I'm trying to produce a stacked barplot with an error bar which represents the total variability per bar. I don't want to use a dodged barplot as I have >10 categories per bar.

Below I have some sample data for a reproducible example:

```
scenario = c('A','A','A','A')
strategy = c('A','A','A','A')
decile = c(0,0,10,10)
asset = c('A','B','A','B')
lower = c(10,20,10, 15)
mean = c(30,50,60, 70)
upper = c(70,90,86,90)
data = data.frame(scenario, strategy, decile, asset, lower, mean, upper)

```

And once we have the `data` df we can use ggplot2 to create a stacked bar as so:

```
ggplot(wide, aes(x=decile, y=mean, fill=asset)) + 
  geom_bar(stat="identity") +
  facet_grid(strategy~scenario) +
  geom_errorbar(aes(ymin = lower, ymax = upper), width = 0.25)

```

However, the error bars produced are for each individual component of each stacked bar:

[![enter image description here](https://i.stack.imgur.com/02fJm.png)](https://i.stack.imgur.com/02fJm.png)

I appreciate this results from me providing the `lower`, `mean` and `upper` for each row of the df, but even when I summed these per decile I didn't get my desired errorbars at the top of each bar stack.

What is the correct ggplot2 code, or alternatively, what is the correct data structure to enable this?