added @importFrom magrittr %>%

DESCRIPTION

@@ -25,4 +25,4 @@ Collate:
     'spanish.R'
 RoxygenNote: 6.1.1
 Suggests: testthat, tidyr
-Depends: magrittr,xml2
+

NAMESPACE

@@ -3,3 +3,4 @@
 export(geocode_cadastral)
 export(to_number)
 export(to_words)
+importFrom(magrittr,"%>%")

R/cadastral_references-data.R

@@ -1,45 +1,45 @@
-#' Cadastral references test data
-#'
-#' Randomly selected data from catastro to test geocode_cadastral function
-#'
-#' @docType data
-#'
-#' @usage data(cadastral_references)
-#'
-#' @format A data frame.
-#'
-#' @keywords datasets
-#'
-#' @references Catastro. Ministerio de Hacienda y función pública.
-#' (\href{http://www.catastro.meh.es/}{Catastro})
-#'
-#' @source \href{http://www.catastro.meh.es/}{Sede Electrónica del Catastro}
-#'
-#' @examples
-#' ## source is cadastral reference number ##
-#'
-#' geocode_cadastral("0636105UF3403N", parse_files = FALSE)
-#'
-#' ## Use lapply to geocode cadastral references from dataframe columns.
-#'
-#' cadastral_references$new <- lapply(cadastral_references$cadref1, geocode_cadastral)
-#'
-#' ## separate previously generated "new" data into columns usign tidyr
-#'
-#' library(tidyr)
-#' separate(cadastral_references, new, into = c('longitude','latitude'), sep = "," )
-#'
-#' ## source is folder. A loop is needed to process each kml file ##
-#'
-#' \dontrun{
-#' files <- list.files("folder", full.names = T)
-#'
-#' for (f in files) {
-#'  coords <- geocode_cadastral(f, parse_files = TRUE)
-#'  d <- as.data.frame(rbind(d , as.data.frame(coords, stringsAsFactors = F )))
-#' }
-#'
-#'# separate lat/lon into columns if you prefer using tidyr
-#' d <- tidyr::separate(coords, into = c("longitude","latitude"), sep = "," )
-#'}
-"cadastral_references"
+#' Cadastral references test data
+#'
+#' Randomly selected data from catastro to test geocode_cadastral function
+#'
+#' @docType data
+#'
+#' @usage data(cadastral_references)
+#'
+#' @format A data frame.
+#'
+#' @keywords datasets
+#'
+#' @references Catastro. Ministerio de Hacienda y función pública.
+#' (\href{http://www.catastro.meh.es/}{Catastro})
+#'
+#' @source \href{http://www.catastro.meh.es/}{Sede Electrónica del Catastro}
+#'
+#' @examples
+#' \dontrun{
+#' ## source is cadastral reference number ##
+#'
+#'  geocode_cadastral("0636105UF3403N", parse_files = FALSE)
+#'
+#' ## Use lapply to geocode cadastral references from dataframe columns.
+#'
+#'  cadastral_references$new <- lapply(cadastral_references$cadref1, geocode_cadastral)
+#'
+#' ## separate previously generated "new" data into columns usign tidyr
+#'
+#' library(tidyr)
+#' separate(cadastral_references, new, into = c('longitude','latitude'), sep = "," )
+#'
+#' ## source is folder. A loop is needed to process each kml file ##
+#'
+#' files <- list.files("folder", full.names = T)
+#'
+#' for (f in files) {
+#'  coords <- geocode_cadastral(f, parse_files = TRUE)
+#'  d <- as.data.frame(rbind(d , as.data.frame(coords, stringsAsFactors = F )))
+#' }
+#'
+#'# separate lat/lon into columns if you prefer using tidyr
+#' d <- tidyr::separate(coords, into = c("longitude","latitude"), sep = "," )
+#'}
+"cadastral_references"

R/geocode_cadastral.R

@@ -36,6 +36,7 @@
 #' # d <- tidyr::separate(coords, into = c("longitude","latitude"), sep = "," )
 #'}
 #' @name geocode_cadastral
+#' @importFrom magrittr %>%
 #' @export
 
 

R/to_number.R

@@ -9,11 +9,11 @@
 #' @examples
 #' to_number("mil trescientos noventa y dos")
 #'
-#' Example table is provided: cantidades
+#' # Example table is provided: cantidades
 #' cantidades$var3 <- lapply(cantidades$var2, to_number)
-#'
 #' @name to_number
 #' @keywords money, currency, euros, translate
+#' @importFrom magrittr %>%
 #' @export
 
 

R/to_words.R

@@ -7,6 +7,7 @@
 #' @param x A valid integer amount.
 #' @return A string for the same integer number in spanish.
 #' @name to_words
+#' @importFrom magrittr %>%
 #' @export