下面是一个tidyverse选项，可以帮助您入门

library(tidyverse)
rel <- list("Mother", "Father", "Brother", "Sister", "Grandparent", "Other adult")
names(rel) <- unlist(rel)
bind_cols(df[, 1, drop = F], map(rel, ~+str_detect(tolower(df[, 2]), tolower(.x))))
#  row Mother Father Brother Sister Grandparent Other adult
#1   1      1      1       1      1           1           1
#2   2      0      0       0      0           0           0
#3   3      1      0       0      1           0           0
#4   4      1      1       0      0           0           0

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示例数据

df <- read.table(text =
    "row lives.with.whom
  1  'Mother (biological mother, foster mother, step mother, etc.), Father (biological father, foster father, step father, etc.), Grandparent(s) (biological, foster, step, etc.), Brother(s) older than 18, Sister(s) older than 18, Other adults (aunts, uncles, etc.)'
  2  ''
  3  'Mother (biological mother, foster mother, step mother, etc.), Sister(s) older than 18'
  4  'Mother (biological mother, foster mother, step mother, etc.), Father (biological father, foster father, step father, etc.)'", header = T)

型

试试这个：

rel<-list("Mother", "Father", "Brother", "Sister", "Grandparent", "Other adult")

for(i in 1:6){
  df$i<-if_else(grepl(rel[[i]],df$lives.with.whom),1,0)
  colnames(df)[i+2]<-rel[[i]]
}

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我做了一些假设，并试图解决它。

library(tidyr)
library(dplyr)
# create nested lists with names of mothers and fathers for two ppl
mother <- list(list("bio_1","step_1","foster_1"), list("bio_2", "stp_2", "foster_2"))
father <- list(list("bio_1", "foster_1", "other_1"), list("bio_2", "stp_2", "foster_2"))

# convert to data frame
test_object <- data_frame(person = c(1,2),mother,father)

# print 
test_object

# A tibble: 2 x 3
  person mother     father    
   <dbl> <list>     <list>    
1      1 <list [3]> <list [3]>
2      2 <list [3]> <list [3]>

# first unnest the lists and get to the inner list
# then convert from wide to long form data
# do another unnnest to get the actual data in the long format
test_object %>%
  unnest(.) %>%
    gather(data = ., key = relationship, value = name, -person) %>%
      unnest() -> test_object
    
    test_object
# A tibble: 12 x 3
   person relationship name    
    <dbl> <chr>        <chr>   
 1      1 mother       bio_1   
 2      1 mother       step_1  
 3      1 mother       foster_1
 4      2 mother       bio_2   
 5      2 mother       stp_2   
 6      2 mother       foster_2
 7      1 father       bio_1   
 8      1 father       foster_1
 9      1 father       other_1 
10      2 father       bio_2   
11      2 father       stp_2   
12      2 father       foster_2

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这里有tidyverse和data.table的链接，它们包含了很多包和函数，可以解决大多数数据木工/争论问题。