Visualise Where Forecasts Are Available.
Usage
plot_forecast_counts(
forecast_counts,
x,
y = "model",
x_as_factor = TRUE,
show_counts = TRUE
)
Arguments
- forecast_counts
A data.table (or similar) with a column
count
holding forecast counts, as produced byget_forecast_counts()
.- x
Character vector of length one that denotes the name of the column to appear on the x-axis of the plot.
- y
Character vector of length one that denotes the name of the column to appear on the y-axis of the plot. Default is "model".
- x_as_factor
Logical (default is
TRUE
). Whether or not to convert the variable on the x-axis to a factor. This has an effect e.g. if dates are shown on the x-axis.- show_counts
Logical (default is
TRUE
) that indicates whether or not to show the actual count numbers on the plot.
Examples
library(ggplot2)
library(magrittr) # pipe operator
forecast_counts <- example_quantile %>%
as_forecast_quantile %>%
get_forecast_counts(by = c("model", "target_type", "target_end_date"))
#> ℹ Some rows containing NA values may be removed. This is fine if not
#> unexpected.
plot_forecast_counts(
forecast_counts, x = "target_end_date", show_counts = FALSE
) +
facet_wrap("target_type")