R/dplyr : Transforming two rows into two columns

Question

我在 R 中有一个数据框，如下所示:

Word    Base    Number  Type
-       -       -       -
shoe    shoe    4834    singular
shoes   shoe    49955   plural
toy     toy     75465   singular
toys    toy     23556   plural
key     key     39485   singular
keys    key     6546    plural
jazz    jazz    58765   plural

我想将其转换为如下所示:

Word_Sg Word_Pl Base    Num_Singular    Num_Plural
--      --      --      --              --
shoe    shoes   shoe    4834            49955
toy     toys    toy     75465           23556
key     keys    key     39485           6546
NA      jazz    jazz    NA              58765

因此，我不想使用两行来存储单数和复数的值，而是想要两列，一列包含单数数字，一列包含复数数字。

我已经使用 dplyr::summarize 尝试了一些操作，但到目前为止，没有任何成功。这是我到目前为止想出的代码:

dataframe1 <- dataframe %>% 
      mutate(Num_Singular = case_when(Type == "singular" ~ Number)) %>%
      mutate(Num_Plural = case_when(Type == "plural" ~ Number)) %>%
      dplyr::select(Word, Base, Num_Singular, Num_Plural) %>%
      group_by(Base) %>%
      dplyr::summarize(Num_Singular = paste(na.omit(Num_Singular)),
                       Num_Plural = paste(na.omit(Num_Plural))

但是，它给了我这个错误:

Error in summarise_impl(.data, dots) : 
  Column `Num_Singular` must be length 1 (a summary value), not 2)

我认为问题可能在于有些行不一定具有单数和复数，而只有其中之一(例如“jazz”)。不过大多数行都有。

那么我如何在 R 或 dplyr 中执行此操作？

Answer 1

如果您首先查看前几列::

select(dat, Base, Word, Type)[1:2,]
#   Base  Word     Type
# 1 shoe  shoe singular
# 2 shoe shoes   plural

从这里开始，考虑它只是将其扩展为单数/复数列，有效地从“高”到“宽”。 (如果 Type 中有两个以上类别，情况会更加明显。)

select(dat, Base, Word, Type) %>%
    spread(Type, Word) %>%
    rename(Word_Pl=plural, Word_Sg=singular)
#   Base Word_Pl Word_Sg
# 1 jazz    jazz    <NA>
# 2  key    keys     key
# 3 shoe   shoes    shoe
# 4  toy    toys     toy

您也可以轻松地对 Number 重复此操作。从那里开始，只需根据键列 Base 合并/连接它们即可:

full_join(
  select(dat, Base, Word, Type) %>%
    spread(Type, Word) %>%
    rename(Word_Pl=plural, Word_Sg=singular),
  select(dat, Base, Number, Type) %>%
    spread(Type, Number) %>%
    rename(Num_Pl=plural, Num_Sg=singular),
  by = "Base"
)
#   Base Word_Pl Word_Sg Num_Pl Num_Sg
# 1 jazz    jazz    <NA>  58765     NA
# 2  key    keys     key   6546  39485
# 3 shoe   shoes    shoe  49955   4834
# 4  toy    toys     toy  23556  75465

---

消耗数据:

library(dplyr)
library(tidyr)
dat <- read.table(text='Word    Base    Number  Type
shoe    shoe    4834    singular
shoes   shoe    49955   plural
toy     toy     75465   singular
toys    toy     23556   plural
key     key     39485   singular
keys    key     6546    plural
jazz    jazz    58765   plural', header=TRUE, stringsAsFactors=FALSE)