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#' @description
#' Create groups of ggplot layers that can be easily migrated from one plot to
#' another, reducing redundant code and improving the ability to format many
#' plots that draw from the same source ggpacket layers.
#'
#' @examples
#' library(ggplot2)
#'
#' # Prep a tidy data.frame to plot with
#' airquality_long <- rbind(
#' data.frame(
#' airquality[,c("Month", "Day")],
#' Variable = "Temp",
#' Measurement = airquality$Temp),
#' data.frame(
#' airquality[,c("Month", "Day")],
#' Variable = "Ozone",
#' Measurement = airquality$Ozone))
#'
#' # Build our new composite ggplot geom
#' geom_error_line <- ggpacket() %+%
#' geom_ribbon(
#' .id = "box",
#' mapping = aes(fill = ..color..),
#' stat = 'summary',
#' fun = mean,
#' fun.min = ~mean(.) - sd(.),
#' fun.max = ~mean(.) + sd(.),
#' alpha = 0.15,
#' color = NA) %+%
#' geom_line(
#' .id = "line",
#' stat = 'summary',
#' fun = mean,
#' alpha = 0.8)
#'
#' # Try it out!
#' ggplot(airquality_long) +
#' aes(x = round((Month * 30 + Day) / 4), y = Measurement, color = Variable) +
#' geom_error_line(na.rm = TRUE, line.size = 1.5) +
#' scale_y_log10() +
#' labs(x = "Week")
#'
#' # for further examples, check out the vignettes
#' vignette(package = "ggpackets")
#'
"_PACKAGE"
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