unnest_tokens

Question

的對面這很可能是一個愚蠢的問題，但我GOOGLE和谷歌搜索並找不到解決方案。我認爲這是因爲我不知道用我的問題來搜索的正確方法。

我有一個數據框，我已經在R中轉換爲整潔的文本格式來擺脫停用詞。我現在想將那個數據框'不整潔'回到原來的格式。

unnest_tokens的反向/反向命令是什麼？

編輯：這裏是我正在使用的數據的樣子。我試圖複製西爾格和羅賓遜的書Tidy Text的分析，但使用意大利歌劇的librettos。

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! 

我把它變成整潔的文本，所以我可以擺脫停止詞：

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) 

現在我有這樣的事情：

text word 
FIGARO cinque 
FIGARO dieci 
FIGARO venti 
FIGARO trenta 
... 

我想它找回來轉換爲字符名稱和相關行的格式來查看其他事物。基本上，我希望文本的格式與之前的格式相同，但要刪除停用詞。

Answer 1

不是一個愚蠢的問題！答案取決於你正在嘗試做什麼，但如果我想通過使用來自purrr的map函數在經過一些處理後的整理表單中恢復原始形式，那麼這將是我典型的方法。

首先，讓我們從原始文本轉到整理格式。

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 

文本現在是整潔！但是我們可以把它弄亂，回到某種原始形式。我通常使用來自tidyr的nest來處理這個問題，然後使用purrr的一些map函數。

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> 

是什麼文字看起來像在年底，在這種特殊情況下？

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