# Tools for making latex tables in R

Thanks Joris for creating this question. Hopefully, it will be made into a community wiki.

The booktabs packages in latex produces nice looking tables. Here is a blog post on how to use xtable to create latex tables that use booktabs

I would also add the `apsrtable`

package to the mix as it produces nice looking regression tables.

Another Idea: Some of these packages (esp. memisc and apsrtable) allow easy extensions of the code to produce tables for different regression objects. One such example is the lme4 memisc code shown in the question. It might make sense to start a github repository to collect such code snippets, and over time maybe even add it to the memisc package. Any takers?

On general request, a community wiki on producing latex tables in R. In this post I'll give an overview of the most commonly used packages and blogs with code for producing latex tables from less straight-forward objects. Please feel free to add any I missed, and/or give tips, hints and little tricks on how to produce nicely formatted latex tables with R.

## Packages :

- xtable : for standard tables of most simple objects. A nice gallery with examples can be found here.
- memisc : tool for management of survey data, contains some tools for latex tables of (basic) regression model estimates.
- Hmisc contains a function
`latex()`

that creates a tex file containing the object of choice. It is pretty flexible, and can also output`longtable`

latex tables. There's a lot of info in the help file`?latex`

- miscFuncs has a neat function 'latextable' that converts matrix data with mixed alphabetic and numeric entries into a LaTeX table and prints them to the console, so they can be copied and pasted into a LaTeX document.
- texreg package (JSS paper) converts statistical model output into LaTeX tables. Merges multiple models. Can cope with about 50 different model types, including network models and multilevel models (lme and lme4).
- reporttools package (JSS paper) is another option for descriptive statistics on continuous, categorical and date variables.
- tables package is perhaps the most general LaTeX table making package in R for descriptive statistics
- stargazer package makes nice comparative statistical model summary tables

## Blogs and code snippets

- There is the outreg function of Paul Johnson that gives Stata-like tables in Latex for the output of regressions. This one works great.
- As given in an earlier question, there's a code snippet to adapt the memisc package for lme4 objects.

## Related questions :

- Suggestion for R/LaTeX table creation package
- Rreport/LaTeX quality output package
- sorting a table for latex output with xtable
- Any way to produce a LaTeX table from an lme4 mer model fit object?
- R data.frame with stacked specified titles for latex output with xtable
- Automating adding tables fast to latex from R, with a very flexible and interesting syntax using the formula language

**... and Trick #3 Multiline entries in an Xtable**

Generate some more data

```
moredata<-data.frame(Nominal=c(1:5), n=rep(5,5),
MeanLinBias=signif(rnorm(5, mean=0, sd=10), digits=4),
LinCI=paste("(",signif(rnorm(5,mean=-2, sd=5), digits=4),
", ", signif(rnorm(5, mean=2, sd=5), digits=4),")",sep=""),
MeanQuadBias=signif(rnorm(5, mean=0, sd=10), digits=4),
QuadCI=paste("(",signif(rnorm(5,mean=-2, sd=5), digits=4),
", ", signif(rnorm(5, mean=2, sd=5), digits=4),")",sep=""))
names(moredata)<-c("Nominal", "n","Linear Model \nBias","Linear \nCI", "Quadratic Model \nBias", "Quadratic \nCI")
```

Now produce our xtable, using the sanitize function to replace column names with the correct Latex newline commands (including double backslashes so R is happy)

```
<<label=multilinetable, results=tex, echo=FALSE>>=
foo<-xtable(moredata)
align(foo) <- c( rep('c',3),'p{1.8in}','p{2in}','p{1.8in}','p{2in}' )
print(foo,
floating=FALSE,
include.rownames=FALSE,
sanitize.text.function = function(str) {
str<-gsub("\n","\\\\", str, fixed=TRUE)
return(str)
},
sanitize.colnames.function = function(str) {
str<-c("Nominal", "n","\\centering Linear Model\\\\ \\% Bias","\\centering Linear \\\\ 95\\%CI", "\\centering Quadratic Model\\\\ \\%Bias", "\\centering Quadratic \\\\ 95\\%CI \\tabularnewline")
return(str)
})
@
```

(although this isn't perfect, as we need \tabularnewline so the table is formatted correctly, and Xtable still puts in a final \, so we end up with a blank line below the table header.)

I have a few tricks and work arounds to interesting 'features' of xtable and Latex that I'll share here.

**Trick #1: Removing Duplicates in Columns and Trick #2: Using Booktabs**

First, load packages and define my clean function

```
<<label=first, include=FALSE, echo=FALSE>>=
library(xtable)
library(plyr)
cleanf <- function(x){
oldx <- c(FALSE, x[-1]==x[-length(x)])
# is the value equal to the previous?
res <- x
res[oldx] <- NA
return(res)}
```

Now generate some fake data

```
data<-data.frame(animal=sample(c("elephant", "dog", "cat", "fish", "snake"), 100,replace=TRUE),
colour=sample(c("red", "blue", "green", "yellow"), 100,replace=TRUE),
size=rnorm(100,mean=500, sd=150),
age=rlnorm(100, meanlog=3, sdlog=0.5))
#generate a table
datatable<-ddply(data, .(animal, colour), function(df) {
return(data.frame(size=mean(df$size), age=mean(df$age)))
})
```

Now we can generate a table, and use the clean function to remove duplicate entries in the label columns.

```
cleandata<-datatable
cleandata$animal<-cleanf(cleandata$animal)
cleandata$colour<-cleanf(cleandata$colour)
@
```

this is a normal xtable

```
<<label=normal, results=tex, echo=FALSE>>=
print(
xtable(
datatable
),
tabular.environment='longtable',
latex.environments=c("center"),
floating=FALSE,
include.rownames=FALSE
)
@
```

this is a normal xtable where a custom function has turned duplicates to NA

```
<<label=cleandata, results=tex, echo=FALSE>>=
print(
xtable(
cleandata
),
tabular.environment='longtable',
latex.environments=c("center"),
floating=FALSE,
include.rownames=FALSE
)
@
```

This table uses the booktab package (and needs a \usepackage{booktabs} in the headers)

```
\begin{table}[!h]
\centering
\caption{table using booktabs.}
\label{tab:mytable}
<<label=booktabs, echo=F,results=tex>>=
mat <- xtable(cleandata,digits=rep(2,ncol(cleandata)+1))
foo<-0:(length(mat$animal))
bar<-foo[!is.na(mat$animal)]
print(mat,
sanitize.text.function = function(x){x},
floating=FALSE,
include.rownames=FALSE,
hline.after=NULL,
add.to.row=list(pos=list(-1,bar,nrow(mat)),
command=c("\\toprule ", "\\midrule ", "\\bottomrule ")))
#could extend this with \cmidrule to have a partial line over
#a sub category column and \addlinespace to add space before a total row
@
```

Another R package for aggregating multiple regression models into LaTeX tables is texreg.