Fix R CMD check warnings

Add missing parameter in documentation and fixed wrong package name. Also deleted explicit calls to base:: functions, as they are redundant (only non-base functions need to be prefixed with their package name).

Author: ccamara

R/caption_groups.R

@@ -13,6 +13,7 @@
 #' @param edits_tbl an optional raw edits table used when 'df' is not supplied.
 #'   Should contain 'user', 'date', 'action', 'key', 'tag'..
 #' @param tags_tbl an optional tags summary with columns 'key' and 'n' (counts)
+#' @param max_names maximum number of names to include in the caption
 #' #'
 #' @returns a length-1 character vector containing the caption.
 #' @export
@@ -39,26 +40,26 @@ caption_group <- function(df = NULL,
   # ---- contribution frequency (changesets/day or edits/active-day) ----
   per_day <- NA_real_
   if (!is.null(contribs_tbl) &&
-      all(c("changesets", "first_edit", "last_edit") %in% base::names(contribs_tbl))) {
-    rng  <- base::range(c(contribs_tbl$first_edit, contribs_tbl$last_edit), na.rm = TRUE)
-    days <- as.numeric(stats::diff(rng)) + 1
-    total_changesets <- base::sum(contribs_tbl$changesets, na.rm = TRUE)
+      all(c("changesets", "first_edit", "last_edit") %in% names(contribs_tbl))) {
+    rng  <- range(c(contribs_tbl$first_edit, contribs_tbl$last_edit), na.rm = TRUE)
+    days <- as.numeric(diff(rng)) + 1
+    total_changesets <- sum(contribs_tbl$changesets, na.rm = TRUE)
     per_day <- ifelse(days > 0, total_changesets / days, total_changesets)
-  } else if (!is.null(df) && "date" %in% base::names(df)) {
+  } else if (!is.null(df) && "date" %in% names(df)) {
     # edits per active day
     per_day <- nrow(df) / dplyr::n_distinct(df$date)
   }
 
   freq <- dplyr::case_when(
-    base::is.na(per_day) ~ "active",
+    is.na(per_day) ~ "active",
     per_day < 1          ~ "occasional",
     per_day < 10         ~ "frequent",
     TRUE                 ~ "heavy"
   )
 
   # ---- activity type (creators / repairers / improvers) ----
   type_word <- "contributors"
-  if (!is.null(df) && "action" %in% base::names(df)) {
+  if (!is.null(df) && "action" %in% names(df)) {
     top_act <- df |>
       dplyr::count(action, name = "n") |>
       dplyr::arrange(dplyr::desc(.data$n)) |>
@@ -71,62 +72,62 @@ caption_group <- function(df = NULL,
       delete = "improvers", remove = "improvers",
       .default = "contributors"
     )
-  } else if (!is.null(contribs_tbl) && all(c("adds","mods","dels") %in% base::names(contribs_tbl))) {
-    sums <- base::colSums(contribs_tbl[, c("adds","mods","dels")], na.rm = TRUE)
-    type_word <- c(adds="creators", mods="repairers", dels="improvers")[base::names(base::which.max(sums))]
+  } else if (!is.null(contribs_tbl) && all(c("adds","mods","dels") %in% names(contribs_tbl))) {
+    sums <- colSums(contribs_tbl[, c("adds","mods","dels")], na.rm = TRUE)
+    type_word <- c(adds="creators", mods="repairers", dels="improvers")[names(which.max(sums))]
   }
 
   # ---- experience level (avg edits per user) ----
   avg_edits <- NA_real_
-  if (!is.null(df) && "user" %in% base::names(df)) {
+  if (!is.null(df) && "user" %in% names(df)) {
     avg_edits <- df |>
       dplyr::count(.data$user, name = "n") |>
-      dplyr::summarise(m = base::mean(.data$n)) |>
+      dplyr::summarise(m = mean(.data$n)) |>
       dplyr::pull(.data$m)
-  } else if (!is.null(contribs_tbl) && "total_edits" %in% base::names(contribs_tbl)) {
-    avg_edits <- base::mean(contribs_tbl$total_edits, na.rm = TRUE)
+  } else if (!is.null(contribs_tbl) && "total_edits" %in% names(contribs_tbl)) {
+    avg_edits <- mean(contribs_tbl$total_edits, na.rm = TRUE)
   }
-  exp_level <- if (base::is.na(avg_edits)) "hobbyists" else dplyr::case_when(
+  exp_level <- if (is.na(avg_edits)) "hobbyists" else dplyr::case_when(
     avg_edits < 50   ~ "hobbyists",
     avg_edits < 500  ~ "pro-ams",
     TRUE             ~ "professionals"
   )
 
   # ---- interests (top 3 tag keys) ----
   top_tags <- character(0)
-  if (!is.null(tags_tbl) && all(c("key","n") %in% base::names(tags_tbl))) {
+  if (!is.null(tags_tbl) && all(c("key","n") %in% names(tags_tbl))) {
     top_tags <- tags_tbl |>
       dplyr::arrange(dplyr::desc(.data$n)) |>
       dplyr::slice_head(n = 3) |>
       dplyr::pull(.data$key)
-  } else if (!is.null(df) && any(c("key","tag") %in% base::names(df))) {
-    tag_col <- if ("key" %in% base::names(df)) "key" else "tag"
+  } else if (!is.null(df) && any(c("key","tag") %in% names(df))) {
+    tag_col <- if ("key" %in% names(df)) "key" else "tag"
     top_tags <- df |>
       dplyr::count(.data[[tag_col]], name = "n") |>
       dplyr::arrange(dplyr::desc(.data$n)) |>
       dplyr::slice_head(n = 3) |>
       dplyr::pull(1)
   }
-  tags_text <- if (base::length(top_tags)) base::paste(top_tags, collapse = ", ") else "a variety of features"
+  tags_text <- if (length(top_tags)) paste(top_tags, collapse = ", ") else "a variety of features"
 
   # ---- homogeneity (Gini on edits/user) ----
   gini <- NA_real_
-  if (!is.null(df) && "user" %in% base::names(df)) {
+  if (!is.null(df) && "user" %in% names(df)) {
     v <- df |>
       dplyr::count(.data$user, name = "n") |>
       dplyr::pull(.data$n) |>
-      base::sort()
-    if (base::length(v)) {
-      n <- base::length(v)
-      gini <- (2 * base::sum(seq_len(n) * v) / base::sum(v) / n) - (n + 1) / n
+      sort()
+    if (length(v)) {
+      n <- length(v)
+      gini <- (2 * sum(seq_len(n) * v) / sum(v) / n) - (n + 1) / n
     }
   }
-  homog <- if (base::is.na(gini)) "diverse" else if (gini > 0.6) "homogeneous"
+  homog <- if (is.na(gini)) "diverse" else if (gini > 0.6) "homogeneous"
   else if (gini > 0.4) "somewhat concentrated" else "diverse"
 
   # ---- final caption ----
   glue::glue(
     "This is a {homog} group of {freq} {type_word}, mostly {exp_level}, with interests in {tags_text}."
   ) |>
-    base::as.character()
+    as.character()
 }