Recoding groups to create a summary accordingly

I have a data like table below

Category Value
14        1
13        2
32        1
63        4
24        1
77        3
51        2
19        4
15        1
24        4
32        3
10        1
.         .
.         .
so on 

actually i want to create a group of variables like

C1= (14,13,24,19,77)
C2= (32,51,63,15,10)
c3= (......)
c4= (...)

so that it will create a dataframe like (Recoding kind of thing)

C1  c2  c3  c4......
14  32  
13  51
24  63
15  10

after this i can create a summary

df<- df[!is.na(df[[cols]]), ]
sum1 <- as.data.frame(table(df[[cols]]))

Final Expected output should be like

   C1  C2 C3 ....
1  22%
2  13%
3  42%
4  15%
N  94

N is total number of counts for that particular groups.

library(dplyr)

df %>%
  group_by(col = case_when(Category %in% C1 ~ 'C1', 
                           Category %in% C2 ~ 'C2')) %>%
  mutate(Value = row_number()) %>%
  tidyr::pivot_wider(names_from = col, values_from = Category) %>%
  janitor::adorn_totals()