geom_count {animint2}  R Documentation 
This is a variant geom_point
that counts the number of
observations at each location, then maps the count to point size. It
useful when you have discrete data.
geom_count( mapping = NULL, data = NULL, stat = "sum", position = "identity", ..., na.rm = FALSE, show.legend = NA, inherit.aes = TRUE ) stat_sum( mapping = NULL, data = NULL, geom = "point", position = "identity", ..., na.rm = FALSE, show.legend = NA, inherit.aes = TRUE )
mapping 
Set of aesthetic mappings created by 
data 
The data to be displayed in this layer. There are three options: If A A 
position 
Position adjustment, either as a string, or the result of a call to a position adjustment function. 
... 
other arguments passed on to 
na.rm 
If 
show.legend 
logical. Should this layer be included in the legends?

inherit.aes 
If 
geom, stat 
Use to override the default connection between

geom_point
understands the following aesthetics (required aesthetics are in bold):
x
y
alpha
colour
fill
shape
size
stroke
number of observations at position
percent of points in that panel at that position
ggplot(mpg, aes(cty, hwy)) + geom_point() ggplot(mpg, aes(cty, hwy)) + geom_count() # Best used in conjunction with scale_size_area which ensures that # counts of zero would be given size 0. Doesn't make much different # here because the smallest count is already close to 0. ggplot(mpg, aes(cty, hwy)) + geom_count() scale_size_area() # Display proportions instead of counts  # By default, all categorical variables in the plot form the groups. # Specifying geom_count without a group identifier leads to a plot which is # not useful: d < ggplot(diamonds, aes(x = cut, y = clarity)) d + geom_count(aes(size = ..prop..)) # To correct this problem and achieve a more desirable plot, we need # to specify which group the proportion is to be calculated over. d + geom_count(aes(size = ..prop.., group = 1)) + scale_size_area(max_size = 10) # Or group by x/y variables to have rows/columns sum to 1. d + geom_count(aes(size = ..prop.., group = cut)) + scale_size_area(max_size = 10) d + geom_count(aes(size = ..prop.., group = clarity)) + scale_size_area(max_size = 10)