## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(
  echo = TRUE,
  fig.align = "center",
  fig.width = 6,
  fig.height = 4,
  out.width = "600px",
  out.height = "400px"
)

library(ggpackets)

## ----include = FALSE----------------------------------------------------------
library(dplyr)
library(ggplot2)

## -----------------------------------------------------------------------------
ggpk_dot_matrix <- function(..., width = 10) {
  ggpacket(...) %+%
    geom_point(
      data = . %>%
        mutate(
          xvar = (seq_len(nrow(.)) - 1) %%  width,
          yvar = (seq_len(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)

## -----------------------------------------------------------------------------
ggpk_tukey_ribbons <- function(...) {
  tukey_whisker_min <- function(x) {
    x[head(which(x > quantile(x, 0.25, names = FALSE) - 1.5 * IQR(x)), 1)]
  }

  tukey_whisker_max <- function(x) {
    x[tail(which(x < quantile(x, 0.75, names = FALSE) + 1.5 * IQR(x)), 1)]
  }

  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 = tukey_whisker_min,
      fun.max = tukey_whisker_max,
      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()