(v0.7.1.9016) deps

R/first_isolate.R

@@ -70,7 +70,7 @@
 #' @keywords isolate isolates first
 #' @seealso \code{\link{key_antibiotics}}
 #' @export
-#' @importFrom dplyr arrange_at lag between row_number filter mutate arrange pull
+#' @importFrom dplyr arrange_at lag between row_number filter mutate arrange pull ungroup
 #' @importFrom crayon blue bold silver
 #' @return Logical vector
 #' @source Methodology of this function is based on: \strong{M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition}, 2014, \emph{Clinical and Laboratory Standards Institute (CLSI)}. \url{https://clsi.org/standards/products/microbiology/documents/m39/}.

R/mic.R

@@ -51,6 +51,8 @@
 #'
 #' plot(mic_data)
 #' barplot(mic_data)
+#' 
+#' library(clean)
 #' freq(mic_data)
 as.mic <- function(x, na.rm = FALSE) {
   if (is.mic(x)) {

R/mo.R

@@ -1412,6 +1412,7 @@ print.mo <- function(x, ...) {
 
 #' @exportMethod summary.mo
 #' @importFrom dplyr n_distinct
+#' @importFrom clean freq top_freq
 #' @export
 #' @noRd
 summary.mo <- function(object, ...) {

R/resistance_predict.R

@@ -58,7 +58,7 @@
 #' @rdname resistance_predict
 #' @export
 #' @importFrom stats predict glm lm
-#' @importFrom dplyr %>% pull mutate mutate_at n group_by_at summarise filter filter_at all_vars n_distinct arrange case_when n_groups transmute
+#' @importFrom dplyr %>% pull mutate mutate_at n group_by_at summarise filter filter_at all_vars n_distinct arrange case_when n_groups transmute ungroup
 #' @inheritSection AMR Read more on our website!
 #' @examples
 #' x <- resistance_predict(septic_patients, col_ab = "AMX", year_min = 2010)

R/rsi.R

@@ -50,7 +50,7 @@
 #' @return Ordered factor with new class \code{rsi}
 #' @keywords rsi
 #' @export
-#' @importFrom dplyr %>%
+#' @importFrom dplyr %>% desc arrange filter 
 #' @seealso \code{\link{as.mic}}
 #' @inheritSection AMR Read more on our website!
 #' @examples
@@ -73,6 +73,8 @@
 #'
 #' plot(rsi_data)    # for percentages
 #' barplot(rsi_data) # for frequencies
+#' 
+#' library(clean)
 #' freq(rsi_data)    # frequency table with informative header
 #'
 #' # using dplyr's mutate