2.1 YAML

The content on the top of the R Markdown document in three dashes is the YAML matter. The YAML matter for this document is as below:

---
title: "Reproducible Research"
subtitle: "Hands-On Excercises"
author: "Roy Francis"
date: "`r format(Sys.Date(),format='%d-%b-%Y')`"
output:
  bookdown::html_document2:
    toc: true
    toc_float: true
    toc_depth: 3
    number_sections: true
    theme: united
    highlight: tango
    df_print: paged
    code_folding: "none"
    self_contained: false
    keep_md: false
    encoding: "UTF-8"
    css: ["assets/course.css"]
---

The title, subtitle, author and date is displayed at the top of the rendered document in a pre-specified .css style. In the above example the data is automatically printed using the r function Sys.Date(). Argument output is used to specify output document type and related arguments. rmarkdown::html_document is used to specify the standard HTML output. rmarkdown::pdf_document is used to specify the standard PDF output. Sub arguments differ depending on the output document type. Above are some of the arguments that can be supplied to the HTML document type. theme is used to specify the document style such as the font and layout. highlight is used to specify the code highlighting style. toc specifies that a table of contents must be included. Use ?rmarkdown::html_document for description of all the various options.

2.2 Text

The above level 2 heading was created by specifying ## Text. Other headings can be specified similarily.

## Level 2 heading  
### Level 3 heading  
#### Level 4 heading  
##### Level 5 heading  
###### Level 6 heading 

Italic text like this This is italic text can be specified using *This is italic text* or _This is italic text_. Bold text like this This is bold text can be specified using **This is italic text** or **This is italic text**. Subscript written like this H~2~O renders as H₂O. Superscript written like this 2^10^ renders as 2¹⁰.

Bullet points are usually specified using an asterisk (+ or -).

+ Point one
+ Point two

• Point one
• Point two

Block quotes can be specified using >.

> This is a block quote. This
> paragraph has two lines.

This is a block quote. This paragraph has two lines.

Lists can also be created inside block quotes.

> 1. This is a list inside a block quote.
> 2. Second item.

1. This is a list inside a block quote.
2. Second item.

Links can be created using [this](https://rmarkdown.rstudio.com/) like this.

2.3 Code

Text can be formatted as code. Code is displayed using monospaced font. Code formatting that stands by itself as a paragraph is called block code. Block codes are specified using three backticks ``` followed by code and then three more backticks.

This text below

```
This is generic block code.
```

renders like this

This is generic block code.

Code formatting can also be included in the middle of a sentence. This is called inline code formatting. Using this `This is an inline formatted code.` renders like this: This is an inline formatted code.

The above codes are not actually executed. They are just text formatted in a different font. Code can be executed by specifying the language along with the backticks. Block code formatted as such:

```{r}
str(iris)
```

renders like this:

str(iris)

## 'data.frame':    150 obs. of  5 variables:
##  $ Sepal.Length: num  5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
##  $ Sepal.Width : num  3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
##  $ Petal.Length: num  1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
##  $ Petal.Width : num  0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
##  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...

Code blocks are called chunks. The chunk is executed when this document is rendered. The rendered code output is also given code highlighting based on the language. For example;

This code chunk

```{r,eval=FALSE}
ggplot(dfr4,aes(x=Month,y=fraction,colour=Year,group=Year))+
  geom_point(size=2)+
  geom_line()+
  labs(x="Month",y="Fraction of support issues")+
  scale_colour_manual(values=c("#000000","#E69F00","#56B4E9",
  "#009E73","#F0E442","#006699","#D55E00","#CC79A7"))+
  theme_bw(base_size=12,base_family="Gidole")+
  theme(panel.border=element_blank(),
        panel.grid.minor=element_blank(),
        panel.grid.major.x=element_blank(),
        axis.ticks=element_blank())
```

when rendered (not evaluated) looks like

ggplot(dfr4,aes(x=Month,y=fraction,colour=Year,group=Year))+
  geom_point(size=2)+
  geom_line()+
  labs(x="Month",y="Fraction of support issues")+
  scale_colour_manual(values=c("#000000","#E69F00","#56B4E9",
  "#009E73","#F0E442","#006699","#D55E00","#CC79A7"))+
  theme_bw(base_size=12,base_family="Gidole")+
  theme(panel.border=element_blank(),
        panel.grid.minor=element_blank(),
        panel.grid.major.x=element_blank(),
        axis.ticks=element_blank())

The chunk has several options which can be used to control chunk properties.

Using `{r,eval=FALSE}` prevents that chunk from being executed. Using `{r,echo=FALSE}` prevents the code from that chunk from being displayed. Using `{r,results="hide"}` hides the output from that chunk.

Chunk options are specified like this:

```{r,eval=FALSE,echo=FALSE,fig.height=6,fig.width=7}
```

2.4 Images

Images can be displayed using ![This is a caption](rr_lab_assets/summer.jpg). For example:

This is a caption

For more control over image size, raw HTML needs to be used. For example;

<img src="rr_lab_assets/summer.jpg" width="100px">

2.5 Plots

R Plots can be plotted like below:

```{r,fig.height=6,fig.width=6}
plot(x=iris$Petal.Length,y=iris$Petal.Width)
```

plot(x=iris$Petal.Length,y=iris$Petal.Width)

Below are some of chunk options relating to plots.

2.6 Export

The R Markdown notebook can be exported into various format. The most common formats are HTML and PDF.

2.6.1 HTML

The R Markdown document can be previewed as an HTML inside RStudio by clicking the ‘Knit’ button.

The document can also be exported as an HTML file by running the code below:

rmarkdown::render("document.Rmd")

HTML documents can be opened and viewed in any standard browser such as Chrome, Safari, Firefox etc.

rmarkdown::render("document.Rmd")

rmarkdown::render("document.Rmd",output_format=pdf_document())

3.1 Report

This is a do-it-yourself challenge to R Markdown Notebook/Report. Have a look at the HTML page below and try to recreate the page. Instructions and helpful tips are given below.

This is the challenge report to prepare.

1. Create a new R Markdown document
2. Set YAML matter

• Set title, subtitle, Author name.
• Set date to be automatically computed in this format “25/04/2018”. Refer to ‘YAML’ section above for how to do this. See here on how to format dates.
• Show a floating table of contents on the top left of the page. See here on how to do this.
• Set automatic numbering of sections.
• Set theme to ‘flatly’.
• Set code highlighting to ‘kate’.
• Notice the little buttons on the right to show/hide code. Show this button and set all code to hidden by default. See here on how to do this.
• Set the default data.frame printing option to pageable HTML table. See here.

3. Add a Level 1 heading
4. Add some text and a Level 2 heading
5. Create an R chunk to display the structure of cars dataset. Display the code and the results. See here to read more about chunk options.
6. Display the first six rows and all columns of the cars dataset as a table.
7. Create a new sub-section and create a scatterplot with the two variables from cars dataset. Hide the code used and only show the plot. Create a square aspect ratio plot by setting equal figure height and width in the chunk options. Add a caption for the plot using chunk options.
8. Create a new sub-section, download a random image and include it in the document.
9. Render the document in RStudio by clicking on the ‘Knit’ button.
10. Render the document to an HTML file using a console command.
11. Render this document to a PDF. Change output type from html_document to pdf_document and remove all arguments except toc: true. Try rendering using ‘Knit’.

3.2 Presentation | ioslides

This is a do-it-yourself challenge to ioslides Presentation using R Markdown. Have a look at the presentation below and try to recreate it. Instructions and helpful tips are given below.

This is the challenge ioslide presentation.

1. Create a new R Markdown document.
2. Set YAML matter output to output: ioslides_presentation. See here for a guide to using ioslides presentation in R.
3. Set theme and highlight as needed.
4. New slides are defined using # with level 1 heading or ---- without a heading. Subtitle can be specified using a pipe symbol, like this # Title | Subtitle. Slides starting with # contains only the title and/or subtitle. ## adds a standard content slide with a heading on the top.
5. Add a title slide

# Title Slide | Subtitle

7. Add a standard slide with a heading and a bulleted list. For example

## Level 2 Heading

- Point one
- Point two

The bullets can set to show incrementally on click:

## Level 2 Heading

> - Point one
> - Point two

8. Create a new slide and add some R chunk. For example:

```{r}
data(iris)
str(cars)
```

9. Create a new slide and display a table by executing an R chunk. For example:

```{r}
head(cars)
```

10. Create a new slide and display an R plot. For example:

```{r,fig.height=3,fig.width=5,fig.cap="This is a scatterplot."}
plot(cars$speed,cars$dist)
```

11. Add an image to a new slide. For example:

![](rr_lab_assets/gotland.jpg)

12. When viewing the presentation, press O to see an overview of the slides.

3.3 Presentation | revealJS

This is a do-it-yourself challenge to RevealJS 2-D Presentation using R Markdown. Have a look at the presentation below and try to recreate it. Instructions and helpful tips are given below.

This is the challenge RevealJS presentation.

1. Install R package revealjs and load the library.
2. Create a new R Markdown document.
3. Set YAML matter output to output: revealjs::revealjs_presentation. See here for a guide to using RevealJS presentation in R.
4. Set theme and highlight as needed.
5. New slides are defined using # with level 1 heading,## with level 2 heading or ---- without a heading. The best feature of RevealJS is that slides are not restricted to horizontal (linear) flow. Slides can also flow vertical from any of the horizontal slides. A level 2 heading ## signifies that the content under that flows vertically.
6. Add a level 1 heading and add some text content.
7. Create a new slide vertically by adding a level 2 heading and add some R chunk. For example:

## Level 2 Heading

```{r}
data(iris)
str(cars)
```

9. Create a new slide vertically using level 2 heading and display a table by executing an R chunk. For example:

## Level 2 Heading

```{r}
head(cars)
```

10. Create a new slide vertically and display an R plot. For example:

## Level 2 Heading

```{r,fig.height=3,fig.width=5,fig.cap="This is a scatterplot."}
plot(cars$speed,cars$dist)
```

11. Create a new slide horizontally. Add an image to a new slide. For example:

![](rr_lab_assets/gotland.jpg)

12. When viewing the presentation, press O to see an overview of the slides.