CRAN v5.2.9

DESCRIPTION

@@ -1,14 +1,14 @@
 Package: lares
 Type: Package
 Title: Analytics & Machine Learning Sidekick
-Version: 5.2.8.9006
+Version: 5.2.9
 Authors@R: c(
     person("Bernardo", "Lares", , "[email protected]", c("aut", "cre")))
 Maintainer: Bernardo Lares <[email protected]>
 Description: Auxiliary package for better/faster analytics, visualization, data mining, and machine
     learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling,
-    Exploratory, API, and Scrapper, it helps the analyst or data scientist to get quick and robust
-    results, without the need of repetitive coding or extensive R programming skills.
+    MMM, Exploratory, API, and Scrapper, it helps the analyst or data scientist to get quick and 
+    robust results, without the need of repetitive coding or advanced R programming skills.
 Depends:
     R (>= 3.5.0)
 Imports:

R/audio.R

@@ -129,7 +129,7 @@ get_mp3 <- function(id,
   if (open) {
     if (file.exists(mp3_file)) {
       message("Opening file: ", mp3_file)
-      browseURL(mp3_file) 
+      browseURL(mp3_file)
     } else {
       warning("Can't open file; possibly due to strange characters in title: ", mp3_file)
     }
@@ -139,7 +139,7 @@ get_mp3 <- function(id,
     if (file.exists(mp3_file)) {
       message("Deleting file: ", mp3_file)
       if (open) Sys.sleep(5)
-      file.remove(mp3_file) 
+      file.remove(mp3_file)
     } else {
       warning("Can't delete file; possibly due to strange characters in title: ", mp3_file)
     }

R/robyn.R

@@ -592,8 +592,10 @@ robyn_performance <- function(
   if (carryovers) {
     try_require("Robyn")
     carrov <- robyn_immcarr(
-      InputCollect, OutputCollect, solID = solID, 
-      start_date = start_date, end_date = end_date, ...) %>%
+      InputCollect, OutputCollect,
+      solID = solID,
+      start_date = start_date, end_date = end_date, ...
+    ) %>%
       filter(.data$type == "Carryover")
     mean_carryovers <- data.frame(
       channel = carrov$rn,

R/scrabble.R

@@ -108,7 +108,7 @@ scrabble_score <- function(words, scores.df) {
 #' @family Scrabble
 #' @param lang Character. Any of "en","es" or "chars". Set to NULL
 #' if you wish to skip this step (and use \code{words} parameter in
-#' \code{scrabble_words()} instead). The "chars" parameter will 
+#' \code{scrabble_words()} instead). The "chars" parameter will
 #' score the number of characters a word has.
 #' @return data.frame with tiles and scores for each alphabet letter.
 #' @examples
@@ -133,15 +133,19 @@ scrabble_points <- function(lang) {
         tolower(LETTERS)[1:14], intToUtf8(241),
         tolower(LETTERS)[15:length(LETTERS)]
       ),
-      scores = c(1, 3, 2, 2, 1, 4, 3, 4, 1, 8, 10, 1, 3, 1, 
-                 8, 1, 3, 5, 1, 1, 1, 2, 4, 10, 10, 5, 10)
+      scores = c(
+        1, 3, 2, 2, 1, 4, 3, 4, 1, 8, 10, 1, 3, 1,
+        8, 1, 3, 5, 1, 1, 1, 2, 4, 10, 10, 5, 10
+      )
     )
   }
   if (lang == "en") {
     scores <- data.frame(
       tiles = tolower(LETTERS),
-      scores = c(1, 4, 4, 2, 1, 4, 3, 3, 1, 10, 5, 2, 4, 
-                 2, 1, 4, 10, 1, 1, 1, 2, 5, 4, 8, 3, 10)
+      scores = c(
+        1, 4, 4, 2, 1, 4, 3, 3, 1, 10, 5, 2, 4,
+        2, 1, 4, 10, 1, 1, 1, 2, 5, 4, 8, 3, 10
+      )
     )
   }
   if (lang %in% c("chars", "unique")) {
@@ -370,17 +374,17 @@ scrabble_words <- function(tiles = "",
   }
   # Exclude letters from positions (Wordle)
   if (exclude_here[1] != "") {
-   for (eh in exclude_here) {
-    pos_tiles <- str_split_merge(tolower(eh))
-    for (i in seq_along(pos_tiles)) {
-      these <- str_split(pos_tiles, "\\|")[i][[1]]
-      if (!any(these %in% letters)) next
-      located <- stringr::str_locate_all(words, pos_tiles[i])
-      these <- !unlist(lapply(located, function(x) sum(x[, 1] == i) > 0))
-      words <- words[these]
-      .temp_print(length(words))
+    for (eh in exclude_here) {
+      pos_tiles <- str_split_merge(tolower(eh))
+      for (i in seq_along(pos_tiles)) {
+        these <- str_split(pos_tiles, "\\|")[i][[1]]
+        if (!any(these %in% letters)) next
+        located <- stringr::str_locate_all(words, pos_tiles[i])
+        these <- !unlist(lapply(located, function(x) sum(x[, 1] == i) > 0))
+        words <- words[these]
+        .temp_print(length(words))
+      }
     }
-   } 
   }
 
   .temp_print(length(words), last = TRUE)
@@ -391,7 +395,7 @@ scrabble_words <- function(tiles = "",
         mutate(length = str_length(.data$word)) %>%
         arrange(desc(.data$scores), desc(.data$length))
     } else {
-      done <- scrabble_score(words, scores.df) 
+      done <- scrabble_score(words, scores.df)
     }
     if (sum(done$scores) == 0) done$scores <- NULL
     return(as_tibble(done))

R/trees.R

@@ -7,9 +7,9 @@
 #' @family Exploratory
 #' @family Visualization
 #' @inheritParams h2o_automl
-#' @inherit rpart::rpart
-#' @inherit rpart::rpart.control
-#' @inherit rpart.plot::rpart.plot
+#' @inheritParams rpart::rpart
+#' @inheritParams rpart::rpart.control
+#' @inheritParams rpart.plot::rpart.plot
 #' @param df Data frame
 #' @param max Integer. Maximal depth of the tree.
 #' @param min Integer. The minimum number of observations that must