gistfile1.r

library(xts)

df = read.csv("Ceny_anonym.csv",sep = ";")
colnames(df) = c('phone','pmax','pmin','pmid','datetime')
df$datetime = as.POSIXct(df$datetime,format="%d.%m.%Y %H:%M")
df$dtl = as.POSIXlt(df$datetime)
df$mno = ((df$dtl$year+1900-2008)*12)+df$dtl$mon

my_norm2 = function(df,name,start) {
  idxs = which(df$phone==name)
  df2 = df[idxs,]
  xdf = xts(df2$pmid, order.by=df2$datetime)
  colnames(xdf) = name
  diff = index(xdf)[[1]] - start
  index(xdf) = index(xdf) - diff
  base = max(xdf) / 100
  xdf / base
}

start = min(df$datetime)

names = unique(df$phone)
xdfs = Map(function(x){my_norm2(df,x,start)},names)
xdf = do.call(merge,xdfs)

mean_fun = function(x) apply(x, 2, function(x) mean(x,na.rm=TRUE))
xdfm = period.apply(xdf, endpoints(xdf, "months"), FUN=mean_fun)

plot.xts(xdfm, screens=1)

plot(time(xdfm),xdfm$Telefon.Ilona,type="l",col="blue",ylim=c(0,100))
lines(time(xdfm),xdfm$Telefon.Ilja,col="red")
lines(time(xdfm),xdfm$Telefon.Michal,col="green")
lines(time(xdfm),xdfm$Telefon.Kvido,col="yellow")