用r中的单词和分号拆分字符串

我有一个数据框（或数据表），在名为

text

的列中有字符串，如下所示：

text
name: john; surname: smith; age: 35; gender:male
name: mark; age:50
name: jack; surname: brown
name: tom; surname: travis; gender: male

如何将字符串的每个部分extact到同一数据帧中的独立列中？我希望有以下专栏：

name.text
name: john
name: mark
name: jack
name: tom

surname.text
surname: smith
(empty)
surname: brown
surname: travis

age.text
age: 35
age: 50
(empty)
(empty)

gender.text
gender:male
(empty)
(empty)
gender:male

---

谢谢大家!

这里有一个选项，我们在

处拆分元素

，然后将分为两列，并将格式从“长”改为“宽”

library(dplyr)
library(tidyr)
library(stringr)
library(tibble)
df1 %>%
   rownames_to_column('rn') %>%
   separate_rows(text, sep = ';\\s*') %>%
   separate(text, into = c('key', 'val'), sep=":\\s*") %>% 
   pivot_wider(names_from = key, values_from = val, 
            values_fill = list(val = "(empty)")) %>%
   select(-rn) %>%
   imap_dfr(~ case_when(.x != "(empty)" ~ str_c(.y, .x, sep=":"), TRUE ~ .x)) %>%
   rename_all(~ str_c(., ".text"))
# A tibble: 4 x 4
#  name.text surname.text   age.text gender.text
#  <chr>     <chr>          <chr>    <chr>      
#1 name:john surname:smith  age:35   gender:male
#2 name:mark (empty)        age:50   (empty)    
#3 name:jack surname:brown  (empty)  (empty)    
#4 name:tom  surname:travis (empty)  gender:male

数据

---

df1非常感谢您的回复。我需要使用几乎基本的R（因为其他项目依赖，不要问为什么：）。你能帮个忙吗？如何只用R基来解决这个问题？@Makaroni。在帖子中，您指定了
data.table
（您使用的是该软件包）@Makaroni。更新为
base R
nm1 <- c("name", "surname", "age", "gender")
lst1 <-  lapply(strsplit(df1$text, ";\\s*"), function(x) {
          prfx <- sub(":.*", "", x)
          x1 <- x[match(nm1, prfx)]
          replace(x1, is.na(x1), "(empty)")})
out <- do.call(rbind.data.frame, lst1)
names(out) <- paste0(nm1, ".text")
out
#   name.text    surname.text age.text  gender.text
#1 name: john  surname: smith  age: 35  gender:male
#2 name: mark         (empty)   age:50      (empty)
#3 name: jack  surname: brown  (empty)      (empty)
#4  name: tom surname: travis  (empty) gender: male

df1 <- structure(list(text = c("name: john; surname: smith; age: 35; gender:male", 
"name: mark; age:50", "name: jack; surname: brown", 
"name: tom; surname: travis; gender: male"
)), class = "data.frame", row.names = c(NA, -4L))

d = lapply(strsplit(df1$text, "; ?"), function(x){
    data.frame(do.call(rbind, strsplit(x, ": ?")), stringsAsFactors = FALSE)
})

fields = unique(unlist(lapply(d, function(x) x$X1)))

d2 = do.call(rbind, lapply(d, function(x)
    data.frame(fields, val = x$X2[match(fields, x$X1)])))

d2[order(match(d2$fields, fields)),]