begin{document}
\SweaveOpts{concordance=TRUE}

\title{An Sweave Demo}
\author{Charles J. Geyer}
\maketitle

% ....

```

---

.overflow-hidden.relative[
.animated.slideOutUp.absolute[
```latex
\documentclass{article}

\usepackage{amsmath}
\usepackage{amscd}
\usepackage[utf8]{inputenc}

\begin{document}
\SweaveOpts{concordance=TRUE}

\title{An Sweave Demo}
\author{Charles J. Geyer}
\maketitle

% ....

```
]

.animated.slideInUp[
```
This is a demo for using the \verb@Sweave@ command in R.  To
get started make a regular \LaTeX\ file (like this one) but
give it the suffix \verb@.Rnw@ instead of \verb@.tex@ and then
turn it into a \LaTeX\ file (\verb@foo.tex@) with the (unix) command
\begin{verbatim}
R CMD Sweave foo.Rnw
\end{verbatim}

Well, we can now include R in our document.  Here's a simple example
<<two>>=
2 + 2
@
```
]
]

---

.overflow-hidden.relative[
.animated.slideOutUp.absolute[
```
This is a demo for using the \verb@Sweave@ command in R.  To
get started make a regular \LaTeX\ file (like this one) but
give it the suffix \verb@.Rnw@ instead of \verb@.tex@ and then
turn it into a \LaTeX\ file (\verb@foo.tex@) with the (unix) command
\begin{verbatim}
R CMD Sweave foo.Rnw
\end{verbatim}

Well, we can now include R in our document.  Here's a simple example
<<two>>=
2 + 2
@
```
]

.animated.slideInUp[
```latex
Figure~\ref{fig:one} (p.~\pageref{fig:one})
is produced by the following code
<<label=fig1plot,include=FALSE>>=
plot(x, y)
abline(out1)
@
\begin{figure}
\begin{center}
<<label=fig1,fig=TRUE,echo=FALSE>>=
<<fig1plot>>
@
\end{center}
\caption{Scatter Plot with Regression Line}
\label{fig:one}
\end{figure}
Note that \verb@x@, \verb@y@, and \verb@out1@ are remembered from
the preceding code chunk.  We don't have to regenerate them.
All code chunks are part of one R ``session''.
```
]
]

---

```latex
Figure~\ref{fig:one} (p.~\pageref{fig:one})
is produced by the following code
*<<label=fig1plot,include=FALSE>>=
*plot(x, y)
*abline(out1)
*@
\begin{figure}
\begin{center}
*<<label=fig1,fig=TRUE,echo=FALSE>>=
*<<fig1plot>>
*@
\end{center}
\caption{Scatter Plot with Regression Line}
\label{fig:one}
\end{figure}
Note that \verb@x@, \verb@y@, and \verb@out1@ are remembered from
the preceding code chunk.  We don't have to regenerate them.
All code chunks are part of one R ``session''.
```

---

```latex
Figure~\ref{fig:one} (p.~\pageref{fig:one})
is produced by the following code
*<<label=fig1plot,include=FALSE>>=
plot(x, y)
abline(out1)
*@
\begin{figure}
\begin{center}
*<<label=fig1,fig=TRUE,echo=FALSE>>=
<<fig1plot>>
*@
\end{center}
\caption{Scatter Plot with Regression Line}
\label{fig:one}
\end{figure}
Note that \verb@x@, \verb@y@, and \verb@out1@ are remembered from
the preceding code chunk.  We don't have to regenerate them.
All code chunks are part of one R ``session''.
```

---

```latex
Figure~\ref{fig:one} (p.~\pageref{fig:one})
is produced by the following code
*<<label=fig1plot,include=FALSE>>=
plot(x, y)
abline(out1)
@
\begin{figure}
\begin{center}
<<label=fig1,fig=TRUE,echo=FALSE>>=
*<<fig1plot>>
@
\end{center}
\caption{Scatter Plot with Regression Line}
\label{fig:one}
\end{figure}
Note that \verb@x@, \verb@y@, and \verb@out1@ are remembered from
the preceding code chunk.  We don't have to regenerate them.
All code chunks are part of one R ``session''.
```

---
layout: true

# knitr

---

---

[Yihui Xie - Interview by DataScience.LA at useR 2014][yihui-knitr-interview]

---

.f3[
1. Write in [markdown](https://commonmark.org/help/)

1. Cleaner chunk and inline R code syntax

1. Easy figures

1. Still literate
]

---

````markdown
Let's write another program that computes prime numbers, called `prime_numbers()`.

```
prime_numbers <- function(m = 1) {
  <<prime-numbers>>
}
```
````

Let's write another program that computes prime numbers, called `prime_numbers()`.

```
prime_numbers <- function(m = 1) {
  <<prime-numbers>>
}
```

---

````markdown
Well, we can now include R in our document.  Here's a simple example.

```{r two}
2 + 2
```
````

.mt5[
Well, we can now include R in our document.  Here's a simple example.

```r
2 + 2
```

```
## [1] 4
```
]

---
name: figure1

````markdown
Figure 1 is produced by the following code

```{r fig1plot, fig.width = 4, fig.height = 4}
n <- 50
x <- seq(1, n)
y <- 3 + (1.5 * x) + (17.3 * rnorm(n))
fit <- lm(y ~ x)
plot(x, y)
par(mar = rep(0, 4))
abline(fit)
```
````

---

````markdown
For one point, `x` is `r x[10]`, `y` is `r y[10]` and we predict
`y` will be `r predict(fit, list(x = 10))`.
````

For one point, `x` is 10, `y` is 26.5050704 and we predict
`y` will be 18.6470099.

---
layout: true

# knitr with pandoc

---

---

---

<div class="shadow-6">
<div class="code-window-title-bar ph2 mb0 pv1 mt5 small bg-black-05 black-80 center relative">
Terminal
<div class="code-window-circles">
  <span class="code-window-circle bg-red br-100 dib"></span><span class="code-window-circle bg-yellow br-100 dib"></span><span class="code-window-circle bg-green br-100 dib"></span>
</div>
</div>
<pre class="mt0 pa3 bg-black white">.code.white[pandoc report.md -o report..yellow.animated.heartBeat.dib[docx]]</pre>
</div>

---

<div class="shadow-6">
<div class="code-window-title-bar ph2 mb0 pv1 mt5 small bg-black-05 black-80 center relative">
Terminal
<div class="code-window-circles">
  <span class="code-window-circle bg-red br-100 dib"></span><span class="code-window-circle bg-yellow br-100 dib"></span><span class="code-window-circle bg-green br-100 dib"></span>
</div>
</div>
<div class="mt0 pa3 bg-black white">.code.white[pandoc report.md -o report.html .yellow[--no-highlight \<br>&nbsp;&nbsp;--css assets/css/title-slide.css \<br>&nbsp;&nbsp;--css assets/css/toronto-data-workshop.css \<br>&nbsp;&nbsp;--section-divs --standalone --variable math=true]]</div>
</div>

---
layout: true

# R Markdown

---

---

---

---

![](assets/img/iphone-original.jpg)

---

![](assets/img/iphone-original-2.jpg)

---
layout: false
class: apple-gradient hide-count middle

.flex[
.w-40.ph4.flex.items-center.justify-center.animated.slideInLeft[
![](assets/img/rmarkdown.png)
]

.w-60.white.f3.pl5.lh-extra.flex.items-center.justify-center.animated.flipInY.delay-1s[
PDF Reports
Word Documents
PowerPoint Presentations
Interactive Dashboards
Books
Websites
]
]

---
layout: false
class: apple-gradient hide-count middle

.flex[
.w-40.ph4.flex.items-center.justify-center[
![](assets/img/rmarkdown.png)
]

.w-60.white.f3.pl5.lh-extra.flex.items-center.justify-center.animated.flipInY[
Slides Like These!
]
]

---
class: hide-count middle

# rmarkdown

[rmarkdown.rstudio.com](https://rmarkdown.rstudio.com)

.w-50.h-100.absolute.right-0.top-0[
![](assets/img/rmarkdown-webpage.png)
]

---
class: inverse middle

# epoxy

---
layout: false

## knitr documents can write themselves

````markdown
```{r}
years <- c(2019, 2020)
grand_total <- c(858462, 346494)
```

```{r plastics}
items <- paste(
  "\n- In", years, "we collected", grand_total, "pieces of plastic."
)
items
```
````

```
## [1] "\n- In 2019 we collected 858462 pieces of plastic."
## [2] "\n- In 2020 we collected 346494 pieces of plastic."
```

---
layout: true

## knitr documents can write themselves

````markdown
```{r}
years <- c(2019, 2020)
grand_total <- c(858462, 346494)
```

```{r plastics, results = "asis"}
items <- paste(
  "\n- In", years, "we collected", grand_total, "pieces of plastic."
)
cat(items)
```
````

---

````markdown
- In 2019 we collected 858462 pieces of plastic.
- In 2020 we collected 346494 pieces of plastic.
````

---

- In 2019 we collected 858462 pieces of plastic.
- In 2020 we collected 346494 pieces of plastic.

---
layout: true

# Meet glue

---

```r
paste(
  "\n- In", years, "we collected", grand_total, "pieces of plastic."
)
```

```
## [1] "\n- In 2019 we collected 858462 pieces of plastic."
## [2] "\n- In 2020 we collected 346494 pieces of plastic."
```

.mv4[
***
]

```r
library(glue)

glue("\n- In {years} we collected {grand_total} pieces of plastic.")
```

```
## - In 2019 we collected 858462 pieces of plastic.
## - In 2020 we collected 346494 pieces of plastic.
```

---
layout: true

# epoxy, like superglue

---

&#x1F449; [gadenbuie/epoxy][epoxy]

```r
library(epoxy)
```

---

```r
glue("\n- In {years} we collected {grand_total} pieces of plastic.")
```

```
## - In 2019 we collected 858462 pieces of plastic.
## - In 2020 we collected 346494 pieces of plastic.
```

---

````markdown
```{epoxy}
- In {years} we collected {grand_total} pieces of plastic.

```
````

- In 2019 we collected 858462 pieces of plastic.

- In 2020 we collected 346494 pieces of plastic.

---

[#tidytuesday](# https://github.com/rfordatascience/tidytuesday/blob/master/data/2021/2021-01-26/)

[Break Free From Plastics](https://www.breakfreefromplastic.org/globalbrandauditreport2020/)

```r
library(dplyr)

# plastics <- tidytuesdayR::tt_load(2021, week = 5)$plastics
plastics <- readr::read_csv(here::here("data", "plastics.csv"))

plastics_grand_summary <-
  plastics %>%
  group_by(country, year, num_events, volunteers) %>%
  summarize(
    grand_total = sum(grand_total, na.rm = TRUE),
    .groups = "drop"
  ) %>%
  arrange(year, desc(grand_total))
```

---

```r
plastics_grand_summary
```

```
## # A tibble: 107 × 5
##    country                      year num_events volunteers grand_total
##    <chr>                       <dbl>      <dbl>      <dbl>       <dbl>
##  1 Taiwan_ Republic of China …  2019          2      31318      241292
##  2 NIGERIA                      2019         14       1648      161140
##  3 EMPTY                        2019        145       1416      113910
##  4 Philippines                  2019         20       3751       74032
##  5 Indonesia                    2019         32       6850       26618
##  6 ECUADOR                      2019          1        455       25430
##  7 Vietnam                      2019          4        400       21774
##  8 Kenya                        2019          5       1560       18988
##  9 Cameroon                     2019         10        387       17190
## 10 Switzerland                  2019          6        327       15002
## # ℹ 97 more rows
```

---

```r
plastics_year_summary <-
  plastics_grand_summary %>%
  group_by(year) %>%
  summarize(
    countries = n(),
    across(c(num_events, volunteers, grand_total), sum, na.rm = TRUE)
  ) %>%
  mutate(across(-(1:2), format, big.mark = ","))
```

---

```r
plastics_year_summary
```

```
## # A tibble: 2 × 5
##    year countries num_events volunteers grand_total
##   <dbl>     <int> <chr>      <chr>      <chr>
## 1  2019        52 483        72,236     858,462
## 2  2020        55 575        14,734     346,494
```

---

````markdown
```{epoxy data = plastics_year_summary}
- **In {year}**, _Break Free From Plastic_ engaged {volunteers} volunteers in
  {countries} countries to conduct {num_events} brand audits.
  These volunteers collected {grand_total} pieces of plastic waste.

```
````

---

.f3[
- **In 2019**, _Break Free From Plastic_ engaged 72,236 volunteers in
  52 countries to conduct 483 brand audits.
  These volunteers collected 858,462 pieces of plastic waste.

- **In 2020**, _Break Free From Plastic_ engaged 14,734 volunteers in
  55 countries to conduct 575 brand audits.
  These volunteers collected 346,494 pieces of plastic waste.
]

---
layout: false
class: inverse middle

# shinyComponents

---

# R Markdown all the things

&#x1F449; [gadenbuie/shinyComponents][epoxy]

---
layout: false
class: inverse middle

# Resources

---

## Links and Further Reading

- [epoxy]

- [shinyComponents]

- [R Markdown Cookbook](https://bookdown.org/yihui/rmarkdown-cookbook/)

- [Wrap Vectors in Markdown Formatting • gluedown](https://kiernann.com/gluedown/)

- [Yihui Xie - New developments in knitr and R Markdown v2 (2014)](https://www.youtube.com/watch?v=2yvW0O_7xOg)

- [Yihui Xie - Interview by DataScience.LA at useR 2014][yihui-knitr-interview]

[yihui-knitr-interview]: https://www.youtube.com/watch?v=LussVnrLZKU
[epoxy]: https://github.com/gadenbuie/epoxy
[shinyComponents]: https://github.com/gadenbuie/shinyComponents