set up maximum value for histogram y axis

[tjcnnl1]

these are the code segments, because I don't know how to upload data, so no data provided.
code1:
ggplot(overall_hist,aes(x=Rate, y=..count..)) +
geom_histogram(bins=50, fill="steelblue", color="white") +
geom_vline(aes(xintercept = ref), linetype="dashed", size=1.0) +
xlim(30,50) + ylim(0,50)

code2:
ggplot(strata_hist,aes(x=Rate, y=..count..)) +
geom_histogram(bins=50, fill="steelblue", color="white") +
xlim(30,50) + ylim(0,50) +
geom_vline(aes(xintercept = Rate), strata_ref, linetype="dashed", size=1.0) +
facet_wrap(~Strata, scales="free_y")

My questions are

1. in general , how to set up maximum value for histogram y axis based on data
2. to generate histograms by above codes, the code1 and code2 syntax are similar.
   Because the data structure is different, the first 2 lines of ggplot statements
   are the same, the 3rd and 4th lines are different. Is it possible to generate a function and based on
   same flag to perform the function differently? Pseudo-code like such

draw_hist <- function(ds,flag){
ggplot(ds,aes(x=Rate, y=..count..)) +
geom_histogram(bins=50, fill="steelblue", color="white") +
xlim(30,50) + ylim(0,50) +
if flag=='O'{
geom_vline(aes(xintercept = ref), linetype="dashed", size=1.0)
}else{
geom_vline(aes(xintercept = Rate), strata_ref, linetype="dashed", size=1.0) +
facet_wrap(~Strata, scales="free_y")

to use the function like such:
draw_hist(overall_hist, 'O')
draw_hist(strata_hist, 'S')

output from code1

output from code2

[mara]

@tjcnnl1

these are the code segments, because I don't know how to upload data, so no data provided.
code1:

You can include an excerpt of your data using dput(), or (my personal favorite option) datapasta.

I did a little write-up on the latter a couple years ago here:

reprex-ing with {datapasta} 🍝

With that done, you'll be able to turn this into a proper reprex (short for reproducible example).

install.packages("reprex")

If you've never heard of a reprex before, you might want to start by reading the tidyverse.org help page. The reprex dos and don'ts are also useful.

There's also a nice FAQ on how to do a minimal reprex for beginners, below:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

What to do if you run into clipboard problems

If you run into problems with access to your clipboard, you can specify an outfile for the reprex, and then copy and paste the contents into the forum.

reprex::reprex(input = "fruits_stringdist.R", outfile = "fruits_stringdist.md")

For pointers specific to the community site, check out the reprex FAQ.