I am generating a lot of ftable()
crosstabulations for a descriptive report. Example:
AUS BEL BUL EST FRA GEO GER HUN ITA NET NOR ROM RUS
30- primary 0.06 0.03 0.07 0.03 0.02 0.03 0.03 0.02 0.05 0.03 0.05 0.04 0.02
secondary 0.30 0.09 0.16 0.10 0.10 0.14 0.10 0.16 0.11 0.08 0.08 0.09 0.11
tertiary 0.05 0.07 0.04 0.05 0.07 0.06 0.02 0.04 0.02 0.05 0.06 0.02 0.09
30+ primary 0.07 0.16 0.12 0.07 0.16 0.03 0.05 0.11 0.35 0.21 0.09 0.17 0.03
secondary 0.40 0.20 0.30 0.29 0.25 0.35 0.35 0.34 0.27 0.20 0.27 0.34 0.26
tertiary 0.13 0.23 0.13 0.18 0.17 0.17 0.18 0.09 0.09 0.23 0.23 0.06 0.24
60+ primary 0.00 0.12 0.10 0.13 0.14 0.07 0.05 0.12 0.09 0.11 0.06 0.19 0.12
secondary 0.00 0.05 0.05 0.08 0.06 0.10 0.14 0.09 0.02 0.04 0.11 0.07 0.06
tertiary 0.00 0.05 0.03 0.06 0.03 0.04 0.07 0.03 0.01 0.05 0.06 0.02 0.07
I am looking for a function that could take the ftable()
or table()
output, and highligh values that deviate from the row-mean, or assign an overall gradient to the text of the values, e.g. from 0-100% the values are coloured from red to green.
The output is now processed through knitr, but I'm not sure at which point in the toolchain I could intervene and add colour based on the relative size of the values.
You can use the latex
function, in the Hmisc
package.
# Example shamelessly copied from http://www.karlin.mff.cuni.cz/~kulich/vyuka/Rdoc/harrell-R-latex.pdf
cat('
\\documentclass{article}
\\usepackage[table]{xcolor}
\\begin{document}
<<results=tex>>=
library(Hmisc)
d <- head(iris)
cellTex <- matrix(rep("", nrow(d) * ncol(d)), nrow=nrow(d))
cellTex[2,2] <- "cellcolor{red}"
cellTex[2,3] <- "color{red}"
cellTex[5,1] <- "rowcolor{yellow}"
latex(d, file = "", cellTexCmds = cellTex, rowname=NULL)
@
\\end{document}',
file="tmp.Rnw" )
Sweave("tmp.Rnw")
library(utils)
texi2pdf("tmp.tex")
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