Chapter 16 Rmarkdown Tricks

We have been using RMarkdown files to combine the analysis and discussion into one nice document that contains all the analysis steps so that your research is reproducible.

There are many resources on the web about Markdown and the variant that RStudio uses (called RMarkdown), but the easiest reference is to just use the RStudio help tab to access the help. I particular like Help -> Cheatsheets -> RMarkdown Reference Guide because it gives me the standard Markdown information but also a bunch of information about the options I can use to customize the behavior of individual R code chunks.

Two topics that aren’t covered in the RStudio help files are how to insert mathematical text symbols and how to produce decent looking tables without too much fuss.

Most of what is presented here isn’t primarily about how to use R, but rather how to work with tools in RMarkdown so that the final product is neat and tidy. While you could print out your RMarkdown file and then clean it up in MS Word, sometimes there is a good to want as nice a starting point as possible.

16.1 Mathematical expressions

The primary way to insert a mathematical expression is to use a markup language called LaTeX. This is a very powerful system and it is what most Mathematicians use to write their documents. The downside is that there is a lot to learn. However, you can get most of what you need pretty easily.

For RMarkdown to recognize you are writing math using LaTeX, you need to enclose the LaTeX with dollar signs ($). Some examples of common LaTeX patterns are given below:

Goal	LaTeX	Output	LaTeX	Output
power	$x^2$	$x^2$	$y^{0.95}$	$y^{0.95}$
Subscript	$x_i$	$x_i$	$t_{24}$	$t_{24}$
Greek	`$\alpha$ $\beta$`	$\alpha$ $\beta$	`$\theta$ $\Theta$`	$\theta$ $\Theta$
Bar	$\bar{x}$	$\bar{x}$	$\bar{mu}_i$	$\bar{\mu}_i$
Hat	$\hat{mu}$	$\hat{\mu}$	$\hat{y}_i$	$\hat{y}_i$
Star	$y^*$	$y^*$	$\hat{\mu}^*_i$	$\hat{\mu}^*_i$
Centered Dot	$\cdot$	$\cdot$	$\bar{y}_{i\cdot}$	$\bar{y}_{i\cdot}$
Sum	$\sum x_i$	$\sum x_i$	$\sum_{i=0}^N x_i$	$\sum_{i=0}^N x_i$

Square Root	$\sqrt{a}$	$\sqrt{a}$	$\sqrt{a^2 + b^2}$	$\sqrt{a^2 + b^2}$

Fractions	$\frac{a}{b}$	$\frac{a}{b}$	$\frac{x_i - \bar{x}{s/\sqrt{n}$	$\frac{x_i - \bar{x}}{s/\sqrt{n}}$

Within your RMarkdown document, you can include LaTeX code by enclosing it with dollar signs. So you might write $\alpha=0.05$ in your text, but after it is knitted to a pdf, html, or Word, you’ll see $\alpha=0.05$. If you want your mathematical equation to be on its own line, all by itself, enclose it with double dollar signs. So

$$z_i = \frac{z_i-\bar{x}}{\sigma / \sqrt{n}}$$

would be displayed as

\[ z_{i}=\frac{x_{i}-\bar{X}}{\sigma/\sqrt{n}} \]

Unfortunately RMarkdown is a little picky about spaces near the $ and $$ signs and you can’t have any spaces between them and the LaTeX command. For a more information about all the different symbols you can use, google ‘LaTeX math symbols’.

16.2 Tables

For the following descriptions of the simple, grid, and pipe tables, I’ve shamelessly stolen from the Pandoc documentation. [http://pandoc.org/README.html#tables]

One way to print a table is to just print in in R and have the table presented in the code chunk. For example, suppose I want to print out the first 4 rows of the trees dataset.

data <- trees[1:4, ]
data

##   Girth Height Volume
## 1   8.3     70   10.3
## 2   8.6     65   10.3
## 3   8.8     63   10.2
## 4  10.5     72   16.4

Usually this is sufficient, but suppose you want something a bit nicer because you are generating tables regularly and you don’t want to have to clean them up by hand. Tables in RMarkdown follow the table conventions from the Markdown class with a few minor exceptions. Markdown provides 4 ways to define a table and RMarkdown supports 3 of those.

16.2.1 Simple Tables

Simple tables look like this (Notice I don’t wrap these dollar signs or anything, just a blank line above and below the table):

Right   Left     Center   Default 
------- ------ ---------- ------- 
     12 12        hmmm        12 
    123 123        123       123 
      1 1            1         1

and would be rendered like this:

Right	Left	Center	Default
12	12	hmmm	12
123	123	123	123
1	1	1	1

The headers and table rows must each fit on one line. Column alignments are determined by the position of the header text relative to the dashed line below it.

If the dashed line is flush with the header text on the right side but extends beyond it on the left, the column is right-aligned. If the dashed line is flush with the header text on the left side but extends beyond it on the right, the column is left-aligned. If the dashed line extends beyond the header text on both sides, the column is centered. If the dashed line is flush with the header text on both sides, the default alignment is used (in most cases, this will be left). The table must end with a blank line, or a line of dashes followed by a blank line.

16.2.2 Grid Tables

Grid tables are a little more flexible and each cell can take an arbitrary Markdown block elements (such as lists).

+---------------+---------------+--------------------+
| Fruit         | Price         | Advantages         |
+===============+===============+====================+
| Bananas       | $1.34         | - built-in wrapper |
|               |               | - bright color     |
+---------------+---------------+--------------------+
| Oranges       | $2.10         | - cures scurvy     |
|               |               | - tasty            |
+---------------+---------------+--------------------+

which is rendered as the following:

Fruit	Price	Advantages
Bananas	$1.34	built-in wrapper bright color
Oranges	$2.10	cures scurvy tasty

Grid table doesn’t support Left/Center/Right alignment. Both Simple tables and Grid tables require you to format the blocks nicely inside the RMarkdown file and that can be a bit annoying if something changes and you have to fix the spacing in the rest of the table. Both Simple and Grid tables don’t require column headers.

16.2.3 Pipe Tables

Pipe tables look quite similar to grid tables but Markdown isn’t as picky about the pipes lining up. However, it does require a header row (which you could leave the elements blank in).

| Right | Left | Default | Center |
|------:|:-----|---------|:------:|
|   12  |  12  |    12   |    12  |
|  123  |  123 |   123   |   123  |
|    1  |    1 |     1   |     1  |

which will render as the following:

Right	Left	Default	Center
12	12	12	12
123	123	123	123
1	1	1	1

In general I prefer to use the pipe tables because it seems a little less picky about getting everything correct. However it is still pretty annoying to get the table laid out correctly.

In all of these tables, you can use the regular RMarkdown formatting tricks for italicizing and bolding. So I could have a table such as the following:

|   Source    |  df  |   Sum of Sq   |    Mean Sq    |    F   |  $Pr(>F_{1,29})$    |
|:------------|-----:|--------------:|--------------:|-------:|--------------------:|
|  Girth      |  *1* |  7581.8       |  7581.8       | 419.26 |  **< 2.2e-16**      |
|  Residual   |  29  |  524.3        |   18.1        |        |                     |

and have it look like this:

Source	df	Sum of Sq	Mean Sq	F	$Pr(>F_{1,29})$
Girth	1	7581.8	7581.8	419.26	< 2.2e-16
Residual	29	524.3	18.1

The problem with all of this is that I don’t want to create these by hand. Instead I would like functions that take a data frame or matrix and spit out the RMarkdown code for the table.

16.3 R functions to produce table code.

There are a couple of different packages that convert a data frame to simple/grid/pipe table. We will explore a couple of these, starting with the most basic and moving to the more complicated. The general idea is that we’ll produce the appropriate simple/grid/pipe table syntax in R, and when it gets knitted, then RMarkdown will turn our simple/grid/pipe table into something pretty.

16.3.1 `knitr::kable`

The knitr package includes a function that produces simple tables. It doesn’t have much customizability, but it gets the job done.

knitr::kable( data )

Girth	Height	Volume
8.3	70	10.3
8.6	65	10.3
8.8	63	10.2
10.5	72	16.4

16.3.2 Package `pander`

The package pander seems to be a nice compromise between customization and not having to learn too much. It is relatively powerful in that it will take summary() and anova() output and produce tables for them. By default pander will produce simple tables, but you can ask for Grid or Pipe tables.

library(pander)
pander( data, style='rmarkdown' )   # style is pipe tables...

Girth	Height	Volume
8.3	70	10.3
8.6	65	10.3
8.8	63	10.2
10.5	72	16.4

The pander package deals with summary and anova tables from a variety of different analyses. So you can simply ask for a nice looking version using the following:

model <- lm( Volume ~ Girth, data=trees )    # a simple regression
pander( summary(model) )    # my usual summary table
pander( anova( model ) )    # my usual anova table

	Estimate	Std. Error	t value	Pr(>\|t\|)
(Intercept)	-36.94	3.365	-10.98	7.621e-12
Girth	5.066	0.2474	20.48	8.644e-19

Fitting linear model: Volume ~ Girth
Observations	Residual Std. Error	$R^2$	Adjusted $R^2$
31	4.252	0.9353	0.9331

Analysis of Variance Table
	Df	Sum Sq	Mean Sq	F value	Pr(>F)
Girth	1	7582	7582	419.4	8.644e-19
Residuals	29	524.3	18.08	NA	NA

Goal	LaTeX	Output	LaTeX	Output
power	$x^2$	\(x^2\)	$y^{0.95}$	\(y^{0.95}\)
Subscript	$x_i$	\(x_i\)	$t_{24}$	\(t_{24}\)
Greek	`$\alpha$ $\beta$`	\(\alpha\) \(\beta\)	`$\theta$ $\Theta$`	\(\theta\) \(\Theta\)
Bar	$\bar{x}$	\(\bar{x}\)	$\bar{mu}_i$	\(\bar{\mu}_i\)
Hat	$\hat{mu}$	\(\hat{\mu}\)	$\hat{y}_i$	\(\hat{y}_i\)
Star	$y^*$	\(y^*\)	$\hat{\mu}^*_i$	\(\hat{\mu}^*_i\)
Centered Dot	$\cdot$	\(\cdot\)	$\bar{y}_{i\cdot}$	\(\bar{y}_{i\cdot}\)
Sum	$\sum x_i$	\(\sum x_i\)	$\sum_{i=0}^N x_i$	\(\sum_{i=0}^N x_i\)

Square Root	$\sqrt{a}$	\(\sqrt{a}\)	$\sqrt{a^2 + b^2}$	\(\sqrt{a^2 + b^2}\)

Fractions	$\frac{a}{b}$	\(\frac{a}{b}\)	$\frac{x_i - \bar{x}{s/\sqrt{n}$	\(\frac{x_i - \bar{x}}{s/\sqrt{n}}\)