In JohnCoene/g2r: Grammar of Graphics for Interactive Visualisations

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
library(dplyr)
library(g2r)
library(gt)
g2r_globals(font = "Quicksand")

Synthax

The synthax of g2r is heavily inspired by ggplot2.

dplyr::tribble(
  ~"ggplot2",       ~"g2r",
  "ggplot",         "g2",
  "aes",            "asp",
  "scale_*",        "gauge_*",
  "geom_*",         "fig_*",
  "facet_*",        "plane_*",
  "theme_*",        "motif_*"
) %>% 
  gt() %>% 
  tab_header(
    title = "g2r syntax",
    subtitle = "From ggplot2 to g2r"
  )

Aspects

In g2r you use aspects (asp) instead of aesthetics (aes) in ggplot2 but they work in very much the same way.

g2(cars, asp(dist, speed, color = speed)) %>% 
  fig_point()

Then you can use gauges (instead of scales in ggplot2) to manipulate those aspects.

g2(cars, asp(dist, speed, color = speed, size = speed)) %>% 
  fig_point() %>% 
  gauge_color(c("blue", "white", "red"))

It may seem like some some figures (equivalent to geoms) are missing, but technically all are available.

fruits %>% 
  arrange(-value) %>% 
  g2(asp(value, color = fruit)) %>% 
  fig_interval_stack() %>% 
  coord_type("theta")

The same could be said of the funnel.

fr <- fruits %>% 
  dplyr::mutate(value = value * 100) %>% 
  dplyr::arrange(-value)

g2(fr, asp(fruit, value, color = fruit, shape = "pyramid")) %>% 
  fig_interval_symmetric() %>% 
  coord_transpose() %>% 
  coord_scale(1, -1) %>% 
  hide_axes()

Examples

You won't find fig_bar but fig_interval does the trick. Below we use the adjust function which is similar to using the stat argument in ggplot2.

g2(temp, asp(month, temp, color = city)) %>% 
  fig_interval(adjust("dodge")) # equivalent to fig_interval_dodge

g2(temp, asp(month, temp, color = city)) %>% 
  fig_interval(adjust("stack")) # equivalent to fig_interval_stack

library(dplyr)

df <- mtcars %>%
  dplyr::mutate(
    cyl = as.factor(cyl),
    am = as.factor(am)
  )

g2(df, asp(cyl , mpg, color = am)) %>%
  fig_boxplot()

There is a fig_violin but it expects the data in a specific format, so a helper function exists, fig_guitar.

df <- mtcars %>%
  dplyr::mutate(
    cyl = as.factor(cyl),
    am = as.factor(am)
  )

g2(df, asp(cyl , mpg, color = am)) %>%
  fig_guitar(asp(opacity = .3), tooltip = FALSE)

A heatmap is easier.

library(dplyr)

data("diamonds", package = "ggplot2")

palette <- c("blue", "cyan", "lime", "yellow", "red")

diamonds %>% 
  count(carat, price) %>% 
  g2(asp(carat, price, color = n)) %>% 
  fig_heatmap() %>% 
  gauge_color(palette)

iris %>%
  g2(asp(Petal.Length, Petal.Width, color = Species)) %>% 
  fig_point() %>%
  plane_wrap(planes(Species), type = "tree")

fruits %>%
  dplyr::mutate(value = value * 100) %>%
  g2(asp(fruit, value)) %>% 
  fig_waffle(asp(color = fruit))

The alter function is used internally by get_map to process GeoJSON files. It'll enable you to easily build otherwise difficult charts. Though there is a fig_hex helper now.

g2(gaus, asp(x, y, color = "count")) %>% 
  fig_bin() %>% 
  gauge_color(c("#BAE7FF", "#1890FF", "#0050B3"))

g2(gaus, asp(x, y, color = "count")) %>% 
  fig_bin(size_count = FALSE, type = "hexagon") %>% 
  gauge_color(c("#BAE7FF", "#1890FF", "#0050B3"))

df <- dplyr::tibble(
  x = runif(25, 1, 500),
  y = runif(25, 1, 500),
  value = runif(25, 1, 500)
)

g2(df, asp(x, y, color = value)) %>%
  fig_voronoi(axes = FALSE)

fruits %>% 
  arrange(value) %>% 
  mutate(label = fruit) %>%  
  g2(asp(fruit, value)) %>% 
  fig_interval(asp(shape = "line")) %>%
  fig_point(asp(shape = "circle")) %>%  
  coord_type("theta", innerRadius = .2, endAngle = pi) %>% 
  info_text(asp(fruit, 0, content = label), style = list(textAlign = "right"))

Many figures have been implemented, many of them actually use the group aspect.

g2(iris, asp(Sepal.Length, group = Species, color = Species))  %>%
  fig_histogram(bin_width = .3)

g2(iris, asp(Petal.Length, group = Species, color = Species)) %>%
  fig_density()

df <- data.frame(
  trt = factor(c(1, 1, 2, 2)),
  resp = c(1, 5, 3, 4),
  group = factor(c(1, 2, 1, 2)),
  upper = c(1.1, 5.3, 3.3, 4.2),
  lower = c(0.8, 4.6, 2.4, 3.6)
)

g2(df, asp(trt, resp, ymin = lower, ymax = upper, color = group)) %>%
  fig_errorbar()

huron <- dplyr::tibble(
  year = as.character(1875:1972), 
  level = as.vector(LakeHuron)
) %>% 
  dplyr::mutate(
    mn = level - 1,
    mx = level + 1
  )

g2(huron, asp(year, level, ymin = mn, ymax = mx)) %>%
  fig_line() %>%
  fig_ribbon() %>% 
  gauge_x_time(tickCount = 3)

g2(cars, asp(speed, dist)) %>%
  fig_point() %>%
  fig_smooth()

In g2r you use motif instead of theme, though you can build your own with custom_motif there is a build-in motif_dark in addition to the default.

cars2 <- dplyr::mutate(cars, speed = jitter(speed))

g2(cars2, asp(speed, dist)) %>%
  fig_point() %>%
  fig_smooth(method = "loess") %>%
  fig_rug() %>%  
  motif_dark()

There is a helper function to create animations (You might have to refresh the page to see it).

anim <- Animation$
  new()$
  appear(duration = 5000, delay = 5000)

iris %>%
  g2(asp(Sepal.Length, Sepal.Width, color = Species)) %>%
  fig_point(anim)

Using "informational elements" to a chart. See documentation for the full list. Note the chart below is inspired by the Bretton Woods Wikipedia page which actually uses the same dataset from CRAN.

data("bankingCrises", package = "Ecdat")

bw <- bankingCrises %>% 
  tidyr::gather("country", "value", -year) %>% 
  dplyr::group_by(year) %>% 
  dplyr::summarise(n = sum(value))

g2(bw, asp(year, n)) %>% 
  fig_interval() %>% 
  info_region(
    start = c("1945", "min"),
    end = c("1971", "max"),
    inherit_asp = FALSE
  ) %>% 
  info_text(
    content = "Bretton Woods",
    position = c("1945", 20),
    inherit_asp = FALSE
  )

You can pass lists as axis data.

library(g2r)
library(purrr)

df <- dplyr::tibble(
  x = letters[1:10],
  y1 = runif(10, 1, 5),
  y2 = runif(10, 7, 10)
) %>% 
  tidyr::nest(y1, y2)

df$data <- df$data %>% 
  map(unlist) %>% 
  map(unname)

g2(df, asp(x, data)) %>% 
  fig_point(asp(shape = "circle", size = 5)) %>% 
  fig_interval(asp(size = 3))