stat_sum(mapping = NULL, data = NULL, geom = "point", position = "identity", ...)
aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.
layer. This can include aesthetics whose values you want to set, not map. See
layerfor more details.
a data.frame with additional columns nnumber of observations at position proppercent of points in that panel at that position
Sum unique values. Useful for overplotting on scatterplots.
stat_sum understands the following aesthetics (required aesthetics are in bold):
d <- ggplot(diamonds, aes(x = cut, y = clarity)) # By default, all categorical variables in the plot form grouping # variables, and the default behavior in stat_sum is to show the # proportion. Specifying stat_sum with no group identifier leads to # a plot which is not meaningful: d + stat_sum()
# To correct this problem and achieve a more desirable plot, we need # to specify which group the proportion is to be calculated over. # There are several ways to do this: # by overall proportion d + stat_sum(aes(group = 1))
d + stat_sum(aes(group = 1)) + scale_size(range = c(3, 10))
d + stat_sum(aes(group = 1)) + scale_area(range = c(3, 10))scale_area is deprecated. Use scale_size_area instead. Note that the behavior of scale_size_area is slightly different: by default it makes the area proportional to the numeric value. (Deprecated; last used in version 0.9.2)
# by cut d + stat_sum(aes(group = cut))
d + stat_sum(aes(group = cut, colour = cut))
# by clarity d + stat_sum(aes(group = clarity))
d + stat_sum(aes(group = clarity, colour = cut))
# Instead of proportions, can also use sums d + stat_sum(aes(size = ..n..))
# Can also weight by another variable d + stat_sum(aes(group = 1, weight = price))
d + stat_sum(aes(group = 1, weight = price, size = ..n..))
# Or using qplot qplot(cut, clarity, data = diamonds)
qplot(cut, clarity, data = diamonds, stat = "sum", group = 1)
ggfluctuationfor a fluctuation diagram,