Tables with gt and gtsummary

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
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ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(gtsummary)

mpg |> 
  select(cyl, cty, hwy) |> 
  tbl_summary()

Characteristic	N = 2341
cyl
4	81 (35%)
5	4 (1.7%)
6	79 (34%)
8	70 (30%)
cty	17 (14, 19)
hwy	24 (18, 27)
1 n (%); Median (Q1, Q3)

mpg |> 
  tbl_cross(row = fl, col = cyl, percent = "cell")

	cyl				Total
	4	5	6	8
fl
c	1 (0.4%)	0 (0%)	0 (0%)	0 (0%)	1 (0.4%)
d	3 (1.3%)	0 (0%)	1 (0.4%)	1 (0.4%)	5 (2.1%)
e	0 (0%)	0 (0%)	1 (0.4%)	7 (3.0%)	8 (3.4%)
p	22 (9.4%)	0 (0%)	17 (7.3%)	13 (5.6%)	52 (22%)
r	55 (24%)	4 (1.7%)	60 (26%)	49 (21%)	168 (72%)
Total	81 (35%)	4 (1.7%)	79 (34%)	70 (30%)	234 (100%)

trial |> 
  head()

# A tibble: 6 × 8
  trt      age marker stage grade response death ttdeath
  <chr>  <dbl>  <dbl> <fct> <fct>    <int> <int>   <dbl>
1 Drug A    23  0.16  T1    II           0     0    24  
2 Drug B     9  1.11  T2    I            1     0    24  
3 Drug A    31  0.277 T1    II           0     0    24  
4 Drug A    NA  2.07  T3    III          1     1    17.6
5 Drug A    51  2.77  T4    III          1     1    16.4
6 Drug B    39  0.613 T4    I            0     1    15.6

library(gapminder)
gapminder |> 
  select(continent, year, lifeExp) |>
  filter(year  %in% c(1952, 2007)) |>
  tbl_cross(row = continent, col = year, percent = "row")

	year		Total
	1952	2007
continent
Africa	52 (50%)	52 (50%)	104 (100%)
Americas	25 (50%)	25 (50%)	50 (100%)
Asia	33 (50%)	33 (50%)	66 (100%)
Europe	30 (50%)	30 (50%)	60 (100%)
Oceania	2 (50%)	2 (50%)	4 (100%)
Total	142 (50%)	142 (50%)	284 (100%)