Applying group_by and summarise(sum) but keep columns with non-relevant conflicting data?

Question

My question is very similar to Applying group_by and summarise on data while keeping all the columns' info but I would like to keep columns which get excluded because th

Answer 1

Here are two other options:

1) Nest columns into one column and then customize the summary by checking the data types:

df %>% 
    group_by(Label, Code) %>% nest() %>% 
    mutate(data = map(data, 
        ~ as.tibble(map(.x, ~ if(is.numeric(.x)) sum(.x) else paste(.x, collapse="_")))
          )
    ) %>% unnest()

# A tibble: 6 x 6
#   Label   Code                        Type Proportion     N     C
#                                  
#1   203c      c                   wholefish    1.00000     1     1
#2   203c      a                       flesh    1.00000     2     2
#3   204a      a               flesh_formula    0.99999     8     8
#4   204a      b     fleshdelip_formuladelip    0.99999    10    10
#5   204a      c           formula_wholefish    0.99999    16    16
#6   204a      d formuladelip_wholefishdelip    0.99999    18    18

2) summarize separately and then join the result:

numeric <- df %>% 
    group_by(Label, Code) %>% 
    summarise_if(is.numeric, sum)

character <- df %>% 
    group_by(Label, Code) %>% 
    summarise_if(~ is.character(.) || is.factor(.), ~ paste(., collapse="_"))

inner_join(numeric, character, by = c("Label", "Code"))
# A tibble: 6 x 6
# Groups:   Label [?]
#   Label   Code Proportion     N     C                        Type
#                                  
#1   203c      a    1.00000     2     2                       flesh
#2   203c      c    1.00000     1     1                   wholefish
#3   204a      a    0.99999     8     8               flesh_formula
#4   204a      b    0.99999    10    10     fleshdelip_formuladelip
#5   204a      c    0.99999    16    16           formula_wholefish
#6   204a      d    0.99999    18    18 formuladelip_wholefishdelip