Changing row labels for frequency distribution tables

iancgmd · April 4, 2023, 6:19am

Describe your issue

Hello! I frequently encounter datasets where values are not presentation-ready like in the dataset below:

 demo_data <- data.frame(
     stringsAsFactors = FALSE,
                  sex = c("m","m","m",
                          "m","m","m","m","m","f",
                          "m"),
  case_classification = c("prob","susp","prob",
                          "susp","susp","susp","susp","susp","susp","susp")
)

When I create a table for presentation, I am able to manipulate column labels with cols_label() for {gt} or set_header_labels() for {flextable}. However, I can’t seem to find an option for either to change the row labels for example:

In sex,
m to “Male”
f to “Female”

In case_classification
susp to “Suspect”
prob to “Probable”

What steps have you already taken to find an answer?

What I am doing now is to recode values, for example:

demo_data <- demo_data %>%  mutate(sex = recode(sex, "m" = "Male"))

Is it possible to “recode” or change row labels as you are constructing the table for presentation already? It does not look like it is possible for {flextable}, while for {gt} you can only add row group labels with tab_row_group().

aspina · April 4, 2023, 7:14am

hey Ian - check out the labelled package - it works with gtsummary which can then be passed to gt or flextable.

Here is some example code for how to set labels - hope this helps

github.com

R4EPI/sitrep/blob/master/inst/rmarkdown/templates/mortality/skeleton/skeleton.Rmd#L897

      
        
            
            
## observation time ------------------------------------------------------------
            
            
## Define observation time in days
            study_data_cleaned <- study_data_cleaned %>% 
              mutate(obstime = as.numeric(enddate - startdate))
            ```
            
            

            
<!-- ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
            /// labelling_data \\\
            --------------------------------------------------------------------------------
            
            
We can use the labelled package to add tags to our variable names and values.  
            This means that we can have both coded values and a cleaner written out form of
            variable names and values; this makes our code easier to write but our output 
            cleaner to look at (because we can use labels in tables/figures).
            
            
So for example our variable name would be "sex" but the label would be "Sex", and
            the values would be "m" and "f" but the label would be "Male" and "Female".
            This corresponds to the option_name and option_label in kobo dictionaries.

machupovirus · April 5, 2023, 1:57am

Hi Ian,

In addition to using the labelled package, as Alex suggested, you could also use case_match and fmt to achieve this, as seen below:

library(tidyverse)
library(gt)

demo_data <- data.frame(
    stringsAsFactors = FALSE,
    sex = c("m", "m", "m",
                    "m", "m", "m", "m", "m", "f",
                    "m"),
    case_classification = c(
        "prob",
        "susp",
        "prob",
        "susp",
        "susp",
        "susp",
        "susp",
        "susp",
        "susp",
        "susp"
    )
)

gt(data = demo_data) |>
    cols_label(sex = "Sex",
                         case_classification = "Case Classification") |>
    fmt(columns = sex,
            fns = \(x) {
                case_match(
                    x,
                    "m" ~ "Male",
                    "f" ~ "Female",
                    .default = NA_character_
                )
            }) |>
    fmt(columns = case_classification,
            fns = \(x) {
                case_match(
                    x,
                    "prob" ~ "Probable",
                    "susp" ~ "Suspect",
                    .default = NA_character_
                )
            })

Sex	Case Classification
Male	Probable
Male	Suspect
Male	Probable
Male	Suspect
Male	Suspect
Male	Suspect
Male	Suspect
Male	Suspect
Female	Suspect
Male	Suspect

^{Created on 2023-04-04 with reprex v2.0.2}

Session info

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All the best,

Tim

iancgmd · April 5, 2023, 2:48am

Thank you Alex and Tim! I’ll look into both the labelled package and fmt() function of tthe gt package. Both seem to work great.

Regards,
Ian

iancgmd · April 6, 2023, 1:33am

Hi again, Tim! I am trying to understand this portion of the code using the fmt() function:

fns = \(x) {
                case_match(
                    x,
                    "m" ~ "Male",
                    "f" ~ "Female",
                    .default = NA_character_
                )
            }

I searched the {gt} documentation which showed that fns could be a single formatting function or a named list of functions. However, the given examples doesn’t look similar to how we applied it.

I understand how the nested case_match() function in our current example works, but how does the \(x) { } work around it?

Thank you.

machupovirus · April 6, 2023, 2:06am

Hello Ian,

This is just shorthand R syntax for an anonymous function, you could replace it with:

fns = function(x) {
                case_match(
                    x,
                    "m" ~ "Male",
                    "f" ~ "Female",
                    .default = NA_character_
                )
            }

If you are more comfortable with that. Alternatively, you could try to write a standalone function if you plan on using it to format various variables in the table and then just call it within the fmt function with the necessary argument values for that given variable.

All the best,

Tim

iancgmd · April 6, 2023, 5:46am

Thanks, Tim! The examples I saw used function(x). I thought the backslash served a different purpose.

Best,
Ian