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~ Function: R to HTML, Univariate analysis ~
r2latexUniv (r2lu in short) performs some basic analyses, then generates
code to be included in a LaTeX document to print the analyses in a (so
nice!) LaTeX way.
r2lu(x,fileOut="",textBefore="",textAfter="",graphDir="graphUniv",graphName="V",type="png",limDiscrete=10) r2latexUniv(x,fileOut="",textBefore="",textAfter="",graphDir="graphUniv",graphName="V",type="png",limDiscrete=10)[data.frame] or [vector] : contains the
data to analyse.[character];
name of the output file in which
the LaTeX summary will be saved. If empty, the code is printed on screen.[character] or [vector(character)] : before
printing a variable analysis, some text can be inserted. If
(r2lu is applied on a single variable,
textBefore should be of length 1. If the function is applied on a data.frame,
textBefore can have same length as the number of columns of
the data.frame (this lets
the user write a specific introduction for each variable), or can be
of length 1. In this case, it is printed before each variable
analysis. See examples for details.[character] or [vector(character)] : after
printing a variable analysis, some text can be added. See
textBefore and examples for details.[character] :
directory used to save the graphs generated by the analyses.[character] or [vector(character)] :
prefix for the graph names. If empty, the graph names are
V1 to V length(data.frame)[character] : type of plotting device used to export the
graphics. Can be Windows metafile, PNG, JPEG, BMP (Windows bitmap format), TIFF,
PostScript or PDF.r2lu distinguish two kinds of numeric :
discrete designates numeric variables with only a few
modalities, continuous designates numeric variables with many
modalities. The limit between 'few' and 'many' can be fixed by the
user via the limDiscrete argument. By setting
limDiscrete to 5, the user will ask r2lu to consider
all the numeric variables with 5 modalities or more as
continuous and all the variables with less than 5 modalities
as discrete. The default value for limDiscrete is 10.
r2lu generate LaTeX code and either print it on the screen, or save it in a
file. It also generate several graphs, optionally in a different directory.
r2lu goes through the following steps:
| Step 1. |
Load the data (usually, a data.frame). |
| Step 2. |
Optionally, set some variables as ordered. |
| Step 3. |
Run r2lu(dataFrame,"fileOut.tex"). |
r2lu performs some basic analyses, then generates a
code to be included in a LaTeX document to print the analyses in a (so
nice!) LaTeX way. r2lu performs the analyses automatically according to the
data class. They consider four classes. The analysis of the
variable depends on the class:
On a data.frame, r2lu runs the analyses on every column.
See /library/r2lh/doc/r2lhOutput.pdf for display details.
r2lMainFile,
r2latexBiv,
r2latexUniv-package,
examCheating,
Sweave,
latex
# # # # # # # # # # # # # # # # # # #
# R to LaTeX, Univariate Analyses #
# Artificial examples #
# Single variable #
# # # # # # # # # # # # # # # # #
### Create some data
V1 <- factor(LETTERS[floor(runif(50,1,4))])
V2 <- rnorm(50,1,1)<0
V3 <- ordered(LETTERS[floor(runif(50,1,4))])
### Create a directory for the output
if(!file.exists("tmp/r2luExample",recursive=TRUE)){dir.create("tmp/r2luExample",recursive=TRUE)}else{}
setwd("tmp/r2luExample")
### Execute r2lu
r2lu(V1,fileOut="first.tex",textBefore="\\section{Variable 1 to 3}",graphName="V1")
r2lu(V2,fileOut="second.tex",graphName="V2")
r2lu(V3,fileOut="third.tex",textBefore="This is variable 3",graphDir="P")
r2lMainFile(text="\\input{first.tex}\n\\input{second.tex}\n\\input{third.tex}")
# # # # # # # # # # # # # # # # # # #
# R to LaTeX, Univariate Analyses #
# Real examples #
# r2lu data.frame #
# # # # # # # # # # # # # # # # #
########################
###### Step 1: Create the data
data(examCheating)
str(examCheating)
########################
###### Step 2: ordering variable
examCheating$YearOfStudy <- ordered(examCheating$YearOfStudy,levels=c("L1","L2","L3","M1","M2"))
examCheating$Bac <- ordered(examCheating$Bac,levels=c("Remedial exam","Pass","Fairly good","Good","Very good","Summa cum laude"))
for(iColumn in 8:17){
examCheating[,iColumn] <- ordered(examCheating[,iColumn],levels=c("Never","Rarely","Sometimes","Often","Always"))
}
str(examCheating)
########################
###### Step 3: running r2lu
### Preparation of textBefore, for transition between variables
textBefore <- paste("\\subsection{",names(examCheating)[c(2:5,18:20)],"}",sep="")
text <- "\\maketitle
\\tableofcontents
\\section{Survey}
\\begin{enumerate}
\\item What is your age?
\\item What is your gender?
\\item What is your level?
\\item What is your field?
\\item Did you cheat at Bac?
\\item Did you cheat high scool?
\\item Cheating score
\\end{enumerate}
\\section{Univariate analysis}
\\input{ExamCheat-univ.tex}
\\section{More information?}
For a detailled analysis, see
http://christophe.genolini.free.fr/EPO/2007 Fraude/EPO2007-Fraude-Rapport.pdf"
### We can run r2lu
r2lu(examCheating[,c(2:5,18:20)],fileOut="ExamCheat-univ.tex",textBefore=textBefore)
r2lMainFile("ExamCheat-main.tex",text=text)
setwd("../..")
### Then compile ExamCheat-main.tex twice. It is ready !
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