podlove_graph_download_curves: Create download curve plot

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

Description

Based on a prepared dataset, this function creates a line curve diagram of downloads over time. It takes an optional grouping variable (e.g. title) as well as options for cumulative display, labeling and print output. For more finetuning options, use the podlove_baseplot() function and add geoms to your liking.

Usage

podlove_graph_download_curves(
  df_tidy_data,
  gvar = "Total",
  cumulative = TRUE,
  plot_type = "line",
  labelmethod = "last.points",
  limit = TRUE,
  legend = FALSE,
  printout = TRUE,
  ...
)

Arguments

df_tidy_data	A tidy data frame with download data, as constructed by podlove_prepare_stats_for_graph()
gvar	Optional grouping parameter (e.g. episode title), handed over to ggplot2::aes(color).
cumulative	Boolean switch to show either cumulative data (TRUE, default), or non-comulative data (FALSE)
plot_type	Sets the plot type to either line plot ("line") or ridgeline plot ("ridge").
labelmethod	Defines where should the labels be attached (at the beinning of the curves: "last.points", default, or at the end of the curves "first.points")
limit	Boolean switch to fix axis limtis (relevant when adding smoothers)
legend	Boolean switch to add a legend'
printout	Switcher to automatically print out the plot (default TRUE)
...	additional formating parameters for ggplot2::geom_line() or ggridges::geom_density_ridges.

Value

A ggplot object

See Also

podlove_prepare_stats_for_graph()

Examples

## Not run: 
# relative, daily plot by episode title, cumulative
data("podcast_example_data")
gdata <- podlove_prepare_stats_for_graph(podcast_example_data, gvar = title) 
podlove_graph_download_curves(gdata, gvar = title, cumulative = TRUE)

# relative, hourly plot by episode number, cumulative
gdata <- podlove_prepare_stats_for_graph(podcast_example_data, 
                                         gvar = ep_number, hourly = TRUE) 
podlove_graph_download_curves(gdata, gvar = ep_number, cumulative = TRUE)

# absolute, daily plot by episode title, noncumulative, with labels at the beginning
gdata <- podlove_prepare_stats_for_graph(podcast_example_data, 
                                         gvar = title, relative = FALSE) 
podlove_graph_download_curves(gdata, gvar = title, cumulative = FALSE, 
                              labelmethod = "first.points")
                              
# abolute, hourly plot by podcast client name, cumulative
gdata <- podlove_prepare_stats_for_graph(podcast_example_data, 
                                         gvar = client_name, relative = FALSE) 
podlove_graph_download_curves(gdata, gvar = client_name, cumulative = TRUE)

## End(Not run)

lordyo/podlover documentation built on Feb. 20, 2020, 5:58 p.m.