#' @title Make An Iris-like Dataset
#' @description Make an \code{tbl} object that resembles the \code{iris} dataset.
#' THis object is not included in the package; instead, it is downloaded from
#' an external source and saved in the \code{extdata/} directory.
#' @param path the file path where this file should be saved
#' @return a \code{tibble} object
#' @export
make_iris_external <- function(path) {
set.seed(90201)
iris_url <- "https://gist.githubusercontent.com/curran/a08a1080b88344b0c8a7/raw/d546eaee765268bf2f487608c537c05e22e4b221/iris.csv"
iris_external <- readr::read_csv(iris_url,col_types = "nnnnc") %>%
dplyr::rename(Species = species,
Sepal.Length = sepal_length,
Sepal.Width = sepal_width,
Petal.Length = petal_length,
Petal.Width = petal_width) %>%
dplyr::mutate_if(is.numeric, ~ round(rnorm(n = 150, mean = mean(.x), sd = sd(.x)),2)) # resample the numeric fields
writexl::write_xlsx(iris_external, path = path)
return(iris_external)
}
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