The `reduce2`

method I used here works reasonably well:

```
suppressPackageStartupMessages(library(tidyverse))
norm_curves <- tribble(
~Mean, ~SD,
5, 3,
10, 1,
16, 4
)
reduce2(.x = norm_curves$Mean,
.y = norm_curves$SD,
.init = ggplot(data = tibble(x = 0:17), aes(x)),
function(prev, .x, .y) {
prev + stat_function(fun = dnorm,
args = list(mean = .x,
sd = .y))
})
```

Edit: Oh, and because it was bugging me that color was potentially problematic with `reduce2`

:

```
suppressPackageStartupMessages(library(tidyverse))
norm_curves <- tribble(
~Group, ~Mean, ~SD,
"A", 5, 3,
"B", 10, 1,
"C", 16, 4
)
pmap(norm_curves,
function(Group, Mean, SD) {
stat_function(data = . %>% mutate(Group = Group),
aes(color = Group),
fun = dnorm,
args = list(mean = Mean,
sd = SD))
}) %>%
reduce(.init = ggplot(data = tibble(x = 0:17),
aes(x)),
`+`)
```