Fix CRAN issues

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: quanteda.textplots
 Title: Plots for the Quantitative Analysis of Textual Data
-Version: 0.94.3
+Version: 0.94.4
 Authors@R: 
     c( 
     person("Kenneth", "Benoit", email = "[email protected]", role = c("cre", "aut", "cph"), comment = c(ORCID = "0000-0002-0797-564X")), 
@@ -44,4 +44,4 @@ Encoding: UTF-8
 BugReports: https://github.com/quanteda/quanteda.textplots/issues
 Language: en-GB
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1

R/textplot_keyness.R

@@ -27,10 +27,10 @@
 #' \dontrun{
 #' library("quanteda")
 #' # compare Trump speeches to other Presidents by chi^2
-#' dfmat1 <- data_corpus_inaugural %>%
-#'      corpus_subset(Year > 1980) %>%
-#'      tokens(remove_punct = TRUE) %>%
-#'      tokens_remove(stopwords("en")) %>%
+#' dfmat1 <- data_corpus_inaugural |>
+#'      corpus_subset(Year > 1980) |>
+#'      tokens(remove_punct = TRUE) |>
+#'      tokens_remove(stopwords("en")) |>
 #'      dfm()
 #' dfmat1 <- dfm_group(dfmat1, groups = dfmat1$President)
 #' tstat1 <- quanteda.textstats::textstat_keyness(dfmat1, target = "Trump")
@@ -39,13 +39,13 @@
 #' textplot_keyness(tstat1, margin = 0.2, n = 10)
 #'
 #' # compare contemporary Democrats v. Republicans
-#' corp <- data_corpus_inaugural %>%
+#' corp <- data_corpus_inaugural |>
 #'     corpus_subset(Year > 1960)
 #' corp$party <- ifelse(docvars(corp, "President") %in% c("Nixon", "Reagan", "Bush", "Trump"),
 #'                      "Republican", "Democrat")
-#' dfmat2 <- corp %>%
-#'     tokens(remove_punct = TRUE) %>%
-#'     tokens_remove(stopwords("en")) %>%
+#' dfmat2 <- corp |>
+#'     tokens(remove_punct = TRUE) |>
+#'     tokens_remove(stopwords("en")) |>
 #'     dfm()
 #' tstat2 <- quanteda.textstats::textstat_keyness(dfm_group(dfmat2, groups = dfmat2$party),
 #'                                                target = "Democrat", measure = "lr")

R/textplot_network.R

@@ -34,19 +34,22 @@
 #' @examples
 #' set.seed(100)
 #' library("quanteda")
-#' toks <- data_char_ukimmig2010 %>%
-#'     tokens(remove_punct = TRUE) %>%
-#'     tokens_tolower() %>%
+#' toks <- data_char_ukimmig2010 |>
+#'     tokens(remove_punct = TRUE) |>
+#'     tokens_tolower() |>
 #'     tokens_remove(pattern = stopwords("english"), padding = FALSE)
 #' fcmat <- fcm(toks, context = "window", tri = FALSE)
-#' feat <- names(topfeatures(fcmat, 30))
-#' fcm_select(fcmat, pattern = feat) %>%
+#' feat <- colSums(fcmat) |>
+#'   sort(decreasing = TRUE) |>
+#'   head(30) |>
+#'   names()
+#' fcm_select(fcmat, pattern = feat) |>
 #'     textplot_network(min_freq = 0.5)
-#' fcm_select(fcmat, pattern = feat) %>%
+#' fcm_select(fcmat, pattern = feat) |>
 #'     textplot_network(min_freq = 0.8)
-#' fcm_select(fcmat, pattern = feat) %>%
+#' fcm_select(fcmat, pattern = feat) |>
 #'     textplot_network(min_freq = 0.8, vertex_labelcolor = rep(c('gray40', NA), 15))
-#' fcm_select(fcmat, pattern = feat) %>%
+#' fcm_select(fcmat, pattern = feat) |>
 #'     textplot_network(vertex_labelsize = 10)
 #' fcm_30 <- fcm_select(fcmat, pattern = feat)
 #' textplot_network(fcm_30,
@@ -198,7 +201,7 @@ as.igraph <- function(x, ...) UseMethod("as.igraph")
 #' # as.igraph
 #' if (requireNamespace("igraph", quietly = TRUE)) {
 #'     txt <- c("a a a b b c", "a a c e", "a c e f g")
-#'     mat <- fcm(txt)
+#'     mat <- fcm(tokens(txt))
 #'     as.igraph(mat, min_freq = 1, omit_isolated = FALSE)
 #' }
 as.igraph.fcm <- function(x, min_freq = 0.5, omit_isolated = TRUE, ...) {

R/textplot_wordcloud.R

@@ -57,11 +57,11 @@
 #' # plot the features (without stopwords) from Obama's inaugural addresses
 #' set.seed(10)
 #' library("quanteda")
-#' dfmat1 <- data_corpus_inaugural %>%
-#'     corpus_subset(President == "Obama") %>%
-#'     tokens(remove_punct = TRUE) %>%
-#'     tokens_remove(stopwords("en")) %>%
-#'     dfm() %>%
+#' dfmat1 <- data_corpus_inaugural |>
+#'     corpus_subset(President == "Obama") |>
+#'     tokens(remove_punct = TRUE) |>
+#'     tokens_remove(stopwords("en")) |>
+#'     dfm() |>
 #'     dfm_trim(min_termfreq = 3)
 #'
 #' # basic wordcloud
@@ -77,23 +77,23 @@
 #'                    color = col, rotation = FALSE)
 #'
 #' # comparison plot of Obama v. Trump
-#' dfmat2 <- data_corpus_inaugural %>%
-#'     corpus_subset(President %in% c("Obama", "Trump")) %>%
-#'     tokens(remove_punct = TRUE) %>%
-#'     tokens_remove(stopwords("en")) %>%
+#' dfmat2 <- data_corpus_inaugural |>
+#'     corpus_subset(President %in% c("Obama", "Trump")) |>
+#'     tokens(remove_punct = TRUE) |>
+#'     tokens_remove(stopwords("en")) |>
 #'     dfm()
-#' dfmat2 <- dfm_group(dfmat2, dfmat2$President) %>%
+#' dfmat2 <- dfm_group(dfmat2, dfmat2$President) |>
 #'     dfm_trim(min_termfreq = 3)
 #'
 #' textplot_wordcloud(dfmat2, comparison = TRUE, max_words = 100,
 #'                    color = c("blue", "red"))
 #'
 #' \dontrun{
 #' # for keyness
-#' tstat <- data_corpus_inaugural[c(1, 3)] %>%
-#'     tokens(remove_punct = TRUE) %>%
-#'     tokens_remove(stopwords("en")) %>%
-#'     dfm() %>%
+#' tstat <- data_corpus_inaugural[c(1, 3)] |>
+#'     tokens(remove_punct = TRUE) |>
+#'     tokens_remove(stopwords("en")) |>
+#'     dfm() |>
 #'     quanteda.textstats::textstat_keyness()
 #' textplot_wordcloud(tstat, min_count = 2)
 #' textplot_wordcloud(tstat, min_count = 2, comparison = FALSE)
@@ -367,9 +367,7 @@ wordcloud <- function(x, min_size, max_size, min_count, max_words,
 #' @param min.freq deprecated argument
 #' @param max.words deprecated argument
 #' @param random.order deprecated argument
-#' @param random.color  deprecated argument
 #' @param rot.per deprecated argument
-#' @param ordered.colors deprecated argument
 #' @param use.r.layout deprecated argument
 #' @param title.size deprecated argument
 #' @importFrom quanteda dfm_trim dfm_weight

R/textplot_xray.R

@@ -24,26 +24,28 @@
 #'   `textplot_xray`.
 #' @examples
 #' library("quanteda")
-#' corp <- corpus_subset(data_corpus_inaugural, Year > 1970)
+#' toks <- data_corpus_inaugural |>
+#'   corpus_subset(Year > 1970) |>
+#'   tokens()
 #' # compare multiple documents
-#' textplot_xray(kwic(corp, pattern = "american"))
-#' textplot_xray(kwic(corp, pattern = "american"), scale = "absolute")
+#' textplot_xray(kwic(toks, pattern = "american"))
+#' textplot_xray(kwic(toks, pattern = "american"), scale = "absolute")
 #'
 #' # compare multiple terms across multiple documents
-#' textplot_xray(kwic(corp, pattern = "america*"),
-#'               kwic(corp, pattern = "people"))
+#' textplot_xray(kwic(toks, pattern = "america*"),
+#'               kwic(toks, pattern = "people"))
 #'
 #' \dontrun{
 #' # how to modify the ggplot with different options
 #' library("ggplot2")
-#' tplot <- textplot_xray(kwic(corp, pattern = "american"),
-#'                        kwic(corp, pattern = "people"))
+#' tplot <- textplot_xray(kwic(toks, pattern = "american"),
+#'                        kwic(toks, pattern = "people"))
 #' tplot + aes(color = keyword) + scale_color_manual(values = c('red', 'blue'))
 #'
 #' # adjust the names of the document names
-#' docnames(corp) <- apply(docvars(corp, c("Year", "President")), 1, paste, collapse = ", ")
-#' textplot_xray(kwic(corp, pattern = "america*"),
-#'               kwic(corp, pattern = "people"))
+#' docnames(toks) <- apply(docvars(toks, c("Year", "President")), 1, paste, collapse = ", ")
+#' textplot_xray(kwic(toks, pattern = "america*"),
+#'               kwic(toks, pattern = "people"))
 #' }
 #' @export
 #' @keywords textplot

cran-comments.md

@@ -1,12 +1,12 @@
 # Submission notes
 
-Resubmitting to reset the flag for the noSuggests, because a package that **quanteda.textplots** suggests was off CRAN for a week.
+Fixes NOTEs warned about by CRAN on 22-Jan-2024.
 
 # Checks
 
 ## Test environments
 
-* local macOS 13.2.1, R 4.2.3
+* local macOS 14.2.1, R 4.2.3
 * Ubuntu 22.04 LTS, R 4.2.3
 * Windows release via devtools::check_win_release()
 * Windows devel via devtools::check_win_devel()

tests/testthat/test-textplot_keyness.R

@@ -4,9 +4,9 @@ pdf(file = tempfile(".pdf"), width = 10, height = 10)
 
 test_that("test textplot_keyness: show_reference works correctly ", {
     skip("until quanteda.textstats is updated")
-    presdfm <- corpus_subset(data_corpus_inaugural, President %in% c("Obama", "Trump")) %>%
-        tokens(remove_punct = TRUE) %>%
-        tokens_remove(stopwords("en")) %>%
+    presdfm <- corpus_subset(data_corpus_inaugural, President %in% c("Obama", "Trump")) |>
+        tokens(remove_punct = TRUE) |>
+        tokens_remove(stopwords("en")) |>
         dfm()
     presdfm <- dfm_group(presdfm, groups = presdfm$President)
     result <- quanteda.textstats::textstat_keyness(presdfm, target = "Trump")