Using gt package in R for summary tables

Question

I'm trying to use the gt package in R to make a summary table. My data are structured as:

Value Condition_1 Condition_2 Type
0.33      LN          0.5      <10%
0.43      LN          0.5      <20%
0.23      LN          0.5      >20%
0.43      LN          0.6      <10%
0.23      LN          0.6      <20%
0.33      LN          0.6      >20%
0.33      LS          0.5      <10%
0.43      LS          0.5      <20%
0.23      LS          0.5      >20%
0.43      LS          0.6      <10%
0.23      LS          0.6      <20%
0.33      LS          0.6      >20%

I'd like the resulting table to look like:

Type <10% <20% >20%
LN-0.5
     0.33  0.43 0.23
LN-0.6
     0.43  0.23 0.33
LS-0.5
     0.33  0.43 0.23
LS-0.6
     0.43  0.23 0.33

I'm getting pretty close I think, and currently have my code set up as:

df %>% gt(rowname_col = c("value"),
       groupname_col = c("Condition_1", "Condition_2")) %>% 
       summary_rows(groups = TRUE,
       columns = vars(value),
       fns = list(avg = ~mean(.)))

I thought it would be as simple as swapping columns = vars(value) for columns = vars(Type) but that option can only handle numeric vectors (as far as I can tell). Can anyone please help figure this out? Thanks in advance!

Susan Switzer · Accepted Answer · 2020-07-28 17:53:41Z

Does this look closer to what you expect? I don't think I perfectly recreated your dataset, but perhaps close enough for proof of concept. Started by wrangling your data to combine Condition_1 and Condition_2, then made the data wider, then passed to gt().

library(gt)
library(tidyverse)

df <- data.frame(Value = c(0.33, 0.43, 0.23, 0.43, 0.23, 0.33, 0.33, 0.43, 0.23, 0.43, 0.23, 0.33), 
                         Condition_1 = c('LN', 'LN', 'LN', 'LN', 'LN', 'LN', 'LS', 'LS', 'LS', 'LS', 'LS', 'LS'), 
                         Condition_2 = c(0.5, 0.5, 0.5, 0.6, 0.6, 0.6, 0.5, 0.5, 0.5, 0.6, 0.6, 0.6), 
                         Type = c('<10%', '<20%', '<20%', '<10%', '<10%', '<20%', '>20%', '<10%', '<20%', '>20%', '<10%', '<20%')) %>% 
            mutate(Condition = paste0(Condition_1, '-', Condition_2)) %>% 
              select(Type, Value, everything()) %>% 
              pivot_wider(names_from = Type, 
                          values_from = Value)
          
          df %>% 
            gt(groupname_col = 'Condition') %>% 
              cols_hide(column = vars(Condition_1, Condition_2))

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