Help with geom_sankey_label() error: “object 'next_x' not found” despite correct structure

General
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1

Hi community,

I'm trying to create a Sankey diagram using the {ggsankey} package to replicate a 10-step semaglutide dose titration pattern as seen in a published paper. I’ve carefully followed all steps and verified that my dataset has the required structure.

Here’s a minimal summary of what I’ve done:

  1. Created rx_long_clean using make_long()
  2. Confirmed it has all four columns: x, node, next_x, next_node
names(rx_long_clean)
#> [1] "x" "node" "next_x" "next_node"
  1. Created a label_data object using:

label_data <- rx_long_clean %>%
group_by(x, node) %>%
summarise(n = n(), .groups = "drop") %>%
mutate(
perc = round(n / sum(n) * 100, 1),
label = paste0(perc, "%"),
x = factor(x, levels = paste0("Rx", 1:10)),
node = factor(node, levels = dose_levels)
)


4. But when I try to run `geom_sankey_label()`:

geom_sankey_label(data = label_data, aes(x = x, node = node, label = label))

I get the error:

Error in geom_sankey_label():
Problem while computing aesthetics.
Caused by error in mutate() -> in across():
Can't subset columns that don't exist.
Column next_x doesn't exist.


5. I **triple-checked** that `label_data` does not need `next_x`, as I’m only mapping `x`, `node`, and `label`.

---

### ❓ What I’ve Tried:

* Verified column names and types
* Ensured both `rx_long_clean` and `label_data` are correctly grouped/factored
* Ignoring the warning `"Ignoring unknown aesthetics: node"` in output still throws error

---

### 🙏 Help Needed:

Is there an internal expectation inside `geom_sankey_label()` for `next_x`, even when it’s not mapped? Or is there another workaround to use labels safely with 10-step Sankey transitions?

Happy to provide a reproducible example if needed!

Thanks so much!
2

Probably a reprex and some sample data would help. I don't see anything wrong but I seldom use {dplyr}

A handy way to supply data is to use the dput() function. Do dput(mydata) where "mydata" is the name of your dataset. For really large datasets probably dput(head(mydata, 100). Paste it here between

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