sparkTable (version 0.1.3)

sparkTable_Config: Create meta objects which are later to be used as input-objects for the plot-function.

Description

Generation of a meta-object which can be used by the print.sparkTable-function. Tis object also contains the properties of the plots.

Usage

sparkTable_Config(df, groups, groupVar, vars, typeNumeric, typePlot, output)

Arguments

df

a data.frame or matrix of input-data

groups

which characteristics of the grouping variable should be used

groupVar

variable name of a grouping-variable

vars

variable names of variables to be plotted

typeNumeric

list or vector of the same length as the number of variables used, each list element can be a vector or NULL,defines the number put into the table (see overview in details)

typePlot

vector or list either "line", "box" or "bar"

output

output format, currently "html" and "eps" are possible

Value

• Returns an object of class meta including $metaData and metaInfo
• metaData
  List of information and properties of every single graphic, for details look at the spark_init function
• metaInfo
  List of information about the output properties, chosen variables, plot type, groups. If the output is "eps" it contains filenames and the latex code. If the output is "html" it contains the html-header and the html-table

Details

typeNumeric can be:

max

min

mean

last

ind1--ind2 : e.g. 1--10 or 10--100

indexN: eg index1 gives the first value

... in principle every function that takes a vector and returns a single value (median, quantile,......)

See Also

print.sparkTable, setPara, sparkTable_Config, spark, spark_init, sparkHTML,, sparkEPS

Examples

# This function produces an artificial data set of N time units

genDF <- function(N) {
	groups <- c("AT","DE","CH","UK","IT")
	nrRows <- N*length(groups)
	df <- data.frame(
			time=rep(1:N, length(groups)), 
			groups=rep(groups, each=N),
			V1=round(rnorm(nrRows, 25, 25),2),
			V2=round(rnorm(nrRows, 125, 55),2),
			V3=round(rnorm(nrRows, 100, 15),2),
			V4=round(rnorm(nrRows, 150, 65),2),
			V5=round(rnorm(nrRows, 40, 85),2)
	)
	df
}

# generate a data.frame
df <- genDF(20)

# creating EPS output:

meta <- sparkTable_Config(df, groups=c("AT","UK"), 
		groupVar="groups", 
		vars=c("V1","V2","V5"), 
		typeNumeric="mean", 
		typePlot="box",
		output="eps")

# this meta object can now be used to generate an EPS-output in R
eps.text <- print(meta, outdir="examples")

# creating HTML file

meta <- sparkTable_Config(df, groups=c("AT","UK","IT"), 
		groupVar="groups", 
		vars=c("V1","V2","V5"), 
		typeNumeric=list(c("mean","1--3","max","4--5","last"),c("mean","1--3","max"),c("mean","1--3","max"))
		, 
		typePlot=list(c("line","box"),"line","line"),
		output="html")

obj <- print(meta,outdir="examples",outfile="test.html")

### production index
data(dat)
pi_jahr <- dat[1:4,]
pi_monat <- dat[6:nrow(dat),]
transform_for_meta <- function(x,time="row",vars=NULL){
  if(time!="row"){
    x <- t(x)                
  }
  if(!is.null(vars)){
    x <- x[,vars]    
  }
  gr <- vector()
  val <- vector()
  for(i in 1:ncol(x)){
    gr <- c(gr,rep(names(x)[i],nrow(x)))
    val <- c(val,x[,i]) 
  }
  data.frame(group=gr,values=val,stringsAsFactors=FALSE)
}
pi_j2 <- transform_for_meta(pi_jahr)
pi_m2 <- transform_for_meta(pi_monat)
j <- vector()
for(i in 6:20){
  j <- c(j,paste(rep(1990+i,12),1:12,sep="-"))
}
pi_m2$values2 <- pi_m2$values
meta <- sparkTable_Config(df=pi_m2,groups=unique(pi_m2[,1]),groupVar=names(pi_m2)[1],
    vars=names(pi_m2)[2:3], 
    typeNumeric=list(NA,c("51--62"))
    , 
    typePlot=list("line",NA),
    output="html")
meta$metaData <- setPara(meta$metaData, "ch", 25,col=1)
obj <- print(meta,outfile="test.html",outdir="examples")