R Markdown: The Definitive Guide A PreTeXt Edition

@Manual{R-base,
  title = {R: A Language and Environment for Statistical
    Computing},
  author = {{R Core Team}},
  organization = {R Foundation for Statistical Computing},
  address = {Vienna, Austria},
  year = {2017},
  url = {https://www.R-project.org/},
}

# First-level header

## Second-level header

### Third-level header

# Preface {-}

- one item
- one item
- one item
    - one more item
    - one more item
    - one more item

1. the first item
2. the second item
3. the third item
    - one unordered item
    - one unordered item

> "I thoroughly disapprove of duels. If a man should challenge me,
  I would take him kindly and forgivingly by the hand and lead him
  to a quiet place and kill him."
>
> --- Mark Twain

```
This text is displayed verbatim / preformatted
```

Or indent by four spaces:

    This text is displayed verbatim / preformatted

In R, the character
# indicates a comment.

The result of 5
- 3 is 2.

$$\begin{array}{ccc}
x_{11} & x_{12} & x_{13}\\
x_{21} & x_{22} & x_{23}
\end{array}$$

$$X = \begin{bmatrix}1 & x_{1}\\
1 & x_{2}\\
1 & x_{3}
\end{bmatrix}$$

$$\Theta = \begin{pmatrix}\alpha & \beta\\
\gamma & \delta
\end{pmatrix}$$

$$\begin{vmatrix}a & b\\
c & d
\end{vmatrix}=ad-bc$$

```{r}
plot(cars, pch = 18)
```

par(mar = c(4, 4, .2, .1))
plot(cars, pch = 19)
plot(pressure, pch = 17)

```{r, out.width='25%', fig.align='center', fig.cap='...'}
knitr::include_graphics('images/hex-rmarkdown.png')
```

```{r tables-mtcars}
knitr::kable(iris[1:5, ], caption = 'A caption')
```

---
title: "Python code chunks in R Markdown"
date: 2018-02-22
---

## A normal R code chunk

```{r}
library(reticulate)
x = 42
print(x)
```

## Modify an R variable

In the following chunk, the value of `x` on the right hand side
is `r x`, which was defined in the previous chunk.

```{r}
x = x + 12
print(x)
```

## A Python chunk

This works fine and as expected. 

```{python}
x = 42 * 2
print(x) 
```

The value of `x` in the Python session is `r py$x`.
It is not the same `x` as the one in R.

## Modify a Python variable

```{python}
x = x + 18 
print(x)
```

Retrieve the value of `x` from the Python session again:

```{r}
py$x
```

Assign to a variable in the Python session from R:

```{r}
py$y = 1:5
```

See the value of `y` in the Python session:

```{python}
print(y)
```

## Python graphics

You can draw plots using the **matplotlib** package in Python.

```{python}
import matplotlib.pyplot as plt
plt.plot([0, 2, 1, 4])
plt.show()
```

```{bash}
echo "Hello Bash!"
cat flights1.csv flights2.csv flights3.csv > flights.csv
```

```{r}
library(DBI)
db = dbConnect(RSQLite::SQLite(), dbname = "sql.sqlite")
```

```{sql, connection=db}
SELECT * FROM trials
```

```{sql, connection=db, max.print = 20}
SELECT * FROM trials
```

```{sql, connection=db, tab.cap = "My Caption"}
SELECT * FROM trials
```

```{sql, connection=db, output.var="trials"}
SELECT * FROM trials
```

```{r}
subjects = 10
```

```{sql, connection=db, output.var="trials"}
SELECT * FROM trials WHERE subjects >= ?subjects
```

```{r setup}
library(DBI)
db = dbConnect(RSQLite::SQLite(), dbname = "sql.sqlite")
knitr::opts_chunk$set(connection = "db")
```

```{sql}
SELECT * FROM trials
```

```{rcpp}
#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::export]]
NumericVector timesTwo(NumericVector x) {
  return x * 2;
}
```

```{Rcpp, cache=TRUE}
#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::export]]
NumericVector timesTwo(NumericVector x) {
  return x * 2;
}
```

All C++ code chunks will be combined to the chunk below:

```{rcpp, ref.label=knitr::all_rcpp_labels(), include=FALSE}
```

First we include the header `Rcpp.h`:

```{rcpp, eval=FALSE}
#include <Rcpp.h>
```

Then we define a function:

```{rcpp, eval=FALSE}
// [[Rcpp::export]]
int timesTwo(int x) {
  return x * 2;
}
```

```{stan, output.var="ex1"}
parameters {
  real y[2];
}
model {
  y[1] ~ normal(0, 1);
  y[2] ~ double_exponential(0, 2);
}
```

```{r}
library(rstan)
fit = sampling(ex1)
print(fit)
```

```{js, echo=FALSE}
$('.title').css('color', 'red')
```

```{css, echo=FALSE}
body {
  color: red;
}
```

```{julia}
a = sqrt(2);  # the semicolon inhibits printing
```

```{c, test-c, results='hide'}
void square(double *x) {
  *x = *x * *x;
}
```

Test the `square()` function:

```{r}
.C('square', 9)
.C('square', 123)
```

---
title: "An Interactive Map"
---

Below is a map that shows the location of the
Department of Statistics, Iowa State University.

```{r out.width='100%', echo=FALSE}
library(leaflet)
leaflet() %>% addTiles() %>%
  setView(-93.65, 42.0285, zoom = 17) %>%
  addPopups(
    -93.65, 42.0285,
    'Here is the <b>Department of Statistics</b>, ISU'
  )
```

---
title: "A Shiny Document"
output: html_document
runtime: shiny
---

A standard R plot can be made interactive by wrapping
it in the Shiny `renderPlot()` function. The `selectInput()`
function creates the input widget to drive the plot.

```{r eruptions, echo=FALSE}
selectInput(
  'breaks', label = 'Number of bins:',
  choices = c(10, 20, 35, 50), selected = 20
)

renderPlot({
  par(mar = c(4, 4, .1, .5))
  hist(
    faithful$eruptions, as.numeric(input$breaks),
    col = 'gray', border = 'white',
    xlab = 'Duration (minutes)', main = ''
  )
})
```