ggplot R Sankey diagram, alluvial?

Question

I'm trying to make a Sankey diagram in R using the alluvial package ( https://cran.r-project.org/web/packages/ggalluvial/vignettes/ggalluvial.html ). So far, I can replicate many of the examples that I've found. However, I'm specifically trying to replicate something that I haven't seen code for using the alluvial package.

Basically the dataset represents people arriving at a station (could be anything), some going onto next station, and some going missing (thus being truncated). In the alluvial package I can't figure out how to do this. I've attached a snapshot of what it should look like (made in http://sankeymatic.com/ ).

Should be fairly basic I imagine. One additional thing from the image I have shown is that I would like for the missing individuals bar to be a different colour at each node.

Could someone show me the code and code structure I would need for this?

Answer 1

You could try with package PantaRhei :

library(PantaRhei)
library(tibble)
library(grid)

# define node position

nodes <- 
  tribble(
~ID, ~label, ~x, ~y, ~label_pos,
"s1", "Station 1", "1", "0", "below",
"s2a", "Station 2: arrived", "2", "0.1", "above",
"s2m", "Station 2: missing", "2", "s1", "below",
"s3a", "Station 3: arrived", "3", "0.2", "above",
"s3m", "Station 3: missing", "3", "s2a", "below",
"s4a", "Station 4: arrived", "4", "0.3", "above",
"s4m", "Station 4: missing", "4", "s3a", "below",
"s5a", "Station 5: arrived", "5", "0.4", "above",
"s5m", "Station 5: missing", "5", "s4a", "below"
  )

# define size of flows

flows <-
  tribble(
    ~from, ~to, ~substance, ~quantity,
    "s1", "s2a", "a", 80,
    "s1", "s2m", "m", 20,
    "s2a", "s3a", "a", 60,
    "s2a", "s3m", "m", 20,
    "s3a", "s4a", "a", 35,
    "s3a", "s4m", "m", 25,
    "s4a", "s5a", "a", 15,
    "s4a", "s5m", "m", 20
    )

# define flow colours

colors <- tribble(
  ~substance, ~color,
  "a",    "green",
  "m",    "red"
)

# node formating

ns <- list(type = "bar", 
           gp=gpar(fill = "lightblue", col = "white", lwd = 1), 
           mag_pos = "inside",
           mag_fmt = "%.0f")

# final sankey image
sankey(nodes, flows, colors, node_style = ns)

Which gives you: