# 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)