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<- function(..., width = 10) {
ggpk_dot_matrix ggpacket(...) %+%
geom_point(
data = . %>%
mutate(
xvar = (1:nrow(.)-1) %% width,
yvar = (1:nrow(.)-1) %/% width
),mapping = aes(x = xvar, y = yvar),
%+%
...) theme_void() %+%
coord_fixed()
}
library(dplyr)
%>%
diamonds sample_frac(0.01) %>%
arrange(cut) %>%
ggplot() +
aes(color = cut) +
ggpk_dot_matrix(size = 3, width = 30)
<- function(...) {
ggpk_tukey_ribbons ggpacket(...) %+%
# Tukey Box Edges
geom_ribbon(.id = "box",
mapping = aes(fill = ..color..),
stat = "summary",
fun = median,
fun.min = ~quantile(., 0.25, names = FALSE),
fun.max = ~quantile(., 0.75, names = FALSE),
alpha = 0.15,
...,color = NA) %+%
# Tukey Whiskers
geom_ribbon(.id = "whisker",
mapping = aes(fill = ..color..),
stat = "summary",
fun = median,
fun.min = ~.[head(which(. > quantile(., 0.25, names = FALSE) - 1.5 * IQR(.)), 1)],
fun.max = ~.[tail(which(. < quantile(., 0.75, names = FALSE) + 1.5 * IQR(.)), 1)],
alpha = 0.15,
...,color = NA) %+%
# Median Line
geom_line(.id = list(NULL, "line"),
stat = "summary",
fun = median,
alpha = 0.8,
...) }
library(dplyr)
%>%
economics_long filter(variable %in% c("pop", "unemploy")) %>%
mutate(year = as.integer(format(as.Date(date, format = "%Y-%m-%d"), "%Y"))) %>%
ggplot() + aes(x = year, y = value, color = variable) +
ggpk_tukey_ribbons() +
scale_y_log10()
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They may not be fully stable and should be used with caution. We make no claims about them.