demo/transform.R

In vegawidget/virgo: A Domain Specific Language for Layered Grammar of Interactive Graphics

library(dplyr)

movies <- jsonlite::read_json(
  "https://vega.github.io/vega-editor/app/data/movies.json"
  , simplifyVector = TRUE)

as_tibble(movies) %>%
  vega(enc(x = Rotten_Tomatoes_Rating, y = IMDB_Rating)) %>%
  mark_point(enc(colour = vg_bin(IMDB_Rating, step = 3)))

movies %>%
  vega() %>%
  mark_bar(enc(x = vg_argmax(Production_Budget, US_Gross), y = Major_Genre))

as_tibble(movies) %>%
  vega(enc(x = Rotten_Tomatoes_Rating, y = IMDB_Rating)) %>%
  mark_point() %>%
  mark_smooth(enc(colour = Major_Genre))

as_tibble(movies) %>%
  vega(enc(x = Rotten_Tomatoes_Rating, y = IMDB_Rating)) %>%
  mark_point() %>%
  mark_smooth(colour = "firebrick", formula = y ~ x^3)

as_tibble(movies) %>%
  vega(enc(x = Rotten_Tomatoes_Rating, y = IMDB_Rating)) %>%
  mark_point() %>%
  mark_smooth(colour = "firebrick", method = "loess")

as_tibble(movies) %>%
  vega(enc(x = Rotten_Tomatoes_Rating, y = IMDB_Rating)) %>%
  mark_point() %>%
  mark_smooth(colour = "firebrick", selection = !select_interval())

as_tibble(movies) %>%
  vega(enc(x = IMDB_Rating, y = Rotten_Tomatoes_Rating, colour = vg_count())) %>%
  mark_bin2d(bin = list(x = list(maxbins = 60), y = list(maxbins = 40)))

# missing data
library(dplyr)
movies <- jsonlite::read_json(
  "https://vega.github.io/vega-editor/app/data/movies.json"
  , simplifyVector = TRUE)
movies <- movies %>%
  mutate(missing = is.na(IMDB_Rating) | is.na(Rotten_Tomatoes_Rating))
movies %>%
  vega(enc(IMDB_Rating, Rotten_Tomatoes_Rating, colour = missing)) %>%
  mark_point(na.rm = FALSE) %>%
  config(mark = list(invalid = NULL))

movies %>%
  vega(enc(IMDB_Rating, Rotten_Tomatoes_Rating)) %>%
  mark_point()

movies %>%
  vega(enc(IMDB_Rating, Rotten_Tomatoes_Rating)) %>%
  mark_point(na.rm = FALSE)

palmerpenguins::penguins %>%
  vega(enc(x = body_mass_g, colour = species)) %>%
  mark_density()