ggtaichi

Two data sources. One grid of yin-yang glyphs. Both halves at a glance.

A geom_tile() heatmap gives you one number per cell. geom_taichi() gives you two.

Install

install.packages("ggtaichi")

# development version
devtools::install_github("PursuitOfDataScience/ggtaichi")

One glyph, two numbers

Yin takes one source, yang the other. No decoration: 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 single large taichi diagram whose red (yang) half encodes one data source and grey (yin) half the other.

Now a grid of them

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

ggplot(pitts_small, aes(week, category)) +
  geom_taichi(yin = Twitter, yang = Google) +
  theme_taichi()

A six-week grid of taichi diagrams for nine Pittsburgh COVID categories, the yang fish shaded red by Google and the yin fish grey by Twitter.

Covid runs dark in both halves, heavy on Twitter and Google alike. Masks darkens on Twitter but stays pale pink: little Google.

The eyes are data too

Six dimensions in one mark: x, y, two fills, two eyes.

quad <- data.frame(x = c(1, 2, 1, 2), y = c(2, 2, 1, 1),
                   yin = c(3, 5, 7, 9), yang = c(9, 7, 5, 3),
                   reach = c(10, 40, 25, 5), quality = c(2, 1, 4, 8))

ggplot(quad, aes(x, y)) +
  geom_taichi(yin = yin, yang = yang, eyes = TRUE,
              yin_eye_size = reach, yang_eye_size = quality,
              limits = c(0, 10)) +
  coord_fixed() +
  theme_taichi()

A two-by-two grid of taichi diagrams with classic eyes whose sizes vary from cell to cell, encoding two extra variables.

Spin it

angle takes a constant or a column: a seventh channel.

rot <- data.frame(x = 1:4, y = 1, yin = 1:4, yang = 4:1,
                  turn = c(0, 45, 90, 135))

ggplot(rot, aes(x, y)) +
  geom_taichi(yin = yin, yang = yang, angle = turn, eyes = TRUE,
              limits = c(0, 5)) +
  coord_fixed() +
  theme_taichi()

Four taichi diagrams rotated by 0, 45, 90, and 135 degrees read from a data column.

Hand angle to gganimate and it actually spins.

library(gganimate)

spin <- expand.grid(x = 1:4, f = 1:48)
spin$y <- 1
spin$turn <- (spin$f - 1) * 7.5 + (spin$x - 1) * 45   # each one out of phase

ggplot(spin, aes(x, y)) +
  geom_taichi(yin = 1, yang = 2, angle = turn, eyes = TRUE,
              yin_colors = "grey15", yang_colors = "#C20824",
              show.legend = FALSE) +
  coord_fixed() +
  theme_void() +
  transition_states(f, transition_length = 1, state_length = 0)

Four taichi glyphs rotating steadily, each a quarter turn out of phase with the last.

Watch a season go by

cafes_tg follows espresso and matcha across twelve weeks. Espresso cools off, matcha warms up.

ggplot(cafes_tg, aes(neighbourhood, "")) +
  geom_taichi(yin = matcha, yang = espresso, shared_legend = TRUE,
              yin_name = "orders / 100 customers") +
  theme_taichi() +
  theme(axis.text.x = element_text(angle = 30, hjust = 1, size = 9)) +
  labs(title = "Week {closest_state}", x = NULL) +
  transition_states(week, transition_length = 2, state_length = 1)

Eight taichi glyphs, one per neighbourhood, animating week by week as the espresso half lightens and the matcha half darkens.

Categories work too

disc <- data.frame(x = c(1, 2, 1, 2), y = c(2, 2, 1, 1),
                   method = factor(c("A", "B", "C", "A")),
                   outcome = factor(c("win", "loss", "win", "loss")))

ggplot(disc, aes(x, y)) +
  geom_taichi(yin = method, yang = outcome) +
  coord_fixed() +
  theme_taichi()

A two-by-two grid of taichi diagrams whose fish are filled by discrete categories: methods A to C for yin and win or loss for yang.

The legend keys are little taichi as well.

Same units? One legend.

ggplot(cafes_tg, aes(week, neighbourhood)) +
  geom_taichi(yin = matcha, yang = espresso, shared_legend = TRUE,
              yin_name = "orders / 100 customers") +
  remove_padding() +
  theme_taichi()

A 12-week by 8-neighbourhood grid of taichi diagrams comparing espresso and matcha orders on one shared grey scale with a single legend.

Bigger, sure. But by how much?

Two fish in one spot tell you which. explicit computes the gap and shows you how much. Cells where the two agree get no eye at all.

ggplot(cafes_tg, aes(week, neighbourhood)) +
  geom_taichi(yin = matcha, yang = espresso, shared_legend = TRUE,
              yin_name = "orders / 100 customers",
              explicit = "difference") +
  remove_padding() +
  theme_taichi()

The espresso versus matcha grid where each glyph's eyes grow with the gap between the two sources, and cells where they agree have no eyes.

Or as tilt, which the eye reads far more precisely. Upright means they agree.

tilt <- data.frame(x = 1:5, y = 1, yin = c(1, 3, 5, 7, 9), yang = 9:5)

ggplot(tilt, aes(x, y)) +
  geom_taichi(yin = yin, yang = yang, shared_limits = TRUE,
              explicit = "difference", explicit_channel = "angle") +
  coord_fixed() +
  theme_taichi()

Five taichi diagrams tilting from left-leaning to right-leaning as the difference between the two sources goes from negative to positive.

Animate it and the eyes blink shut exactly where the two sources cross.

ggplot(cafes_tg, aes(neighbourhood, "")) +
  geom_taichi(yin = matcha, yang = espresso, shared_legend = TRUE,
              yin_name = "orders / 100 customers",
              explicit = "difference") +
  theme_taichi() +
  theme(axis.text.x = element_text(angle = 30, hjust = 1, size = 9)) +
  labs(title = "Week {closest_state}", x = NULL) +
  transition_states(week, transition_length = 2, state_length = 1)

Eight taichi glyphs animating across a season; their eyes shrink to nothing as espresso and matcha cross over, then swell again.

Is your palette fair?

If the two ramps don’t span the same luminance, equal values don’t look equal and one fish quietly wins. Ask:

taichi_check_palette()
#>   largest luminance mismatch : 40.6 L* (tolerance 5.0)
#>   Verdict: FAIL

Yes: the defaults fail their own check, and are kept only so old figures don’t move. palette = "balanced" passes.

ggplot(cafes_tg, aes(week, neighbourhood)) +
  geom_taichi(yin = matcha, yang = espresso,
              palette = "balanced", shared_limits = TRUE) +
  remove_padding() +
  theme_taichi()

The espresso versus matcha grid drawn with a luminance-matched blue and brick-red palette pair, so equal values carry equal visual weight.

Too many cells? Bin it.

ggplot(cafes_tg, aes(week, neighbourhood)) +
  geom_taichi(yin = matcha, yang = espresso,
              yin_scale  = scale_taichi_yin_binned(n.breaks = 4),
              yang_scale = scale_taichi_yang_binned(n.breaks = 4),
              shared_limits = TRUE) +
  remove_padding() +
  theme_taichi()

The espresso versus matcha grid with both fish filled from four discrete colour steps rather than a continuous ramp.

Hover for the exact numbers

p <- ggplot(cafes_tg, aes(week, neighbourhood)) +
  geom_taichi(yin = matcha, yang = espresso,
              interactive = TRUE, data_id_by = "source")

ggiraph::girafe(ggobj = p)

Hover one yin fish and every yin fish lights up. Live version in the gallery.

vignette("ggtaichi") for the full tour, vignette("animations") for motion, and the gallery for the rest.

Acknowledgement

ggtaichi is a spinoff of the ggDoubleHeat package, which introduced the idea of folding two data sources into a single reformed heat map. ggtaichi takes that two-scale design and re-imagines the per-cell glyph as a taichi diagram.