Example Usage

library(tabtibble)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

The tabtibble package is typically used to create a list of tables for reporting, often in quarto or rmarkdown.

A simple example is to create a list of tables with each number of cylinders grouped together.

d_tab <-
  mtcars %>%
  tidyr::nest(table = !"cyl") %>%
  dplyr::mutate(
    caption = glue::glue("Cars with {cyl} cylinders")
  ) %>%
  new_tab_tibble()

Then, print it! You must set results='asis' for the chunk printing your tab_tibble.

knit_print(d_tab)
Cars with 6 cylinders
mpg disp hp drat wt qsec vs am gear carb
21 160 110 3.9 2.62 16.46 0 1 4 4
21 160 110 3.9 2.875 17.02 0 1 4 4
21.4 258 110 3.08 3.215 19.44 1 0 3 1
18.1 225 105 2.76 3.46 20.22 1 0 3 1
19.2 167.6 123 3.92 3.44 18.3 1 0 4 4
17.8 167.6 123 3.92 3.44 18.9 1 0 4 4
19.7 145 175 3.62 2.77 15.5 0 1 5 6
Cars with 4 cylinders
mpg disp hp drat wt qsec vs am gear carb
22.8 108 93 3.85 2.32 18.61 1 1 4 1
24.4 146.7 62 3.69 3.19 20 1 0 4 2
22.8 140.8 95 3.92 3.15 22.9 1 0 4 2
32.4 78.7 66 4.08 2.2 19.47 1 1 4 1
30.4 75.7 52 4.93 1.615 18.52 1 1 4 2
33.9 71.1 65 4.22 1.835 19.9 1 1 4 1
21.5 120.1 97 3.7 2.465 20.01 1 0 3 1
27.3 79 66 4.08 1.935 18.9 1 1 4 1
26 120.3 91 4.43 2.14 16.7 0 1 5 2
30.4 95.1 113 3.77 1.513 16.9 1 1 5 2
21.4 121 109 4.11 2.78 18.6 1 1 4 2
Cars with 8 cylinders
mpg disp hp drat wt qsec vs am gear carb
18.7 360 175 3.15 3.44 17.02 0 0 3 2
14.3 360 245 3.21 3.57 15.84 0 0 3 4
16.4 275.8 180 3.07 4.07 17.4 0 0 3 3
17.3 275.8 180 3.07 3.73 17.6 0 0 3 3
15.2 275.8 180 3.07 3.78 18 0 0 3 3
10.4 472 205 2.93 5.25 17.98 0 0 3 4
10.4 460 215 3 5.424 17.82 0 0 3 4
14.7 440 230 3.23 5.345 17.42 0 0 3 4
15.5 318 150 2.76 3.52 16.87 0 0 3 2
15.2 304 150 3.15 3.435 17.3 0 0 3 2
13.3 350 245 3.73 3.84 15.41 0 0 3 4
19.2 400 175 3.08 3.845 17.05 0 0 3 2
15.8 351 264 4.22 3.17 14.5 0 1 5 4
15 301 335 3.54 3.57 14.6 0 1 5 8

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