Nest ggplot histograms per variable-CodePudding

I want to create a data frame where I summarize values like number of observations, mean and median, and I want to nest its ggplot histograms. For this, I will use the iris dataset.

This is my first attempt:

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))

So it gives me:

# A tibble: 4 x 4
  Vars           obs  mean median
  <chr>        <int> <dbl>  <dbl>
1 Petal.Length   150  3.76   4.35
2 Petal.Width    150  1.2    1.3 
3 Sepal.Length   150  5.84   5.8 
4 Sepal.Width    150  3.06   3

This is the expected table:

# A tibble: 4 x 5
  Vars           obs  mean median plot
  <chr>        <int> <dbl>  <dbl> <list>
1 Petal.Length   150  3.76   4.35 <gg>
2 Petal.Width    150  1.2    1.3  <gg>
3 Sepal.Length   150  5.84   5.8  <gg>
4 Sepal.Width    150  3.06   3    <gg>

This is what I have tried:

iris %>%
  pivot_longer(-Species, 
               names_to = "Vars", 
               values_to = "Values") %>%
  group_by(Vars) %>%
  nest() %>%
  mutate(metrics = lapply(data, function(df) df %>% summarise(obs = n(), mean = mean(Values), median = median(Values))),
         plots = lapply(data, function(df) df %>% ggplot(aes(Values))   geom_histogram()))

Almost there, I see this:

# A tibble: 4 x 4
# Groups:   Vars [4]
  Vars         data               metrics          plots 
  <chr>        <list>             <list>           <list>
1 Sepal.Length <tibble [150 × 2]> <tibble [1 × 3]> <gg>  
2 Sepal.Width  <tibble [150 × 2]> <tibble [1 × 3]> <gg>  
3 Petal.Length <tibble [150 × 2]> <tibble [1 × 3]> <gg>  
4 Petal.Width  <tibble [150 × 2]> <tibble [1 × 3]> <gg>

But I don't know how to see the expected tibble with the obs, mean, median and plots columns without the data and metrics columns. Any help will be greatly appreciated.

CodePudding user response：

We may use cur_data() in summarise and get the output in a list by wrapping

library(dplyr)
library(ggplot2)
library(tidyr)
out <- 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()))

-output

out
# A tibble: 4 × 5
  Vars           obs  mean median plots 
  <chr>        <int> <dbl>  <dbl> <list>
1 Petal.Length   150  3.76   4.35 <gg>  
2 Petal.Width    150  1.2    1.3  <gg>  
3 Sepal.Length   150  5.84   5.8  <gg>  
4 Sepal.Width    150  3.06   3    <gg>