R: tidy text dataset - tibble: Difference between revisions
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| Line 35: | Line 35: | ||
unnest_tokens(word, text) | unnest_tokens(word, text) | ||
tidy_books | 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() | |||
==Pranala Menarik== | ==Pranala Menarik== | ||
* [[R]] | * [[R]] | ||
Revision as of 02:21, 31 October 2018
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()