按变量拆分列并创建新列R

Question

我正在尝试使用答案第一个问题拆分下面的列。 目前，我正在使用字母在df中创建新列。 我想在名称前使用字母作为新的列名称。 在低于G，D，W，C，UTIL的情况下。 由于类别G和名字First Person等之间仅存在“空格”，因此我为将类别G以及名字和姓氏分开并在适当的列中加入它们而努力。

library(stringr)

test <- data.frame(Lineup = c("G First Person D Another Last W Fake  Name C Test Another UTIL Another Test", "G Fake Name W Another Fake D Third person UTIL Another Name C Name Another "))

1 G First Person D Another Last W Fake Name C Test Another UTIL Another Test
2 G Fake Name W Another Fake D Third person UTIL Another Name C Name Another

test$G <- str_split_fixed(test$Lineup, " ", 2)

结果：

G
G

希望的结果：

     G             D            W              C             UTIL    
First Person  Another Last  Fake Name      Test Another  Another Test
Fake Name     Third Person  Another Fake   Name Another  Another Name

Answer 1

这是使用tidyverse的一种方法：

# example data
test <- data.frame(Lineup = c("G First Person D Another Last W Fake  Name C Test Another UTIL Another Test", 
                              "G Fake Name W Another Fake D Third person UTIL Another Name C Name Another "))

library(tidyverse)

# create a dataset of words and info about
# their initial row id
# whether they should be a column in our new dataset
# group to join on
dt_words = test %>%
  mutate(id = row_number()) %>%
  separate_rows(Lineup) %>%
  mutate(is_col = Lineup %in% c(LETTERS, "UTIL"),
         group = cumsum(is_col))

# get the corresponding values of your new dataset
dt_values = dt_words %>%
  filter(is_col == FALSE) %>%
  group_by(group, id) %>%
  summarise(values = paste0(Lineup, collapse = " "))

# get the columns of your new dataset
# join corresponding values
# reshape data
dt_words %>%
  filter(is_col == TRUE) %>%
  select(-is_col) %>%
  inner_join(dt_values, by=c("group","id")) %>%
  select(-group) %>%
  spread(Lineup, values) %>%
  select(-id)

#    C            D            G            UTIL            W
# 1  Test Another Another Last First Person Another Test    Fake Name
# 2 Name Another  Third person    Fake Name Another Name Another Fake

请注意 ，这里的假设是，您总是会有一个大写字母来拆分值，这些大写字母将成为新数据集中的列。