View source for R: tidy text dataset - tibble

==Text Vector==

 text <- c("Because I could not stop for Death -",
           "He kindly stopped for me -",
           "The Carriage held but just Ourselves -",
           "and Immortality")
 text


==Tidy Text Dataset==

 install.packages("dplyr")
 library(dplyr)
 text_df <- data_frame(line = 1:4, text = text)
 text_df


==Tidy Text Novel==

 library(janeaustenr)
 library(dplyr)
 library(stringr)
 original_books <- austen_books() %>%
    group_by(book) %>%
    mutate(linenumber = row_number(),
           chapter = cumsum(str_detect(text, regex("^chapter [\\divxlc]",
                                             ignore_case = TRUE)))) %>%
    ungroup()
 original_books

Buat menjadi one-token-per-row

 library(tidytext)
 tidy_books <- original_books %>%
               unnest_tokens(word, text)
 tidy_books

Buang stopwords

 data(stop_words)
 tidy_books <- tidy_books %>%
               anti_join(stop_words)

Word Count

 tidy_books %>%
     count(word, sort = TRUE)

Plot

 library(ggplot2)
 tidy_books %>%
     count(word, sort = TRUE) %>%
 filter(n > 600) %>%
 mutate(word = reorder(word, n)) %>%
 ggplot(aes(word, n)) +
        geom_col() +
        xlab(NULL) +
        coord_flip()


==Tidy Text gutenbergr==

 install.packages("gutenbergr")
 library(gutenbergr)


 hgwells <- gutenberg_download(c(35, 36, 5230, 159))
 tidy_hgwells <- hgwells %>%
                 unnest_tokens(word, text) %>%
 anti_join(stop_words)
 tidy_hgwells %>%
     count(word, sort = TRUE)


 bronte <- gutenberg_download(c(1260, 768, 969, 9182, 767))
 tidy_bronte <- bronte %>%
                unnest_tokens(word, text) %>%
 anti_join(stop_words)
 tidy_bronte %>%
     count(word, sort = TRUE)

Compare 3 text

 library(tidyr)
 frequency <- bind_rows(mutate(tidy_bronte, author = "Brontë Sisters"),
                        mutate(tidy_hgwells, author = "H.G. Wells"),
                        mutate(tidy_books, author = "Jane Austen")) %>%
    mutate(word = str_extract(word, "[a-z']+")) %>%
    count(author, word) %>%
    group_by(author) %>%
    mutate(proportion = n / sum(n)) %>%
    select(-n) %>%
    spread(author, proportion) %>%
    gather(author, proportion, `Brontë Sisters`:`H.G. Wells`)

Plot

 library(scales)
 # expect a warning about rows with missing values being removed
 ggplot(frequency, aes(x = proportion, y = `Jane Austen`,
                   color = abs(`Jane Austen` - proportion))) +
        geom_abline(color = "gray40", lty = 2) +
        geom_jitter(alpha = 0.1, size = 2.5, width = 0.3, height = 0.3) +
        geom_text(aes(label = word), check_overlap = TRUE, vjust = 1.5) +
        scale_x_log10(labels = percent_format()) +
        scale_y_log10(labels = percent_format()) +
        scale_color_gradient(limits = c(0, 0.001),
             low = "darkslategray4", high = "gray75") +
             facet_wrap(~author, ncol = 2) +
             theme(legend.position="none") +
        labs(y = "Jane Austen", x = NULL)

==Pranala Menarik==

* [[R]]