数据：

team_a <- c('John', 'Tim')
team_b <- c('David', 'Jack')
team_c <- c('Sue', 'Frank', 'Jane')

df <- data.frame(D = c("John; Tim; David; Jack", "Tim", "Jack; David; Sue"))

# to create the data frame: 
D <- c(paste(c(team_a, team_b), collapse = "; "),
       paste(team_a[2], collapse = "; "),
       paste(c(team_b, team_c[1]), collapse = "; "))

df <- data.frame(D = D)

task1：

library(dplyr)
library(tidyr)

df %>%
  mutate(id = row_number()) %>% 
  separate_rows(D, sep = "; ") %>%
  mutate(team = case_when(
    D %in% team_a ~ "team_a",
    D %in% team_b ~ "team_b",
    D %in% team_c ~ "team_c",
    TRUE ~ NA_character_
  )) %>%
  filter(!is.na(team)) %>%
  pivot_wider(names_from = team, values_from = D, values_fn = list(D = toString))

 id team_a    team_b      team_c
  <int> <chr>     <chr>       <chr> 
1     1 John, Tim David, Jack NA    
2     2 Tim       NA          NA    
3     3 NA        Jack, David Sue

task2：

df %>%
  mutate(id = row_number()) %>% 
  separate_rows(D, sep = "; ") %>%
  mutate(team = case_when(
    D %in% team_a ~ "team_a",
    D %in% team_b ~ "team_b",
    D %in% team_c ~ "team_c",
    TRUE ~ NA_character_
  )) %>%
  filter(!is.na(team)) %>%
  group_by(id, team) %>%
  summarise(n = n(), .groups = "drop") %>%
  pivot_wider(names_from = team, values_from = n, values_fill = 0)

     id team_a team_b team_c
  <int>  <int>  <int>  <int>
1     1      2      2      0
2     2      1      0      0
3     3      0      2      1