yamlet (version 1.2.1)

ggplot.decorated: Create a New ggplot for a Decorated Data Frame

Description

Creates a new ggplot object for a decorated data.frame. This is the ggplot() method for class 'decorated'. It creates a ggplot object using the default method, but reclassifies it as 'decorated_ggplot' so that a custom print method is invoked; see print.decorated_ggplot.

Usage

# S3 method for decorated
ggplot(data, ...)

Value

return value like ggplot but inheriting 'decorated_ggplot'

Arguments

data

decorated, see decorate

...

passed to ggplot

Details

This approach is similar to but more flexible than the method for ggready. For fine control, you can switch between 'data.frame' and 'decorated' using as_decorated (supplies null decorations) and as.data.frame (preserves decorations).

See Also

decorate resolve ggready

Other decorated_ggplot: ggplot_build.decorated_ggplot(), print.decorated_ggplot()

Other interface: canonical.decorated(), classified.data.frame(), decorate.character(), decorate.data.frame(), desolve.decorated(), enscript.default(), io_csv.character(), io_csv.data.frame(), io_res.character(), io_res.decorated(), io_table.character(), io_table.data.frame(), io_yamlet.character(), io_yamlet.data.frame(), is_parseable.default(), mimic.default(), modify.default(), promote.list(), read_yamlet(), resolve.decorated(), selected.default(), write_yamlet()

Examples

file <- system.file(package = 'yamlet', 'extdata','quinidine.csv')
library(ggplot2)
library(dplyr)
library(magrittr)
# par(ask = FALSE)

x <- decorate(file)
x %<>% filter(!is.na(conc))

# Manipulate class to switch among ggplot methods.
class(x)
class(data.frame(x))
class(as_decorated(data.frame(x)))

# The bare data.frame gives boring labels and un-ordered groups.
# (After ggplot2 v. 3.5.1 label attributes are honored as axis labels.)
map <- aes(x = time, y = conc, color = Heart)
data.frame(x) %>% ggplot(map) + geom_point()

# Decorated data.frame uses supplied labels.
# Notice CHF levels are still not ordered. (Moderate first.)
x %>% ggplot(map) + geom_point()

# If we resolve Heart, CHF levels are ordered.
x %>% resolve(Heart) %>% ggplot(map) + geom_point()

# We can map aesthetics as decorations.
x %>% 
  decorate('Heart: [ color: [gold, purple, green]]') %>%
  ggplot(map) + geom_point()

# Colors are matched to particular levels. Purple drops out here:
x %>% 
  decorate('Heart: [ color: [gold, purple, green]]') %>%
  filter(Heart != 'Moderate') %>%
  ggplot(map) + geom_point()

# We can resolve other columns for a chance to enrich the output with units.
x %>%
  resolve %>%
  ggplot(map) + geom_point()

# Underscore and circumflex imply subscript and superscript:
x %>% 
  redecorate("conc: [ conc_serum, mg*L^-1 ]") %>%
  ggplot(map) + geom_point()

# If we invoke enscript(), the subscripts and superscripts are rendered: 
x %>% 
  redecorate("conc: [ conc_serum, mg*L^-1 ]") %>%
  redecorate("Heart: [ CHF^\\* ]") %>%
  enscript %>%
  ggplot(map) + geom_point()

# Here we try a dataset with conditional labels and units.

file <- system.file(package = 'yamlet', 'extdata','phenobarb.csv')
x <- file %>% decorate %>% resolve
# Note that value has two elements for label, etc.
x %>% decorations(value)

# The print method defaults to the first, with warning.
map <- aes(x = time, y = value, color = event)
# \donttest{
x %>% ggplot(map) + geom_point()
# }

# If we subset appropriately, the relevant value is substituted.
x %>% filter(event == 'conc') %>% ggplot(map) + geom_point()

x %>% filter(event == 'conc') %>%
ggplot(aes(x = time, y = value, color = ApgarInd)) + geom_point()

x %>% filter(event == 'dose') %>%
ggplot(aes(x = time, y = value, color = Wt)) +
geom_point() +
scale_y_log10() +
scale_color_gradientn(colours = rainbow(4))

# print.decorated_ggplot will attempt to honor coordinated aesthetics.
x <- data.frame(x = c(1:6, 3:8), y = c(1:6,1:6), z = letters[c(1:6,1:6)])
x %<>% decorate('z: [color: ["red", "blue", "green", "gold", "black", "magenta"]]')
x %<>% decorate('z: [fill: ["red", "blue", "green", "gold", "black", "magenta"]]')
x %<>% decorate('z: [shape: [20, 21, 22, 23, 24, 25]]')
x %<>% decorate('z: [linetype: [6, 5, 4, 3, 2, 1]]')
x %<>% decorate('z: [alpha: [ .9, .8, .7, .6, .5, .4]]')
x %<>% decorate('z: [size: [1, 1.5, 2, 2.5, 3, 3.5]]')
x %>% ggplot(aes(
 x, y,
  color = z,
  fill = z,
  shape = z,
  linetype = z, 
  alpha = z,
  size = z,
)) + 
  geom_point() +
  geom_line(size = 1)