podlove_graph_performance: Create performance grid for podcast episodes

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

Description

Based on data created by podlove_performance_stats, plot all episodes on an X/Y grid, X showing long-term average downloads, Y showing average downloads during launch. Horizontal and vertcal lines show median values. This allows for categorization of epsisodes into performance clusters. Note that you won't see episodes which are younger than your post_launch limit.

Usage

podlove_graph_performance(df_perfstats, label, legend, printout = TRUE)

Arguments

df_perfstats	a tidy data frame created by performance_stats()
label	Unquoted, episode-related variable to use for labelling. By default, podlove_performance_stats creates the options title, ep_number (default) and ep_num_title. Use label = "" or leave argument away to display no label
legend	Unquoted, episode-related variable to use in a explanatory legend next to the performance graph.
printout	Switcher to automatically print out the plot (default TRUE)

Value

A ggplot object

Examples

## Not run: 
# plot episode performance stats with a launch period of 2 days and a
# post-launch period of 5 days

perf <- podlove_performance_stats(podcast_example_data, launch = 2, post_launch = 5)
podlove_graph_performance(perf)

# add a label
perf <- podlove_performance_stats(podcast_example_data, launch = 2, post_launch = 5,
                                  label = ep_number, legend = title)
podlove_graph_performance(perf)

## End(Not run)

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