2 Attributes of Bookdown

This section contains examples and information of things we can do (interactive charts, tables, etc)

## Warning: package 'DT' was built under R version 4.2.2

## Warning: package 'tidyverse' was built under R version 4.2.2

## Warning: package 'kableExtra' was built under R version 4.2.2

You can label chapter and section titles using {#label} after them, e.g., we can reference Chapter 1. If you do not manually label them, there will be automatic labels anyway, e.g., Chapter ??.

Figures and tables with captions will be placed in figure and table environments, respectively.

Code

par(mar = c(4, 4, .1, .1))
plot(pressure, type = 'b', pch = 19)

Figure 2.1: Here is a nice figure!

Reference a figure by its code chunk label with the fig: prefix, e.g., see Figure 2.1. Similarly, you can reference tables generated from knitr::kable(), e.g., see Table 2.1.

Code

knitr::kable(
  head(iris, 20), caption = 'Here is a nice table!',
  booktabs = TRUE
)

Table 2.1: Here is a nice table!

Sepal.Length	Sepal.Width	Petal.Length	Petal.Width	Species
5.1	3.5	1.4	0.2	setosa
4.9	3.0	1.4	0.2	setosa
4.7	3.2	1.3	0.2	setosa
4.6	3.1	1.5	0.2	setosa
5.0	3.6	1.4	0.2	setosa
5.4	3.9	1.7	0.4	setosa
4.6	3.4	1.4	0.3	setosa
5.0	3.4	1.5	0.2	setosa
4.4	2.9	1.4	0.2	setosa
4.9	3.1	1.5	0.1	setosa
5.4	3.7	1.5	0.2	setosa
4.8	3.4	1.6	0.2	setosa
4.8	3.0	1.4	0.1	setosa
4.3	3.0	1.1	0.1	setosa
5.8	4.0	1.2	0.2	setosa
5.7	4.4	1.5	0.4	setosa
5.4	3.9	1.3	0.4	setosa
5.1	3.5	1.4	0.3	setosa
5.7	3.8	1.7	0.3	setosa
5.1	3.8	1.5	0.3	setosa

You can write citations, too. For example, we are using the bookdown package [@R-bookdown] in this sample book, which was built on top of R Markdown and knitr [@xie2015].

Finally, here is an example of an interactive plot that leverages HTML and Javascript we can use for illustrating statistical distributions. (These only work for HTML format and not LaTex nor PDF.)

This is an interactive table

Code

DT::datatable(iris)

Show 102550100 entries

Search:

	Sepal.Length	Sepal.Width	Petal.Length	Petal.Width	Species
1	5.1	3.5	1.4	0.2	setosa
2	4.9	3	1.4	0.2	setosa
3	4.7	3.2	1.3	0.2	setosa
4	4.6	3.1	1.5	0.2	setosa
5	5	3.6	1.4	0.2	setosa
6	5.4	3.9	1.7	0.4	setosa
7	4.6	3.4	1.4	0.3	setosa
8	5	3.4	1.5	0.2	setosa
9	4.4	2.9	1.4	0.2	setosa
10	4.9	3.1	1.5	0.1	setosa

Showing 1 to 10 of 150 entries

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2.1 Interactive Plots

and here are a few examples of interactive plots using plotly and other packages. The R Graph Gallery is a good reference for the type of plots at our disposal.

Code

p <- gapminder %>%
  filter(year==1977) %>%
  ggplot( aes(gdpPercap, lifeExp, size = pop, color=continent)) +
  geom_point() +
  theme_bw()

ggplotly(p)

Code

theUrl <- "http://vincentarelbundock.github.io/Rdatasets/csv/reshape2/tips.csv"
tips <- read.table(file = theUrl, header = TRUE, sep = ",")

p <- ggplot(tips, aes(x=total_bill, weight = tip, color=sex, fill = sex)) +
  geom_histogram(binwidth=2.5) +
  ylab("sum of tip") + 
  geom_rug(sides="t", length = unit(0.3, "cm"))
fig <- ggplotly(p)
fig

Code

df <- read.csv('https://raw.githubusercontent.com/plotly/datasets/master/iris-data.csv')

pl_colorscale=list(c(0.0, '#19d3f3'),
               c(0.333, '#19d3f3'),
               c(0.333, '#e763fa'),
               c(0.666, '#e763fa'),
               c(0.666, '#636efa'),
               c(1, '#636efa'))

axis = list(showline=FALSE,
            zeroline=FALSE,
            gridcolor='#ffff',
            ticklen=4)

fig <- df %>%
  plot_ly() 
fig <- fig %>%
  add_trace(
    type = 'splom',
    dimensions = list(
      list(label='sepal length', values=~sepal.length),
      list(label='sepal width', values=~sepal.width),
      list(label='petal length', values=~petal.length),
      list(label='petal width', values=~petal.width)
    ),
    text=~class,
    marker = list(
      color = as.integer(df$class),
      colorscale = pl_colorscale,
      size = 7,
      line = list(
        width = 1,
        color = 'rgb(230,230,230)'
      )
    )
  ) 

## Warning in add_trace(., type = "splom", dimensions = list(list(label = "sepal length", : NAs
## introduced by coercion

Code

fig <- fig %>%
  layout(
    title= 'Iris Data set',
    hovermode='closest',
    dragmode= 'select',
    plot_bgcolor='rgba(240,240,240, 0.95)',
    xaxis=list(domain=NULL, showline=F, zeroline=F, gridcolor='#ffff', ticklen=4),
    yaxis=list(domain=NULL, showline=F, zeroline=F, gridcolor='#ffff', ticklen=4),
    xaxis2=axis,
    xaxis3=axis,
    xaxis4=axis,
    yaxis2=axis,
    yaxis3=axis,
    yaxis4=axis
  )

fig