When working with categorical variables, crosstable()
allows a very flexible output thanks to the percent_pattern
argument.
This vignette will review the many things you can do using
percent_pattern
.
Init
First, let’s add some missing values to the mtcars2
dataset and tweak some options:
library(crosstable)
mtcars3 = mtcars2
mtcars3$cyl[1:5] = NA
mtcars3$vs[5:12] = NA
crosstable_options(
percent_digits=0
)
Default behaviour
By default, crosstable()
will use
percent_pattern="{n} ({p_row})"
, so it outputs the size
n
along with the row’s percentage p_row
:
crosstable(mtcars3, cyl, by=vs) %>% as_flextable()
label 
variable 
Engine 


straight 
vshaped 
NA 

Number of cylinders 
4 
7 (88%) 
1 (12%) 
2 
6 
0 (0%) 
1 (100%) 
3 

8 
0 (0%) 
11 (100%) 
2 

NA 
2 
2 
1 
Here, we will see how we can tweak percent_pattern
in
order to display other figures.
NOTE: Missing values will always be described with
n
alone. If you want to describe them as nonmissing
values, you will have to mutate them as one, most likely using
forcats::fct_explicit_na()
.
Allowed variables
First, here is the list of all the internal variables you can use:

n
,n_row
,n_col
, andn_tot
: respectively the size of the cell, the row, the column, and the whole table. 
p_row
,p_col
, andp_tot
: respectively the proportion relative to the row, the column, and the whole table. 
p_tot_inf
,p_tot_sup
,p_row_inf
,p_row_sup
,p_col_inf
,p_col_sup
: the confidence interval (calculated using Wilson score) for each of the proportions above.
Should you ever need it, note that it is also possible to use any
external variable defined outside of crosstable()
.
Here is a simple example:
crosstable(mtcars3, cyl, by=vs,
percent_pattern="N={n}/{n_row} > p={p_row}") %>%
as_flextable()
label 
variable 
Engine 


straight 
vshaped 
NA 

Number of cylinders 
4 
N=7/8 > p=88% 
N=1/8 > p=12% 
2 
6 
N=0/1 > p=0% 
N=1/1 > p=100% 
3 

8 
N=0/11 > p=0% 
N=11/11 > p=100% 
2 

NA 
2 
2 
1 
Missing values
As you can see, these internal variables do not account for missing
values (except for n
, obviously).
This should make sense in most cases, but if it doesn’t, you can use the following variables to account for NA explicitly:

n_row_na
,n_col_na
,n_tot_na

p_tot_na
,p_row_na
,p_col_na

p_tot_na_inf
,p_tot_na_sup
,p_row_na_inf
,p_row_na_sup
,p_col_na_inf
,p_col_na_sup
(See the last section for an example)
Note that if you use showNA="no"
, there will be no
difference between the standard variables and the _na
variables.
Proportions in totals
As you may have noticed, totals are considered separately:
crosstable(mtcars3, cyl, by=vs, total=TRUE,
percent_pattern="N={n}, p={p_row} ({n}/{n_row})") %>%
as_flextable()
label 
variable 
Engine 
Total 


straight 
vshaped 
NA 

Number of cylinders 
4 
N=7, p=88% (7/8) 
N=1, p=12% (1/8) 
2 
10 (37%) 
6 
N=0, p=0% (0/1) 
N=1, p=100% (1/1) 
3 
4 (15%) 

8 
N=0, p=0% (0/11) 
N=11, p=100% (11/11) 
2 
13 (48%) 

NA 
2 
2 
1 
5 

Total 
9 (38%) 
15 (62%) 
8 
32 (100%) 
Indeed, you cannot have the same pattern for totals. For instance, the proportion relative to the row would not make sense in the context of the entire row itself.
To get control over the percent_pattern
in totals, you
have to pass a list with names body
,
total_row
, total_col
, and
total_all
:
pp = list(body="N={n}, p={p_tot} ({n}/{n_tot})",
total_row="N={n} p=({p_col})",
total_col="{n}", total_all="Total={n}")
crosstable(mtcars3, cyl, by=vs, total=TRUE,
percent_pattern=pp) %>%
as_flextable()
label 
variable 
Engine 
Total 


straight 
vshaped 
NA 

Number of cylinders 
4 
N=7, p=35% (7/20) 
N=1, p=5% (1/20) 
2 
10 
6 
N=0, p=0% (0/20) 
N=1, p=5% (1/20) 
3 
4 

8 
N=0, p=0% (0/20) 
N=11, p=55% (11/20) 
2 
13 

NA 
2 
2 
1 
5 

Total 
N=9 p=(38%) 
N=15 p=(62%) 
8 
Total=32 
get_percent_pattern()
To easily get a percent_pattern
list, you can use the
get_percent_pattern()
helper:
get_percent_pattern("all")
#> $body
#> [1] "{n} ({p_tot} / {p_row} / {p_col})"
#>
#> $total_row
#> [1] "{n} ({p_col})"
#>
#> $total_col
#> [1] "{n} ({p_row})"
#>
#> $total_all
#> [1] "{n} ({p_tot})"
get_percent_pattern("col", na=TRUE)
#> $body
#> [1] "{n} ({p_col_na})"
#>
#> $total_row
#> [1] "{n} ({p_col_na})"
#>
#> $total_col
#> [1] "{n} ({p_row_na})"
#>
#> $total_all
#> [1] "{n} ({p_tot_na})"
You can also set the result to a variable and modify its members at
will. See ?get_percent_pattern
for more information.
Ultimate example
Here is the ultimate example for percent_pattern
. Give a
close look to all possible values and you will surely find the one that
you need.
ULTIMATE_PATTERN=list(
body="N={n}
Cell: p = {p_tot} ({n}/{n_tot}) [{p_tot_inf}; {p_tot_sup}]
Col: p = {p_col} ({n}/{n_col}) [{p_col_inf}; {p_col_sup}]
Row: p = {p_row} ({n}/{n_row}) [{p_row_inf}; {p_row_sup}]
Cell (NA): p = {p_tot_na} ({n}/{n_tot_na}) [{p_tot_na_inf}; {p_tot_na_sup}]
Col (NA): p = {p_col_na} ({n}/{n_col_na}) [{p_col_na_inf}; {p_col_na_sup}]
Row (NA): p = {p_row_na} ({n}/{n_row_na}) [{p_row_na_inf}; {p_row_na_sup}]",
total_row="N={n}
Row: p = {p_row} ({n}/{n_row}) [{p_row_inf}; {p_row_sup}]
Row (NA): p = {p_row_na} ({n}/{n_row_na}) [{p_row_na_inf}; {p_row_na_sup}]",
total_col="N={n}
Col: p = {p_col} ({n}/{n_col}) [{p_col_inf}; {p_col_sup}]
Col (NA): p = {p_col_na} ({n}/{n_col_na}) [{p_col_na_inf}; {p_col_na_sup}]",
total_all="N={n}
P: {p_col} [{p_col_inf}; {p_col_sup}]
P (NA): {p_col} [{p_col_na_inf}; {p_col_na_sup}]"
)
crosstable(mtcars3, cyl, by=vs,
percent_digits=0, total=TRUE, showNA="always",
percent_pattern=ULTIMATE_PATTERN) %>%
as_flextable() %>%
flextable::theme_box()
label 
variable 
Engine 
Total 


straight 
vshaped 
NA 

Number of cylinders 
4 
N=7 
N=1 
2 
N=10 
6 
N=0 
N=1 
3 
N=4 

8 
N=0 
N=11 
2 
N=13 

NA 
2 
2 
1 
5 

Total 
N=9 
N=15 
8 
N=32 