Plot a raw case counts as a histogram

Usage

plot_cases(
  raw,
  ...,
  mapping = .check_for_aes(raw, ..., class_aes = "fill"),
  events = i_events
)

Arguments

raw

The raw case data either as a summarised count or as a line-list - EITHER: a dataframe with columns:

count (positive_integer) - Positive case counts associated with the specified time frame
time (ggoutbreak::time_period + group_unique) - A (usually complete) set of singular observations per unit time as a `time_period`

Any grouping allowed.

OR with columns:

time (ggoutbreak::time_period) - A set of events with a timestamp as a `time_period`

Any grouping allowed.

...

Named arguments passed on to geom_events

events

Significant events or time spans - a dataframe with columns:

label (character) - the event label
start (date) - the start date, or the date of the event
end (date) - the end date or NA if a single event

Any grouping allowed.

A default value is defined.

mapping

a ggplot2::aes mapping. Most importantly setting the fill to something if there are multiple types of event in the plot. If a class column is present the mapping will default to using this.

events

Significant events or time spans - a dataframe with columns:

label (character) - the event label
start (date) - the start date, or the date of the event
end (date) - the end date or NA if a single event

Any grouping allowed.

A default value is defined.

Value

a ggplot object

Examples


# 50 random times:
tmp = dplyr::tibble(
  time = as.time_period( sample.int(10,50,replace=TRUE) ,"1 day"),
  class = rep(c("one","two","three"), length.out=50)
)

if(interactive()) {
  plot_cases(tmp)
}