Want to add sd and mean to a facet wrap

[Brett1]

I'm relatively new to R and I'm a heck of a time figuring this out on my own. I used get symbols to get the last 5 years of a few stocks and now I'm trying to write a function that allows me view them with ggplot's facet_wrap by period and put that periods standard deviation and mean on each plot.

First I added the desired periods (terms) to the data like this:

start_dates <- c(st_date, (st_date + months(15) + days(1)), (st_date + months(30) + days(1)), (st_date + months(45) + days(1)))
end_dates <- c(st_date + months(15), st_date + months(30), st_date + months(45), st_date + months(60))

term <- function(date) {
cut(date,
breaks = ymd(st_date, end_dates),
labels = c("Months: 45-60", "Months: 30-45", "Months: 15-45", "Months: Today-15")
)
}

Then I took the raw data and pivoted it to a long format :

tail(Sector_Prices_long)

A tibble: 6 x 4

date assets prices term

1 2020-10-30 FB 263. Months: Today-15
2 2020-10-30 AMZN 3036. Months: Today-15
3 2020-10-30 NFLX 476. Months: Today-15
4 2020-10-30 GOOG 1621. Months: Today-15
5 2020-10-30 Sector_Value 1349. Months: Today-15
6 2020-10-30 Spy 327. Months: Today-15

which looks like that. and then I wrote a function that I hoped would accomplish my goal :

plot_4_ranges <- function(data, column, asset, stat, title) {
column <- rlang::enquo(column)
asset <- rlang::ensym(asset)
raw_num_eval <- data.frame(data %>%
filter(assets == asset) %>%
group_by(term) %>%
summarise(
sd = sd(prices),
mean = mean(prices),
count = length(prices)))
ungroup(raw_num_eval)

  stat = c("sd", "mean", "count")
  
  label_a <- plyr::mapvalues(stat, from = c("sd", "mean", "count"), to = c("(expression(sigma))", "(expression(mu))", "n"))
  
  raw_num_eval$join <- paste0(raw_num_eval$term, "\n(", label_a, " = ",
                              round(raw_num_eval[[stat]], 4), ")")
  
  raw_map <- setNames(raw_num_eval$join, as.factor(raw_num_eval$term))
  return(raw_map[as.character(data[[asset]])])

  plot1 <-
  data %>% 
  dplyr::filter(!!column == asset) %>% 
  ggplot(aes(prices)) +
  geom_histogram(aes(y = stat(count))) +
  facet_wrap(~ term, ncol = 2, labeler = label_both(pluck(.raw_map[["stat"]])), scales = 'free_x')  +
    geom_vline(data = raw_num_eval, aes(xintercept = mean), color = "steelblue", size = 1) +
    ggtitle(title) +
    theme_bw()

    plot(plot1)
}

but when I plot it

plot_4_ranges(Sector_Prices_long, assets, Spy, stat = "sd", "Spy Prices")

I get this error message

Error in .subset2(x, i, exact = exact) :
recursive indexing failed at level 2

can someone help me figure out where I am screwing up?

[AlexisW]

It would be easier to help if you provided a minimal example, with some data and the shortest code possible that reproduces the error.

Here is some guidance that can help.