使用 forcats 和 purrr 总结字符向量列表

Question

I have tibble where col1 is a list of character vectors of variable length and col2 is a numeric vector indicating a group assignment, either 1 or 0. I want to first convert all of the character vectors in the list ( col1 ) to factors, and then unify all of the factors levels across these factors so that I can ultimately get a tally of counts for each factor level. For the example data below, that would mean the tally would be as follows:

overall:

    level, count  
    "a", 2
    "b", 2
    "c", 2
    "d", 3
    "e", 1

for group=1:

    level, count  
    "a", 1
    "b", 2
    "c", 1
    "d", 1
    "e", 0

for group=0:

    level, count  
    "a", 1
    "b", 0
    "c", 1
    "d", 2
    "e", 1

The ultimate goal is to be able to get a total count of each factor level c("a","b","c","d","e") and plot them by the grouping variable.

Here is some code that might give better context to my problem:

library(forcats)
library(purrr)
library(dplyr)
library(ggplot2)

tib <- tibble(col1=list(c("a","b"),
                 c("b","c","d"), 
                 c("a","d","e"),
                 c("c","d")),
       col2=c(1,1,0,0))


tib %>% 
  mutate(col3=map(.$col1,.f = as_factor)) %>% 
  mutate(col4=map(.$col3,.f = fct_unify))

Unfortunately, this code fails. I get the following error, but don't know why:

Error: fs must be a list

I thought my input was a list?

I appreciate any help anyone might offer. Thanks.

Answer 1

You can first unnest and then count

library(dplyr)
library(tidyr)

tib %>%
  unnest(col = col1) %>%
  #If needed col1 as factors
  #mutate(col1 =factor(col1)) %>%
  count(col1)

#  col1      n
#  <fct> <int>
#1 a         2
#2 b         2
#3 c         2
#4 d         3
#5 e         1

---

To count based on group ie col2 , we can do

tib %>% 
  unnest(col = col1) %>% 
  mutate_at(vars(col1, col2), factor) %>%
  count(col1, col2, .drop = FALSE)

#   col1  col2      n
#   <fct> <fct> <int>
# 1 a     0         1
# 2 a     1         1
# 3 b     0         0
# 4 b     1         2
# 5 c     0         1
# 6 c     1         1
# 7 d     0         2
# 8 d     1         1
# 9 e     0         1
#10 e     1         0