r - How to map tibble elements to ggplot2 aesthetics? -

i have following dataset

map(.x = list(small = 3, medium = 10, large  = 100) ,        .f = ~ sample(rnorm(1000), .x, replace = t)) %>%        tibble(sample = ., mean = map_dbl(., mean))   # tibble: 3 x 2        sample       mean        <list>      <dbl> 1   <dbl [3]> 0.61473548 2  <dbl [10]> 0.17278357 3 <dbl [100]> 0.04156308 

i trying functionally create 1 histogram in ggplot2 each record in column sample. display plots in same grid, thought somehow use facet_wrap() not sure how map aesthetics lists.

this have tried far:

map(.x = list(small = 3, medium = 10, large  = 100) ,            .f = ~ sample(rnorm(1000), .x, replace = t)) %>%            tibble(sample = ., mean = map_dbl(., mean)) %>%     ggplot2::ggplot(data = .) + geom_histogram(mapping = aes(sample)) + facet_wrap(~ sample) 

the output expect 3 histograms 3, 10 , 100 observations respectively.

i wonder if possible solution involve splitting sample in 2 columns: 1 values, indicating distribution size each value belongs to. more compliant ggplot2 logic, not sure how expand tibble accordingly.

ps: not sure how phrase question suggestions welcome

i think need tidyr::unnest:

library(dplyr) library(tidyr) library(ggplot2)  ## generate data set.seed(123) dtf <- map(.x = list(small = 3, medium = 10, large  = 100),            .f = ~ sample(rnorm(1000), .x, replace = t)) %>%     tibble(sample = ., mean = map_dbl(., mean))  ## plot dtf %>%     mutate(group = names(sample)) %>%  # or: group = lengths(sample)     unnest(sample) %>%     ggplot(data = .) +     geom_histogram(mapping = aes(sample)) +     facet_wrap(~ group) 

wiki