Talk:Ladle/Statistics

Instructions for generating plots for 'Individual stats'
1. Install R and Rstudio (http://cran.rstudio.com/bin/windows/base/R-3.0.2-win.exe, http://download1.rstudio.org/RStudio-0.98.501.exe)

2. From within Rstudio install these packages: ggplot2, Cairo

3. Create a new "R script" and copy the code below (with updated ladle data)

require(ggplot2) require(scales) require(Cairo) data <- list(      dread       =c(22,37,39,42,48,51,54,55,56,61,65,66,69,73,74,76,78),       fofo        =c(12,13,15,27,29,30,31,36,46,48,50,52,57,58,75),       hoax        =c(12,13,15,22,23,28,44,45,50,55,56,61,75),       xyron       =c(21,24,27,32,33,37,39,40,42,50,55,56,61),       lacka       =c(03,09,11,14,18,34,35,38,43,60,63,64),       flex        =c(12,13,15,18,19,26,29,30,31,36,50,52),       woned       =c(16,20,25,32,37,39,40,42,53,71,72),       eckz        =c(41,49,51,54,57,58,59,62,65,66),       dlh         =c(06,09,18,19,33,34,35,55,56,61),       durka       =c(08,10,14,17,22,23,28,44,45,61),       newb        =c(01,04,06,09,11,21,24,33,34,35),       olive       =c(21,24,27,33,38,43,55,56,61,78),       gonzap      =c(20,32,37,39,40,42,53,71,72),       b3er        =c(25,32,37,39,40,42,53,71,72),       freako      =c(14,17,21,24,27,34,41,55,56),       mazuff      =c(04,06,09,11,18,19,33,34,48), vov        =c(57,65,66,69,73,74,76,78), gazelle    =c(53,62,68,69,73,74,76,77), viper      =c(07,24,27,29,30,31,36,46), emmy       =c(16,20,25,32,37,39,40,42), titan      =c(33,38,43,46,60,63,70), soul       =c(65,66,69,73,74,76,78), wap        =c(37,40,42,53,71,72), poke       =c(38,43,60,63,64,70), psyko      =c(07,11,26,29,30,36), kult       =c(73,74,76,78), over       =c(63,64,70,71), orion      =c(36,78), jdawg      =c(71,72), fippmam    =c(62,67), magi       =c(67) )    plot_ladle_wins <- function(at_least=5) {       df <- data.frame(p=rep(paste(names(data)," (",sapply(data,length),")",sep=""),times=sapply(data,length)), l=unlist(data,use.names=F), c=unlist(sapply(data,function(x)(1:length(x))),use.names=F), m=unlist(sapply(data,function(x)(rep(length(x),length(x)))),use.names=F))      dfup <- df[df$m >= at_least,]       bre <- unique(c(seq(from=1,to=max(dfup$c),by=4),max(dfup$c)))       ggplot(dfup) + geom_point(aes(x=l,y=reorder(p,l),size=c,colour=c),shape=9) +          scale_colour_gradient('wins', guide="legend", breaks=bre) +         scale_size_area('wins',breaks=bre) +          theme(axis.title.y=element_blank,axis.ticks.x=element_blank,axis.ticks.y=element_blank) +          scale_x_continuous(breaks=c(1,seq(from=12,to=max(dfup$l),by=12)),minor_breaks=seq(from=1,to=max(dfup$l), by=1)) +          xlab(paste("Ladle trophies (",at_least,"+) sorted by players' activity\n", "(updated ", format(Sys.time, "%Y/%m/%d"),")",sep=""))}     plot_ladle_dominance <- function (last_ladle=(max(unlist(data,use.names=F))), months_ago=18, at_least=3) {       data2 <- lapply(data,function(a)(a[a>(last_ladle-months_ago) & a<=last_ladle])) data2 <- data2[sapply(data2,length)>0] df2 <- data.frame(p=rep(paste(names(data2)," (",sapply(data2,length),")",sep=""),times=sapply(data2,length)),                        l=unlist(data2,use.names=F),                         c=unlist(sapply(data2,function(x)(1:length(x))),use.names=F),                         m=unlist(sapply(data2,function(x)(rep(length(x),length(x)))),use.names=F)) df2up <- df2[df2$m >= at_least,] ggplot(df2up) + geom_point(aes(x=l,y=reorder(p,c),size=c,color=c),shape=21,fill="Black") + scale_x_continuous(breaks = seq(from = min(df2up$l), to = max(df2up$l), by = 1)) + theme(axis.title.y=element_blank,panel.grid.minor=element_blank,axis.ticks.x=element_blank,axis.ticks.y=element_blank,legend.position="none") + coord_fixed(1) + xlab(paste("Ladle dominance (",at_least,"+) in the last ",months_ago," months since L",last_ladle,"\n", "(updated ", format(Sys.time, "%Y/%m/%d"),")",sep=""))} ### SAVE PLOTS ggsave("ladle_wins.png", plot_ladle_wins, width=14, height=7, dpi=72, type="cairo-png") ggsave("ladle_dominance.png", plot_ladle_dominance, width=14, height= 3.5, dpi=72, type="cairo-png")

3. Run the script. Two png plots will be saved