This function creates a ggplot2 layer that shades date ranges based on grouped data. It's particularly useful for highlighting specific periods in time series data.
Usage
stat_shade_ranges(
mapping = NULL,
data = NULL,
geom = "linerange",
position = "identity",
na.rm = TRUE,
show.legend = NA,
inherit.aes = TRUE,
...
)Arguments
- mapping
Set of aesthetic mappings created by
aes. Must include `x` for dates and `group` for categorizing ranges.- data
The data to be displayed in this layer. If NULL, the default, the data is inherited from the plot data as specified in the call to
ggplot.- geom
The geometric object to use display the data. Default is "linerange".
- position
Position adjustment, either as a string, or the result of a call to a position adjustment function. Default is "identity".
- na.rm
If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.
- show.legend
logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped.
- inherit.aes
If FALSE, overrides the default aesthetics, rather than combining with them.
- ...
Other arguments passed on to
layer. These are often aesthetics, used to set an aesthetic to a fixed value.
Examples
if (FALSE) {
library(ggplot2)
library(data.table)
# Create sample data
dt <- data.table(
datetime = seq(as.POSIXct("2023-01-01"), as.POSIXct("2023-12-31"), by = "day"),
close = runif(365, 100, 200),
call = sample(c("buy", "sell", "none"), 365, replace = TRUE, prob = c(0.3, 0.3, 0.4))
)
# Create plot with shaded ranges
ggplot(dt, aes(x = datetime)) +
geom_line(aes(y = close), linewidth = 1.5, colour = "white") +
stat_shade_ranges(aes(group = call, fill = call), alpha = 0.25) +
scale_fill_manual(
name = "Call",
values = c("buy" = "green", "sell" = "red", "none" = "gray")
) +
theme_minimal() +
labs(title = "Stock Price with Buy/Sell Signals", x = "Date", y = "Price")
}