I would like to leave an alternative way to visualize this data. You can visualize how people moved or traveled by using the circlize and migest packages in R. You gotta do lots of coding, but it is still possible to create something you want if you follow demos in migest. You need a matrix and a data frame to draw this figure. But, once you have them right you can use codes from the demos. In this example, you see how people from 6 countries traveled. For example, Aussies visited Japan, Malaysia, and India in this fake data; three red lines reaching those countries. If lines are wider, that means more people visited these countries. Likewise, Chinese visited Australia, Japan, and Malaysia. I leave my codes here.
library(circlize)
library(migest)
library(dplyr)
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)
### Create a data frame
df1 <- m[, c(1,2, 9:11)]
### Create a matrix
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])
}
