/man/translate_qplot_ggplot.Rd
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- % Generated by roxygen2: do not edit by hand
- % Please edit documentation in R/translate-qplot-ggplot.r
- \name{translate_qplot_ggplot}
- \alias{translate_qplot_ggplot}
- \title{Translating between qplot and ggplot}
- \description{
- Within ggplot2, there are two basic methods to create plots, with qplot()
- and ggplot(). qplot() is designed primarily for interactive use: it makes
- a number of assumptions that speed most cases, but when designing multilayered
- plots with different data sources it can get in the way. This section
- describes what those defaults are, and how they map to the fuller ggplot()
- syntax.
- }
- \examples{
- # By default, qplot() assumes that you want a scatterplot,
- # i.e., you want to use geom_point()
- # qplot(x, y, data = data)
- # ggplot(data, aes(x, y)) + geom_point()
- # Using Aesthetics
- # If you map additional aesthetics, these will be added to the defaults. With
- # qplot() there is no way to use different aesthetic mappings (or data) in
- # different layers
- # qplot(x, y, data = data, shape = shape, colour = colour)
- # ggplot(data, aes(x, y, shape = shape, colour = colour)) + geom_point()
- #
- # Aesthetic parameters in qplot() always try to map the aesthetic to a
- # variable. If the argument is not a variable but a value, effectively a new column
- # is added to the original dataset with that value. To set an aesthetic to a
- # value and override the default appearance, you surround the value with I() in
- # qplot(), or pass it as a parameter to the layer.
- # qplot(x, y, data = data, colour = I("red"))
- # ggplot(data, aes(x, y)) + geom_point(colour = "red")
- # Changing the geom parameter changes the geom added to the plot
- # qplot(x, y, data = data, geom = "line")
- # ggplot(data, aes(x, y)) + geom_line()
- # Not all geoms require both x and y, e.g., geom_bar() and geom_histogram().
- # For these two geoms, if the y aesthetic is not supplied, both qplot and
- # ggplot commands default to "count" on the y-axis
- # ggplot(data, aes(x)) + geom_bar()
- # qplot(x, data = data, geom = "bar")
- # If a vector of multiple geom names is supplied to the geom argument, each
- # geom will be added in turn
- # qplot(x, y, data = data, geom = c("point", "smooth"))
- # ggplot(data, aes(x, y)) + geom_point() + geom_smooth()
- # Unlike the rest of ggplot2, stats and geoms are independent
- # qplot(x, y, data = data, stat = "bin")
- # ggplot(data, aes(x, y)) + geom_point(stat = "bin")
- #
- # Any layer parameters will be passed on to all layers. Most layers will ignore
- # parameters that they don't need
- # qplot(x, y, data = data, geom = c("point", "smooth"), method = "lm")
- # ggplot(data, aes(x, y)) + geom_point(method = "lm") + geom_smooth(method = "lm")
- # Scales and axes
- # You can control basic properties of the x and y scales with the xlim, ylim,
- # xlab and ylab arguments
- # qplot(x, y, data = data, xlim = c(1, 5), xlab = "my label")
- # ggplot(data, aes(x, y)) + geom_point() +
- # scale_x_continuous("my label", limits = c(1, 5))
- # qplot(x, y, data = data, xlim = c(1, 5), ylim = c(10, 20))
- # ggplot(data, aes(x, y)) + geom_point() +
- # scale_x_continuous(limits = c(1, 5)) + scale_y_continuous(limits = c(10, 20))
- # Like plot(), qplot() has a convenient way of log transforming the axes.
- # qplot(x, y, data = data, log = "xy")
- # ggplot(data, aes(x, y)) + geom_point() + scale_x_log10() + scale_y_log10()
- # There are many other possible transformations, but not all are
- # accessible from within qplot(), see ?scale_continuous for more
- # Plot options
- # qplot() recognises the same options as plot does, and converts them to their
- # ggplot2 equivalents. See ?theme for more on ggplot options
- # qplot(x, y, data = data, main="title", asp = 1)
- # ggplot(data, aes(x, y)) + geom_point() + labs(title = "title") + theme(aspect.ratio = 1)
- }