History: Profile_r_test13_parse_body

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            ! Unfinished work. Alfa state.

This page first of all produces a simple barchart using conventional R body content ie with

!!- Fetch data using TrackerList to fetch data
__Wiki a wiki template__
{trackerlist trackerId=2 fields="9:10:11" list_mode=csv max=4 showpagination="n" tplwiki=r_demo13_template01}

__Without a wiki template, and with param list_mode=csv__
{trackerlist trackerId=2 fields="9:10:11" list_mode=csv max=4 showpagination="n"}

__With a wiki template, and without param list_mode=csv__
{trackerlist trackerId=2 fields="9:10:11" max=4 showpagination="n" tplwiki=r_demo13_template01}

So now that you can generate output from a tracker using a trackerlist plugin, or for more flexibility using the list plugin, then a lot more options become possible with R   :-)

However, it doesn't work as of July 2015 (Tiki12). See bug report related to param list_mode=csv
"plugin trackerlist param list_mode=csv does nothing for me" - https://dev.tiki.org/item5688

!!- Display dummy data using a Barplot
{R(bg="yellow" parse_body="y" echodebug=1)}
abundance <- matrix(c({trackerlist trackerId=2 fields="9:10:11" list_mode=csv max=4 showpagination="n" tplwiki=r_demo13_template01}),ncol=3,byrow=TRUE);
abundance;
barplot(abundance);
{R}
In the above the echodebug now shows the body content both pre and post parsing so that it can be checked.


!! Fetch data using ajax services and display using sjPlot
{RR(bg="yellow" parse_body="n" echodebug=1)}
r <- getOption("repos")
r["CRAN"] <- "http://ftp.heanet.ie/mirrors/cran.r-project.org/"
options(repos=r)
install.packages("sjPlot")
library("sjPlot")


### EXAMPLE with pre-set data frame by hand
marca<-c("opel","renault","renault")
model<-c("corsa","laguna","modus")
cilindrada<-c(1.2,1.9,1.5)
color<-c("blanc","vermell","violeta")
cotxes<-data.frame(marca,model,cilindrada,color)
cotxes

### FETCH tracker data __using Ajax services__
Use some url such as:
^ http://localhost/tiki-ajax_services.php?controller=tracker&action=export_items&trackerId=2&encoding=UTF-8&separator=%2C&delimitorL=%22&delimitorR=%22&CR=%25%25%25&listfields[]=9&listfields[]=10&listfields[]=11&recordsMax=-1
^

# If your tiki is not under localhost, adapt the path below for my.file
my.file <- "http://localhost/tiki-ajax_services.php?controller=tracker&action=export_items&trackerId=2&encoding=UTF-8&separator=%2C&delimitorL=%22&delimitorR=%22&CR=%25%25%25&listfields[]=9&listfields[]=10&listfields[]=11&recordsMax=-1"
my.df <- read.csv(my.file)
#colnames(my.df) <- c("f_9", "f_10", "f_11")
unlist(str_split(colnames(my.df), "\\."))[1]
str_split(colnames(my.df), "\\.")[[1]][1] # field name from f_9 in this example
str_split(colnames(my.df), "\\.")[[2]][1] # field name from f_10 in this example
str_split(colnames(my.df), "\\.")[[3]][1] # field name from f_11 in this example

# load libraries
library(sjPlot)
library(sjmisc)
# init default theme for plots
sjp.setTheme(geom.label.size = 2.5, axis.title.size = .9, axis.textsize = .9)
sjp.frq(cotxes$marca)
sjp.frq(cotxes[,1])

sjp.frq(my.df[,1])
{RR}

See:
* https://strengejacke.wordpress.com/2013/07/17/plotting-likert-scales-net-stacked-distributions-with-ggplot-rstats/
* http://strengejacke.de/sjPlot/custplot/