Summary table with across()

library(tidyverse)

mpg %>% 
  head()

## # A tibble: 6 x 11
##   manufacturer model displ  year   cyl trans      drv     cty   hwy fl    class 
##   <chr>        <chr> <dbl> <int> <int> <chr>      <chr> <int> <int> <chr> <chr> 
## 1 audi         a4      1.8  1999     4 auto(l5)   f        18    29 p     compa~
## 2 audi         a4      1.8  1999     4 manual(m5) f        21    29 p     compa~
## 3 audi         a4      2    2008     4 manual(m6) f        20    31 p     compa~
## 4 audi         a4      2    2008     4 auto(av)   f        21    30 p     compa~
## 5 audi         a4      2.8  1999     6 auto(l5)   f        16    26 p     compa~
## 6 audi         a4      2.8  1999     6 manual(m5) f        18    26 p     compa~

mpg %>% 
  group_by(class) %>% 
  summarise(average = mean(cty))

## # A tibble: 7 x 2
##   class      average
## * <chr>        <dbl>
## 1 2seater       15.4
## 2 compact       20.1
## 3 midsize       18.8
## 4 minivan       15.8
## 5 pickup        13  
## 6 subcompact    20.4
## 7 suv           13.5

mpg %>% 
  group_by(class) %>% 
  summarise(across(cty,.fns = mean),
            .groups = "drop")

## # A tibble: 7 x 2
##   class        cty
## * <chr>      <dbl>
## 1 2seater     15.4
## 2 compact     20.1
## 3 midsize     18.8
## 4 minivan     15.8
## 5 pickup      13  
## 6 subcompact  20.4
## 7 suv         13.5

mpg %>% 
  group_by(class) %>% 
  summarise(mean_city = mean(cty),
            std_city = sd(cty))
            

## # A tibble: 7 x 3
##   class      mean_city std_city
## * <chr>          <dbl>    <dbl>
## 1 2seater         15.4    0.548
## 2 compact         20.1    3.39 
## 3 midsize         18.8    1.95 
## 4 minivan         15.8    1.83 
## 5 pickup          13      2.05 
## 6 subcompact      20.4    4.60 
## 7 suv             13.5    2.42

mpg %>% 
  group_by(class) %>% 
  summarise(across(cty,.fns = list(mean = mean, std = sd)),
             .groups = "drop")

## # A tibble: 7 x 3
##   class      cty_mean cty_std
## * <chr>         <dbl>   <dbl>
## 1 2seater        15.4   0.548
## 2 compact        20.1   3.39 
## 3 midsize        18.8   1.95 
## 4 minivan        15.8   1.83 
## 5 pickup         13     2.05 
## 6 subcompact     20.4   4.60 
## 7 suv            13.5   2.42

mpg %>% 
  group_by(class) %>% 
  summarise(mean_city = mean(cty),
            std_city = sd(cty),
            mean_hwy = mean(hwy),
            std_hwy = sd(hwy),)

## # A tibble: 7 x 5
##   class      mean_city std_city mean_hwy std_hwy
## * <chr>          <dbl>    <dbl>    <dbl>   <dbl>
## 1 2seater         15.4    0.548     24.8    1.30
## 2 compact         20.1    3.39      28.3    3.78
## 3 midsize         18.8    1.95      27.3    2.14
## 4 minivan         15.8    1.83      22.4    2.06
## 5 pickup          13      2.05      16.9    2.27
## 6 subcompact      20.4    4.60      28.1    5.38
## 7 suv             13.5    2.42      18.1    2.98

mpg %>% 
  group_by(class) %>% 
  summarise(across(c(cty, hwy),
                   .fns = list(mean = mean, std = sd)),
             .groups = "drop")

## # A tibble: 7 x 5
##   class      cty_mean cty_std hwy_mean hwy_std
## * <chr>         <dbl>   <dbl>    <dbl>   <dbl>
## 1 2seater        15.4   0.548     24.8    1.30
## 2 compact        20.1   3.39      28.3    3.78
## 3 midsize        18.8   1.95      27.3    2.14
## 4 minivan        15.8   1.83      22.4    2.06
## 5 pickup         13     2.05      16.9    2.27
## 6 subcompact     20.4   4.60      28.1    5.38
## 7 suv            13.5   2.42      18.1    2.98