translate_qplot_lattice

0th

Percentile

Translating between qplot and lattice

The major difference between lattice and ggplot2 is that lattice uses a formula based interface. ggplot2 does not because the formula does not generalise well to more complicated situations.

Keywords
internal
Aliases
  • translate_qplot_lattice
Examples
library(ggplot2) library(lattice) if (require("ggplot2movies")) { xyplot(rating ~ year, data=movies) qplot(year, rating, data=movies) xyplot(rating ~ year | Comedy + Action, data = movies) qplot(year, rating, data = movies, facets = ~ Comedy + Action) # Or maybe qplot(year, rating, data = movies, facets = Comedy ~ Action) # While lattice has many different functions to produce different types of # graphics (which are all basically equivalent to setting the panel argument), # ggplot2 has qplot(). stripplot(~ rating, data = movies, jitter.data = TRUE) qplot(rating, 1, data = movies, geom = "jitter") histogram(~ rating, data = movies) qplot(rating, data = movies, geom = "histogram") bwplot(Comedy ~ rating ,data = movies) qplot(factor(Comedy), rating, data = movies, geom = "boxplot") xyplot(wt ~ mpg, mtcars, type = c("p","smooth")) qplot(mpg, wt, data = mtcars, geom = c("point","smooth")) } # The capabilities for scale manipulations are similar in both ggplot2 and # lattice, although the syntax is a little different. xyplot(wt ~ mpg | cyl, mtcars, scales = list(y = list(relation = "free"))) qplot(mpg, wt, data = mtcars) + facet_wrap(~ cyl, scales = "free") xyplot(wt ~ mpg | cyl, mtcars, scales = list(log = 10)) qplot(mpg, wt, data = mtcars, log = "xy") xyplot(wt ~ mpg | cyl, mtcars, scales = list(log = 2)) qplot(mpg, wt, data = mtcars) + scale_x_continuous(trans = scales::log2_trans()) + scale_y_continuous(trans = scales::log2_trans()) xyplot(wt ~ mpg, mtcars, group = cyl, auto.key = TRUE) # Map directly to an aesthetic like colour, size, or shape. qplot(mpg, wt, data = mtcars, colour = cyl) xyplot(wt ~ mpg, mtcars, xlim = c(20,30)) # Works like lattice, except you can't specify a different limit # for each panel/facet qplot(mpg, wt, data = mtcars, xlim = c(20,30)) # Both lattice and ggplot2 have similar options for controlling labels on the plot. xyplot(wt ~ mpg, mtcars, xlab = "Miles per gallon", ylab = "Weight", main = "Weight-efficiency tradeoff") qplot(mpg, wt, data = mtcars, xlab = "Miles per gallon", ylab = "Weight", main = "Weight-efficiency tradeoff") xyplot(wt ~ mpg, mtcars, aspect = 1) qplot(mpg, wt, data = mtcars, asp = 1) # par.settings() is equivalent to + theme() and trellis.options.set() # and trellis.par.get() to theme_set() and theme_get(). # More complicated lattice formulas are equivalent to rearranging the data # before using ggplot2.
Documentation reproduced from package ggplot2, version 2.2.1, License: GPL-2 | file LICENSE

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