dataframe：将由星号分隔的数据块从长格式重新格式化为宽格式

我正在制作一个数据表，它讨论由一列组成的街道。 每条街道都是一排长度可变的街道 第一行包含街道名称，其他行包含各种详细信息 每条街道由一个包含4颗星的单元与另一条街道隔开。 如何重新组织数据

dataset <- c("Rosa street", "London", "From to", "Description : lorem ipsum", "****", "Main street", "Bristol", "From to", "Description : dolor sit amet", "coordinates", "****"

 dataset <- as.data.frame(dataset)

预期产量

     var1        |var2      |var3    |var4                           |var5         |
------------------------------------------------------------------------------------
1    Rosa street | London  | From to |  Description : lorem ipsum    |NA           | 
2    Main street | Bristol | From to |  Description : dolor sit amet | coordinates |

这里有一个使用tidyverse的选项-

这里有一个使用tidyverse的选项-

这是否有效：

library(tidyr)
library(dplyr)
library(stringr)
dataset %>% mutate(grp = cumsum(street == '****')) %>% filter(street != '****') %>% 
   mutate(vars = case_when(str_detect(street, 'street') ~ 'var1',
                           str_detect(street, 'From to') ~ 'var3', 
                           str_detect(street, 'Description :') ~ 'var4', 
                           str_detect(street, 'coordinates') ~ 'var5',
                           TRUE ~ 'var2')) %>% pivot_wider(id_cols = grp, names_from = vars, values_from = street) %>% select(-grp)
# A tibble: 2 x 5
  var1        var2    var3    var4                         var5       
  <chr>       <chr>   <chr>   <chr>                        <chr>      
1 Rosa street London  From to Description : lorem ipsum    NA         
2 Main street Bristol From to Description : dolor sit amet coordinates

使用的数据：

dataset <- data.frame( street = c("Rosa street", "London", "From to", "Description : lorem ipsum", "****", "Main street", "Bristol", "From to", "Description : dolor sit amet", "coordinates", "****"))

这是否有效：

library(tidyr)
library(dplyr)
library(stringr)
dataset %>% mutate(grp = cumsum(street == '****')) %>% filter(street != '****') %>% 
   mutate(vars = case_when(str_detect(street, 'street') ~ 'var1',
                           str_detect(street, 'From to') ~ 'var3', 
                           str_detect(street, 'Description :') ~ 'var4', 
                           str_detect(street, 'coordinates') ~ 'var5',
                           TRUE ~ 'var2')) %>% pivot_wider(id_cols = grp, names_from = vars, values_from = street) %>% select(-grp)
# A tibble: 2 x 5
  var1        var2    var3    var4                         var5       
  <chr>       <chr>   <chr>   <chr>                        <chr>      
1 Rosa street London  From to Description : lorem ipsum    NA         
2 Main street Bristol From to Description : dolor sit amet coordinates

使用的数据：

dataset <- data.frame( street = c("Rosa street", "London", "From to", "Description : lorem ipsum", "****", "Main street", "Bristol", "From to", "Description : dolor sit amet", "coordinates", "****"))