#' Documentation of Tidying Original Crime Data
#'
#' The documentation that records the tidying of crime data, as retrieved from Kaggle, in order to fit SAfeR functionality.
#'
#'
#'
#' @format A data frame with 339471 records and 5 variables:
#' \describe{
#' \item{Province}{South African Province;}
#' \item{Station}{Police Station in Respective Province;}
#' \item{Category}{Types of Crime Committed;}
#' \item{Year}{Year in which Crimes were Committed;}
#' \item{Crime_Rate}{Number of Crimes Committed in a Given Year;}
#' }
#' @export
#' @source
#' These data were downloaded from Kaggle user Stephan Wessels, retrievable here: https://www.kaggle.com/slwessels/crime-statistics-for-south-africa.
#' @examples
#' mean_crime("Cape Town Central", data = crime)
#'
if(FALSE) {
# Tidy the dataset by turning column values into row values
crime <- gather(crime, Year, Crime_Rate, -Province, -Station, -Category)
# Fix row values into single years
crime$Year <- substr(crime$Year, 2, 5) %>% as.numeric()
# Save data into repository
devtools::use_data(crime, overwrite = TRUE)
}
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