Plot histograms per row using gt tables - R

Question

I want to create a gt table where I see some metrics like number of observations, mean and median, and I want a column with its histogram. For this question I will use the iris dataset.

I have recently learned how to put a plot in a tibble using this code:

library(dplyr)
library(tidyr)
library(purrr)
library(gt)
my_tibble <- iris %>%
  pivot_longer(-Species, 
               names_to = "Vars", 
               values_to = "Values") %>%
  group_by(Vars) %>%
  summarise(obs = n(),
            mean = round(mean(Values),2),
            median = round(median(Values),2), 
            plots = list(ggplot(cur_data(), aes(Values)) + geom_histogram()))

Now I want to use the plots column for plotting an histogram per variable, so I have tried this:

my_tibble %>%
  mutate(ggplot = NA) %>%
  gt() %>%
  text_transform(
    locations = cells_body(vars(ggplot)),
    fn = function(x) {
      map(.$plots,ggplot_image)
    }
  )

But it returns me an error:

Error in body[[col]][stub_df$rownum_i %in% loc$rows] <- fn(body[[col]][stub_df$rownum_i %in%  : 
  replacement has length zero

The gt table should be like this:

Any help will be greatly appreciated.

Answer 1

We need to loop over the plots

library(dplyr)
library(tidyr)
library(purrr)
library(gt)
library(ggplot2)
iris %>%
  pivot_longer(-Species, 
               names_to = "Vars", 
               values_to = "Values") %>%
  nest_by(Vars) %>%
  mutate(n = nrow(data),
         mean = round(mean(data$Values), 2), 
         median = round(median(data$Values), 2), 
         plots = list(ggplot(data, aes(Values)) + geom_histogram()), .keep = "unused") %>%
  ungroup %>%
  mutate(ggplot = NA) %>%
  {dat <- .
  dat %>%
    select(-plots) %>%
    gt() %>%
  text_transform(locations = cells_body(c(ggplot)),
                 fn = function(x) {
                  map(dat$plots, ggplot_image, height = px(100))
                 }
                 
                 
                 )
  }

-check for the output