R/plot_intro.r

In DataExplorer: Automate Data Exploration and Treatment

#' Plot introduction
#'
#' Plot basic information (from \link{introduce}) for input data.
#' @param data input data
#' @param geom_label_args a list of other arguments to \link{geom_label}
#' @param title plot title
#' @param ggtheme complete ggplot2 themes. The default is \link{theme_gray}.
#' @param theme_config a list of configurations to be passed to \link{theme}.
#' @return invisibly return the ggplot object
#' @keywords plot_intro
#' @import ggplot2
#' @importFrom stats reorder
#' @importFrom scales comma percent
#' @export
#' @seealso \link{introduce}
#' @examples
#' plot_intro(airquality)
#' plot_intro(iris)

plot_intro <- function(data, geom_label_args = list(), title = NULL, ggtheme = theme_gray(), theme_config = list()) {
  ## Declare variable first to pass R CMD check
  id <- dimension <- variable <- value <- NULL
  ## Get intro data
  intro <- introduce(data)
  memory_usage <- intro[["memory_usage"]]
  class(memory_usage) <- "object_size"
  memory_usage_string <- format(memory_usage, unit = "auto")
  intro2 <- data.table(
    "id" = seq.int(5L),
    "dimension" = c(rep("column", 3L), "row", "observation"),
    "variable" = c("Discrete Columns", "Continuous Columns", "All Missing Columns", "Complete Rows", "Missing Observations"),
    "value" = c(
      intro[["discrete_columns"]] / intro[["columns"]],
      intro[["continuous_columns"]] / intro[["columns"]],
      intro[["all_missing_columns"]] / intro[["columns"]],
      intro[["complete_rows"]] / intro[["rows"]],
      intro[["total_missing_values"]] / intro[["total_observations"]]
    )
  )
  ## Create ggplot object
  output <- ggplot(intro2, aes(x = reorder(variable, -id), y = value, fill = dimension)) +
    geom_bar(stat = "identity") +
    scale_y_continuous(labels = percent) +
    scale_fill_discrete("Dimension") +
    coord_flip() +
    labs(x = "Metrics", y = "Value") +
    guides(fill = guide_legend(override.aes = aes(label = "")))
  geom_label_args_list <- list("mapping" = aes(label = percent(value)))
  output <- output +
    do.call("geom_label", c(geom_label_args_list, geom_label_args))
  ## Plot object
  class(output) <- c("single", class(output))
  plotDataExplorer(
    plot_obj = output,
    title = ifelse(is.null(title), paste("Memory Usage:", memory_usage_string), title),
    ggtheme = ggtheme,
    theme_config = theme_config
  )
}