plot - How can I remove spacing in Pie charts in multi panel and have only one legend at the top using r -

the pie charts:

the link data: https://drive.google.com/file/d/0bwopt0jygdzorkm3cva0wjjodvk/view?usp=sharing

mydata<-read.csv(file="final_analysis_candy_analysis.csv",head=true,sep=",")  dhfr.arg <- table(mydata$dhfr.arg.59.163.137.)     dhfr.ile <- table(mydata$dhfr.ile.51.214.65.)     dhfr.asn108 <- table(mydata$dhfr.asn108.328.372.) glu.540 <- table(mydata$glu.540.538.326.200.)     gly.437 <- table(mydata$gly.437.848.300.)  library(plotrix)  par(op) op <-par(mfrow=c(2,3),mar=c(0,0,1,0))    pct <- round(dhfr.arg/sum(dhfr.arg)*100) lbls <- paste(names(dhfr.arg), pct) # add percents labels     lbls <- paste(lbls,"%",sep="") # ad % labels     lp<-pie3d(dhfr.arg,radius=0.8,labels=lbls,explode=0.1, labelrad=1.4,main="dhfr arg 59(163,137)")     pct <- round(dhfr.ile/sum(dhfr.ile)*100)     lbls <- paste(names(dhfr.ile), pct) # add percents labels     lbls <- paste(lbls,"%",sep="") # ad % labels lp<-pie3d(dhfr.ile,radius=0.8,labels=lbls,explode=0.1,   labelrad=1.4,main="dhfr ile 51(214,65)")     pct <- round(dhfr.asn108/sum(dhfr.asn108)*100)     lbls <- paste(names(dhfr.asn108), pct) # add percents labels     lbls <- paste(lbls,"%",sep="") # ad % labels     lp <- pie3d(dhfr.asn108,radius=0.8,labels=lbls,explode=0.1,   labelrad=1.4,main="dhfr asn108(328,372)") pct <- round(glu.540/sum(glu.540)*100)     lbls <- paste(names(glu.540), pct) # add percents labels    lbls <- paste(lbls,"%",sep="") # ad % labels     lp<-pie3d(glu.540,radius=0.8,labels=lbls,explode=0.1,   labelrad=1.4,main="glu 540(538,326,200)")     pct <- round(gly.437/sum(gly.437)*100)    lbls <- paste(names(gly.437), pct) # add percents labels     lbls <- paste(lbls,"%",sep="") # ad % labels lp <- pie3d(gly.437,radius=0.8,labels=lbls,explode=0.1,   labelrad=1.4,main="gly 437(848,300)") par(op) 

using 2d visualization plot easier comprehend. therefore, alternative 2d solution ggplot:

# load needed packages library(data.table) library(ggplot2) library(scales)  # process & summarise data (with data.table) mydat <- melt(setdt(mydata),               id=1,               measure.vars=4:8)[, .n, = .(variable,value)                                 ][, `:=` (perc = round(n/sum(n),2),                                           pos = cumsum(n)-0.5*n), = variable]  # create plot ggplot2 & scales ggplot(mydat) +   geom_bar(stat="identity", aes(x="", y=n, fill=value)) +   geom_text(aes(x = "", y = pos, label = percent(perc))) +   scale_x_discrete(expand = c(0,0)) +   scale_y_continuous(expand = c(0,0)) +   coord_polar(theta = "y") +   facet_grid(.~ variable, scales = "free") +   theme_minimal(base_size = 16) +   theme(axis.title = element_blank(), axis.text = element_blank(),         panel.grid = element_blank(), legend.title = element_blank()) 

which gives following plot:

see this answer how calculate pos variable base r or plyr , dplyr packages.

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however, pie-charts not best way visualize data. in case bart chart result in clearer visualization. with:

ggplot(mydat, aes(x=variable, y=perc, fill=value)) +   geom_bar(stat="identity", aes(label = percent(perc)), width=0.6) +   scale_y_continuous(labels = percent(c(0,0.25,0.50,0.75,1.00))) +   coord_flip() +   theme_minimal(base_size = 14) +   theme(axis.title = element_blank(), legend.title = element_blank()) 

you get: