R/base-datasets.R

In abdala9512/dareML: Data repository for Machine learning

# Iris dataset ------------------------------------------------------------

#' Call iris dataset
#'
#' Ideal dataset for clustering, multi-class
#' problems (tree based models) and EDA.
#'
#' @return \code{iris} dataset with the following columns:
#' \itemize{
#'   \item Sepal.Length
#'   \item Sepal.Width
#'   \item Petal.Length
#'   \item Petal.Width
#'   \item Species
#' }
#' @export
#'
#' @author Miguel Arquez
#'
#' @examples
#' my_iris_df <- getIris()
getIris <-
function(){
  irisDF <- iris
  cat("Classic Iris dataset imported.")
  calculateSize(irisDF)
  return(irisDF)
}


#' Load Iris dataset in the current environment
#'
#' Load the iris dataset as a \code{data.frame} object called
#' \code{irisDF}
#'
#' @return
#' @export
#'
#' @examples
#' loadIris()
loadIris <-
function(){
  irisDF <<- iris
  cat("Classic Iris dataset loaded.")
}


# Housing dataset ---------------------------------------------------------


#' Retrieve Housing dataset
#'
#' @param ...
#'
#' @return
#' @export
#'
#' @examples
getHousingDataSet <-
function(...){
  housing <- read.csv("https://raw.githubusercontent.com/ageron/handson-ml/master/datasets/housing/housing.csv", ...)
  cat("Housing dataset imported")
  return(housing)
}


#' Housing dataset loaded in current environment
#'
#' @param ...
#'
#' @return
#' @export
#'
#' @examples
loadHousingDataSet <-
function(...){
  housing <<- read.csv("https://raw.githubusercontent.com/ageron/handson-ml/master/datasets/housing/housing.csv", ...)
  cat("Housing dataset imported")
}



#' Title
#'
#' @param ...
#'
#' @return
#' @export
#'
#' @examples
getMNIST <-
function(...){
  msnist <- read.csv("https://datahub.io/machine-learning/mnist_784/r/mnist_784.csv")
  cat("MSNIST dataset imported")
  return(mnist)
}




#' Title
#'
#' @param ...
#'
#' @return
#' @export
#'
#' @examples
loadMSNIST <-
function(...){
  mnist <<- read.csv("https://datahub.io/machine-learning/mnist_784/r/mnist_784.csv")
  cat("MNIST Dataset loaded")
  calculateSize(mnist)
}