README

ggtaichi is a ggplot2 extension that compares data from two sources on a single grid of taichi (yin-yang) diagrams. A regular heat map made with geom_tile() encodes three dimensions (the x, y position and one value); geom_taichi() turns every cell into a taichi symbol whose two interlocking fish are filled by two sources at once, so four dimensions are expressed on one plot.

Installation

# install.packages("devtools")
devtools::install_github("PursuitOfDataScience/ggtaichi")

Anatomy of a taichi

Each symbol is a circle split by an S-curve into two interlocking fish. The yang (light) fish is shaded by one source and the yin (dark) fish by the other, each on its own gradient. There are no decorative dots: every drop of ink is data.

library(ggtaichi)
library(ggplot2)

one <- data.frame(x = 1, y = 1, google = 7, twitter = 3)

ggplot(one, aes(x, y)) +
  geom_taichi(yin = twitter, yang = google) +
  coord_fixed() +
  theme_taichi()

A clear, small grid

The built-in pitts_tg dataset holds the 30-week COVID-related Google and Twitter incidence rates for 9 categories in the Pittsburgh Metropolitan Statistical Area. With many weeks the symbols shrink, so it is often easier to read a slice. Here are the first six weeks, where each taichi is big enough to compare the two halves at a glance.

pitts_small <- subset(pitts_tg, week <= 6)

ggplot(pitts_small, aes(x = week, y = category)) +
  geom_taichi(yin = Twitter, yang = Google) +
  theme_taichi() +
  ggtitle("Pittsburgh: Google (yang) vs Twitter (yin), weeks 1-6")

The legend titles default to the column names you supply. Note how Covid and Masks lean dark (high Twitter) while staying pink (moderate Google).

Your own palettes

Each fish gets its own gradient, and any extra argument is passed straight to ggplot2::scale_fill_gradientn().

ggplot(pitts_small, aes(x = week, y = category)) +
  geom_taichi(
    yin  = Twitter, yin_name  = "Twitter (%)",
    yin_colors  = c("#deebf7", "#3182bd", "#08306b"),
    yang = Google,  yang_name = "Google (%)",
    yang_colors = c("#fee6ce", "#e6550d", "#7f2704")
  ) +
  theme_taichi()

Comparing places

Because geom_taichi() is an ordinary layer, faceting just works. The states_tg dataset repeats the same measurements across four states; showing two of them over a handful of weeks keeps the glyphs large and legible.

two_states <- subset(states_tg, state %in% c("New York", "Texas") & week <= 6)

ggplot(two_states, aes(x = week, y = category)) +
  geom_taichi(yin = Twitter, yang = Google) +
  facet_wrap(~ state, ncol = 1) +
  remove_padding(x = "c", y = "d") +
  theme_taichi() +
  ggtitle("New York vs Texas, weeks 1-6")

Acknowledgement

ggtaichi is built on top of, and is the spiritual sibling of, the ggDoubleHeat package, which introduced the idea of folding two data sources into a single reformed heat map through the geom_heat_*() family. ggtaichi reuses that two-scale design (and its example data) and re-imagines the per-cell glyph as a taichi diagram. ggDoubleHeat is the foundational layer of this package and should be cited when you use ggtaichi: