In my field of research (HEP), the vertical errors for the histograms are widely used.

Usually, they are calculated assuming narrow bins and Poisson distribution for the number of entries,

i.e. the error is `sqrt(Nentries)`

It is clear how to extend `Plots.scatterbins`

for such errors.

While, it gets more complicated (implementation-wise) when the

- data are weighted
- histogram is normalized

Plots use `StatsBase.Histogram`

that does not give access to the entries weights inside of individual bins. This information seems to be lost once `Histogram`

is created.

Any ideas on the problem?

Here is my `errorhist`

recipe for the Poisson error.

```
@recipe function f(::Type{Val{:errorhist}}, x, y, z)
h = Plots._make_hist(
(y,),
plotattributes[:bins],
normed = plotattributes[:normalize],
weights = plotattributes[:weights],
)
x := h.edges[1]
y := h.weights
seriestype := :scatterbins
#
@series begin
primary := false
seriestype := :yerror
x := Plots._bin_centers(h.edges[1])
yerror --> map(x->x < 0 ? 0.0 : sqrt(x), h.weights)
end
()
end
@shorthands errorhist
```