这很可能是一个愚蠢的问题，但我用google搜索并搜索，无法找到解决方案。我认为这是因为我不知道用正确的方式来搜索我的问题。
我有一个数据框，我已在R中转换为整洁的文本格式，以摆脱停用词。我现在想要不整洁＆＃39;该数据帧恢复为原始格式。
unexst_tokens的反向/反向命令是什么？
编辑：这是我正在使用的数据的样子。我试图复制Silge和Robinson的Tidy Text书中的分析，但使用的是意大利歌剧史诗。
character = c("FIGARO", "SUSANNA", "CONTE", "CHERUBINO")
line = c("Cinque... dieci.... venti... trenta... trentasei...quarantatre", "Ora sì ch'io son contenta; sembra fatto inver per me. Guarda un po', mio caro Figaro, guarda adesso il mio cappello.", "Susanna, mi sembri agitata e confusa.", "Il Conte ieri perché trovommi sol con Barbarina, il congedo mi diede; e se la Contessina, la mia bella comare, grazia non m'intercede, io vado via, io non ti vedo più, Susanna mia!")
sample_df = data.frame(character, line)
sample_df
character line
FIGARO Cinque... dieci.... venti... trenta... trentasei...quarantatre
SUSANNA Ora sì ch'io son contenta; sembra fatto inver per me. Guarda un po', mio caro Figaro, guarda adesso il mio cappello.
CONTE Susanna, mi sembri agitata e confusa.
CHERUBINO Il Conte ieri perché trovommi sol con Barbarina, il congedo mi diede; e se la Contessina, la mia bella comare, grazia non m'intercede, io vado via, io non ti vedo più, Susanna mia!
我把它变成整洁的文字，这样我就可以摆脱停止的话：
tribble <- sample_df %>%
unnest_tokens(word, line)
# Get rid of stop words
# I had to make my own list of stop words for 18th century Italian opera
itstopwords <- data_frame(text=mystopwords)
names(itstopwords)[names(itstopwords)=="text"] <- "word"
tribble2 <- tribble %>%
anti_join(itstopwords)
现在我有这样的事情：
text word
FIGARO cinque
FIGARO dieci
FIGARO venti
FIGARO trenta
...
我想让它回到角色名称的格式和相关的行来查看其他内容。基本上我希望文本采用与以前相同的格式，但删除了停用词。
答案 0 :(得分：9)
不是一个愚蠢的问题！答案取决于你正在尝试做什么，但如果我想通过使用purrr的map函数对其整理后的形式进行一些处理后，我希望将文本恢复到原始形式，这将是我的典型方法。
首先，让我们从原始文本转到整理格式。
library(tidyverse)
library(tidytext)
tidy_austen <- janeaustenr::austen_books() %>%
group_by(book) %>%
mutate(linenumber = row_number()) %>%
ungroup() %>%
unnest_tokens(word, text)
tidy_austen
#> # A tibble: 725,055 x 3
#> book linenumber word
#> <fctr> <int> <chr>
#> 1 Sense & Sensibility 1 sense
#> 2 Sense & Sensibility 1 and
#> 3 Sense & Sensibility 1 sensibility
#> 4 Sense & Sensibility 3 by
#> 5 Sense & Sensibility 3 jane
#> 6 Sense & Sensibility 3 austen
#> 7 Sense & Sensibility 5 1811
#> 8 Sense & Sensibility 10 chapter
#> 9 Sense & Sensibility 10 1
#> 10 Sense & Sensibility 13 the
#> # ... with 725,045 more rows
现在文字很整洁！但我们可以将它弄清楚，回到某种类似于其原始形式的东西。我通常使用来自tidyr的nest，然后来自purrr的一些map函数来处理此问题。
nested_austen <- tidy_austen %>%
nest(word) %>%
mutate(text = map(data, unlist),
text = map_chr(text, paste, collapse = " "))
nested_austen
#> # A tibble: 62,272 x 4
#> book linenumber data
#> <fctr> <int> <list>
#> 1 Sense & Sensibility 1 <tibble [3 x 1]>
#> 2 Sense & Sensibility 3 <tibble [3 x 1]>
#> 3 Sense & Sensibility 5 <tibble [1 x 1]>
#> 4 Sense & Sensibility 10 <tibble [2 x 1]>
#> 5 Sense & Sensibility 13 <tibble [12 x 1]>
#> 6 Sense & Sensibility 14 <tibble [13 x 1]>
#> 7 Sense & Sensibility 15 <tibble [11 x 1]>
#> 8 Sense & Sensibility 16 <tibble [12 x 1]>
#> 9 Sense & Sensibility 17 <tibble [11 x 1]>
#> 10 Sense & Sensibility 18 <tibble [15 x 1]>
#> # ... with 62,262 more rows, and 1 more variables: text <chr>
在这种特殊情况下，文本最后会是什么样子？
nested_austen %>%
select(text)
#> # A tibble: 62,272 x 1
#> text
#> <chr>
#> 1 sense and sensibility
#> 2 by jane austen
#> 3 1811
#> 4 chapter 1
#> 5 the family of dashwood had long been settled in sussex their estate
#> 6 was large and their residence was at norland park in the centre of
#> 7 their property where for many generations they had lived in so
#> 8 respectable a manner as to engage the general good opinion of their
#> 9 surrounding acquaintance the late owner of this estate was a single
#> 10 man who lived to a very advanced age and who for many years of his
#> # ... with 62,262 more rows
答案 1 :(得分：7)
library(tidyverse)
tidy_austen %>%
group_by(book,linenumber) %>%
summarise(text = str_c(word, collapse = " "))