Chord diagram is an efficient way to display flows between entities. This post shows how to build a customized version using the circlize package.
The circlize package
developped by
Zuguang Gu is the best way
to build chord diagram in R. The
chord diagram section of the gallery provides a step by step
introduction to it.
This example explains how to build a highly customized chord
diagram, adding links manually thanks to the
circos.link()
function.
Note that the library also offers a
chordDiagram()
functions that builds everything
automatically, but offers less customization. (See it
here.)
Important: This example has been found on stackoverflow, made by Jazzuro.
### You need several libraries
library(circlize)
library(migest)
library(dplyr)
### Make data
m <- data.frame(order = 1:6,
country = c("Ausralia", "India", "China", "Japan", "Thailand", "Malaysia"),
V3 = c(1, 150000, 90000, 180000, 15000, 10000),
V4 = c(35000, 1, 10000, 12000, 25000, 8000),
V5 = c(10000, 7000, 1, 40000, 5000, 4000),
V6 = c(7000, 8000, 175000, 1, 11000, 18000),
V7 = c(70000, 30000, 22000, 120000, 1, 40000),
V8 = c(60000, 90000, 110000, 14000, 30000, 1),
r = c(255,255,255,153,51,51),
g = c(51, 153, 255, 255, 255, 255),
b = c(51, 51, 51, 51, 51, 153),
stringsAsFactors = FALSE)
df1 <- m[, c(1,2, 9:11)]
m <- m[,-(1:2)]/1e04
m <- as.matrix(m[,c(1:6)])
dimnames(m) <- list(orig = df1$country, dest = df1$country)
#Sort order of data.frame and matrix for plotting in circos
df1 <- arrange(df1, order)
df1$country <- factor(df1$country, levels = df1$country)
m <- m[levels(df1$country),levels(df1$country)]
### Define ranges of circos sectors and their colors (both of the sectors and the links)
df1$xmin <- 0
df1$xmax <- rowSums(m) + colSums(m)
n <- nrow(df1)
df1$rcol<-rgb(df1$r, df1$g, df1$b, max = 255)
df1$lcol<-rgb(df1$r, df1$g, df1$b, alpha=200, max = 255)
### Plot sectors (outer part)
par(mar=rep(0,4))
circos.clear()
### Basic circos graphic parameters
circos.par(cell.padding=c(0,0,0,0), track.margin=c(0,0.15), start.degree = 90, gap.degree =4)
### Sector details
circos.initialize(factors = df1$country, xlim = cbind(df1$xmin, df1$xmax))
### Plot sectors
circos.trackPlotRegion(ylim = c(0, 1), factors = df1$country, track.height=0.1,
#panel.fun for each sector
panel.fun = function(x, y) {
#select details of current sector
name = get.cell.meta.data("sector.index")
i = get.cell.meta.data("sector.numeric.index")
xlim = get.cell.meta.data("xlim")
ylim = get.cell.meta.data("ylim")
#text direction (dd) and adjusmtents (aa)
theta = circlize(mean(xlim), 1.3)[1, 1] %% 360
dd <- ifelse(theta < 90 || theta > 270, "clockwise", "reverse.clockwise")
aa = c(1, 0.5)
if(theta < 90 || theta > 270) aa = c(0, 0.5)
#plot country labels
circos.text(x=mean(xlim), y=1.7, labels=name, facing = dd, cex=0.6, adj = aa)
#plot main sector
circos.rect(xleft=xlim[1], ybottom=ylim[1], xright=xlim[2], ytop=ylim[2],
col = df1$rcol[i], border=df1$rcol[i])
#blank in part of main sector
circos.rect(xleft=xlim[1], ybottom=ylim[1], xright=xlim[2]-rowSums(m)[i], ytop=ylim[1]+0.3,
col = "white", border = "white")
#white line all the way around
circos.rect(xleft=xlim[1], ybottom=0.3, xright=xlim[2], ytop=0.32, col = "white", border = "white")
#plot axis
circos.axis(labels.cex=0.6, direction = "outside", major.at=seq(from=0,to=floor(df1$xmax)[i],by=5),
minor.ticks=1, labels.away.percentage = 0.15)
})
### Plot links (inner part)
### Add sum values to df1, marking the x-position of the first links
### out (sum1) and in (sum2). Updated for further links in loop below.
df1$sum1 <- colSums(m)
df1$sum2 <- numeric(n)
### Create a data.frame of the flow matrix sorted by flow size, to allow largest flow plotted first
df2 <- cbind(as.data.frame(m),orig=rownames(m), stringsAsFactors=FALSE)
df2 <- reshape(df2, idvar="orig", varying=list(1:n), direction="long",
timevar="dest", time=rownames(m), v.names = "m")
df2 <- arrange(df2,desc(m))
### Keep only the largest flows to avoid clutter
df2 <- subset(df2, m > quantile(m,0.6))
### Plot links
for(k in 1:nrow(df2)){
#i,j reference of flow matrix
i<-match(df2$orig[k],df1$country)
j<-match(df2$dest[k],df1$country)
#plot link
circos.link(sector.index1=df1$country[i], point1=c(df1$sum1[i], df1$sum1[i] + abs(m[i, j])),
sector.index2=df1$country[j], point2=c(df1$sum2[j], df1$sum2[j] + abs(m[i, j])),
col = df1$lcol[i])
#update sum1 and sum2 for use when plotting the next link
df1$sum1[i] = df1$sum1[i] + abs(m[i, j])
df1$sum2[j] = df1$sum2[j] + abs(m[i, j])
}
👋 After crafting hundreds of R charts over 12 years, I've distilled my top 10 tips and tricks. Receive them via email! One insight per day for the next 10 days! 🔥