R/podlove_baseplot_multi.R

In lordyo/podlover: Collects, Cleans and Analyzes Podcast Download Data from Podlove Publisher

#' Construct a basic podcast download ridgeline plot
#'
#' Creates the basic ridge line plot to display Podlove download data over time, using
#'     \code{ggplot2()}. Includes  an optional grouping variable and a switcher between
#'     cumulative/non-cumulative data. 
#'
#' @param  df_tidy_data A tidy data frame with download data, as constructed
#'     by \code{podlove_prepare_stats_for_graph()}
#' @param gvar Optional grouping parameter string (e.g. "title"), handed over
#'     to \code{ggplot2::aes_string(color)}. Must correspond to the data structure
#'     in \code{df_tidy_data}.
#' @param cumulative Boolean switch to show either cumulative data (TRUE, default),
#'     or non-comulative data (FALSE) 
#' @param ... Additional parameters to be handed over to \code{ggplot2::geom_density_ridge()} 
#' 
#' @return A ggplot2 plot 
#' 
#' @examples 
#' \dontrun{
#' #prepare data
#' gdata <- podlove_prepare_stats_for_graph(podcast_example_data, gvar = title)
#' 
#' # line graph with cumulative data (grouped by title)
#' podlove_baseplot(plot_data, gvar = "title", cumulative = TRUE)
#' 
#' # line graph with non-cumulative data
#' podlove_baseplot(plot_data, gvar = "title", cumulative = FALSE)
#' 
#' # line graph with non-cumulative data and additional formating paramters
#' gdata <- podlove_prepare_stats_for_graph(podcast_example_data)
#' podlove_baseplot(plot_data, cumulative = TRUE,
#'                  color = "white", fill = "#6699CC", scale = 2)
#' }
#' 
#' @importFrom magrittr %>% 
#' @importFrom ggplot2 ggplot 

podlove_baseplot_multi <- function(df_tidy_data,
                                   gvar = "Total",
                                   cumulative = TRUE,
                                   ...) {
  
  # switcher for cumulative data (use listeners or listeners-total)
  if (cumulative == TRUE) {
    
    g_dl_curves <- ggplot2::ggplot(df_tidy_data,
                                   ggplot2::aes(x = time, 
                                                y = {{gvar}}, 
                                                height = listeners_total))
    
  } else {
    
    g_dl_curves <- ggplot2::ggplot(df_tidy_data,
                                   ggplot2::aes(x = time, 
                                                y = {{gvar}}, 
                                                height = listeners))
  }
  
  
  # add ridgeline plot
  g_dl_curves <- g_dl_curves + ggridges::geom_density_ridges(stat = "identity",
                                                             ...)
  
  g_dl_curves
  
}