Clarification on arg order

DESCRIPTION

@@ -74,4 +74,4 @@ Config/testthat/edition: 3
 Encoding: UTF-8
 LazyData: TRUE
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.2
+RoxygenNote: 7.2.3

R/unnest_tokens.R

@@ -70,13 +70,13 @@
 #' d
 #'
 #' d %>%
-#'   unnest_tokens(word, txt)
+#'   unnest_tokens(output = word, input = txt)
 #'
 #' d %>%
-#'   unnest_tokens(sentence, txt, token = "sentences")
+#'   unnest_tokens(output = sentence, input = txt, token = "sentences")
 #'
 #' d %>%
-#'   unnest_tokens(ngram, txt, token = "ngrams", n = 2)
+#'   unnest_tokens(output = ngram, input = txt, token = "ngrams", n = 2)
 #'
 #' d %>%
 #'   unnest_tokens(chapter, txt, token = "regex", pattern = "Chapter [\\\\d]")

vignettes/tidytext.Rmd

@@ -49,12 +49,12 @@ original_books <- austen_books() %>%
 original_books
 ```
 
-To work with this as a tidy dataset, we need to restructure it as **one-token-per-row** format. The `unnest_tokens` function is a way to convert a dataframe with a text column to be one-token-per-row:
+To work with this as a tidy dataset, we need to restructure it as **one-token-per-row** format. The `unnest_tokens` function is a way to convert a dataframe with a text column to be one-token-per-row. Here let's tokenize to a new `word` column from the existing `text` column:
 
 ```{r}
 library(tidytext)
 tidy_books <- original_books %>%
-  unnest_tokens(word, text)
+  unnest_tokens(output = word, input = text)
 
 tidy_books
 ```
@@ -188,7 +188,7 @@ is a sad sentence, not a happy one, because of negation. The [Stanford CoreNLP](
 
 ```{r}
 PandP_sentences <- tibble(text = prideprejudice) %>% 
-  unnest_tokens(sentence, text, token = "sentences")
+  unnest_tokens(output = sentence, input = text, token = "sentences")
 ```
 
 Let's look at just one.