How to produce summary table?

Suppose I have the following table named df.

A; B
A; B
B; C; D
C; D; E; F

Weight for each element of the row is computed as: wt[i] <- 1/lengths(str_split(df[1],";")). Ideally, the above table weights attached to each elements seems the following.

0.5*A; 0.5*B
0.5*A; 0.5*B
0.333*B; 0.333*C; 0.333*D
0.25*C; 0.25*D; 0.25*E; 0.25*F

So, my intention is to have a table where the frequencies are the sum of the weights. The output I need is the following:

A     B     C     D      E     F
1  1.333 0.583  0.583  0.25  0.25

Any help is highly appreciated!

Solution

Here is an option in base R. After splitting the first column by ; followed by zero or more spaces (\\s*), get the lengths of list and find the sum using tapply

lst1 <- strsplit(df[[1]], ";\\s*")
l1 <- lengths(lst1)
tapply(rep(1/l1, l1), unlist(lst1), sum)
#        A         B         C         D         E         F 
#1.0000000 1.3333333 0.5833333 0.5833333 0.2500000 0.2500000

Or in tidyverse, we can use separate_rows to split up the column and then do a group by summarise

library(tibble)
library(dplyr)
library(tidyr)
df %>%
    mutate(rn = row_number()) %>%
    separate_rows(v1) %>%
    add_count(rn) %>% 
    mutate(n = 1/n) %>% 
    group_by(v1) %>% 
    summarise(n = sum(n))
# A tibble: 6 x 2
#  v1        n
#  <chr> <dbl>
#1 A     1    
#2 B     1.33 
#3 C     0.583
#4 D     0.583
#5 E     0.25 
#6 F     0.25

data

df <- structure(list(v1 = c("A; B", "A; B", "B; C; D", "C; D; E; F"
)), class = "data.frame", row.names = c(NA, -4L))