Building a career path in a graph

Question

I have a dataframe

test <- structure(list( y2002 = c("freshman","freshman","freshman","sophomore","sophomore","senior"), y2003 = c("freshman","junior","junior","sophomore","sophomore","senior"), y2004 = c("junior","sophomore","sophomore","senior","senior",NA), y2005 = c("senior","senior","senior",NA, NA, NA)), .Names = c("2002","2003","2004","2005"), row.names = c(c(1:6)), class = "data.frame") > test 2002 2003 2004 2005 1 freshman freshman junior senior 2 freshman junior sophomore senior 3 freshman junior sophomore senior 4 sophomore sophomore senior <NA> 5 sophomore sophomore senior <NA> 6 senior senior <NA> <NA> 

and I want to create a graph that should resemble the ugly text art below:

 freshman ---- junior ----------------------\ freshman ---- junior --- sophomore -------- senior sophomore ================================/ senior ---------------------------------/ 

In other words, I need to show on the graph the possible paths to the "senior", giving the weights to the ribs in accordance with the number of cases using this path.

First attempt This code generates a graph, but not one that is similar to the text above.

 library(igraph) elist <- lapply(seq_len(nrow(test)), function(i) { x <- as.character(test[i,]) x <- unique(na.omit(x)) x <- rep(x, each=2) x <- x[-1] x <- x[-length(x)] r <- matrix(x, ncol=2, byrow=TRUE) if (nrow(r) > 0) { r <- cbind(r, i) } else { r <- cbind(r, numeric()) } r }) result <- as.data.frame(do.call(rbind, elist)) names(result) <- c("vertex","edge", "id") categories <- data.frame(name=c("freshman","junior","sophomore","senior")) g <- graph.data.frame(result,directed=T,vertices=categories) g <- set.edge.attribute(g, "weight", value=runif(ecount(g))*10) igraph.par("plot.layout", layout.reingold.tilford) plot(g, vertex.label=categories$name, vertex.label.dist=7, edge.width=get.edge.attribute(g,"weight"), edge.arrow.size=1.5) 

Result (not what I wanted)

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Answer 1

This is a fully developed solution. You need to read the graph from the bottom up, bearing in mind that each individual is represented by a vertical line representing their career path. Yes, I set iGraph for this task. \ O /

 require(reshape2) meltpath <- function(x){ require(data.table) x <- melt(data = x, id.vars = 'id', measure.vars = names(x)[-1]) names(x) <- c('id','year','category') x$year <- factor(x$year) id <- unique(x$id) idtable <- data.table(id = id, count = 1:length(id)) x <- x[order(x$id), ] x <- merge(x, idtable, by='id') return(x) } carpath <- function(datatable, max_x = max(datatable$count)){ require(ggplot2) p = ggplot(datatable, aes(x = count, y = year, fill = category)) + geom_tile() + scale_y_discrete(name = "year\n", breaks = rev(levels(datatable$year))) + scale_x_continuous(name = "cumulative count", limits = c(0,max_x)) + guides(fill = guide_legend(title="Career stage\n", reverse=TRUE)) + theme(panel.grid.major = element_blank(), panel.background = element_blank(), axis.ticks = element_blank(), plot.title = element_text(vjust = 1.2, face="bold", size=20), axis.title.y = element_text(size=15, face="bold"), axis.text.y = element_text(size=15, colour="black"), legend.title = element_text(size = 15), legend.text = element_text(size = 15)) + scale_fill_brewer(palette = "Dark2") + ggtitle("Career path of individual Students by year") p } test <- structure(list( id = 1:6, y2002 = c("freshman","freshman","freshman","sophomore","sophomore","senior"), y2003 = c("freshman","junior","sophomore","sophomore","sophomore","senior"), y2004 = c("junior","sophomore","sophomore","senior","senior",NA), y2005 = c("senior","senior","senior",NA, NA, NA)), .Names = c("id","2002","2003","2004","2005"), row.names = c(c(1:6)), class = "data.frame") # Grow dataset testg = data.frame() for (i in rownames(test)) { test0 <- test[rep(i, each=abs(floor(rnorm(1)*100))),] testg <- rbind(testg, test0) } testg$id <- 1:nrow(testg) # Munge test0 <- testg test1 <- melt(data = test0, id.vars = 'id', measure.vars = names(test0)[-1]) names(test1) <- c('id','year','category') test1$category[test1$category == 'freshman'] <- 1 test1$category[test1$category == 'junior'] <- 2 test1$category[test1$category == 'sophomore'] <- 3 test1$category[test1$category == 'senior'] <- 4 test1$category <- factor(test1$category, levels=1:4, labels = c('1. freshman','2. junior','3. sophomore','4. senior')) test1 <- test1[order(test1$category), ] test1 <- dcast(test1, id ~ year) test1 <- test1[order(test1$'2005',test1$'2004',test1$'2003',test1$'2002'), ] test2 <- meltpath(test1) carpath(test2) 

Answer 2

I don’t think you understand exactly what you have, in your example sketch sketch you have 8 nodes. But in the figure you created, you have only 4 nodes. This is due to the fact that you have only 4 nodes in the created chart. igraph will process nodes with the same name (for example, two sophomores as the same node, but with two edges)

However, once you have done a graph with a few minor nodes. e.g. sophomore1 and sophomore2. Then you can place the nodes where you want with layout , as shown below

  df<- read.table(text="vertex edge weight freshman junior 2 junior senior 2 freshman2 junior2 2 junior2 sophomore 2 sophomore senior 2 sophomore2 senior 3 senior2 senior 2",header=TRUE) categories <-data.frame(name=c("freshman","junior","sophomore","senior","freshman2", "junior2","sophomore2","senior2")) g <- graph.data.frame(df,directed=T,vertices=categories) layOUT<-data.frame(x=c(1,2,3,4,1,2,1,1),y=c(4,4,3,3,3,3,2,1)) l<-as.matrix(layOUT) plot(g,layout=l)