geom_point(mapping = NULL, data = NULL, stat = "identity", position = "identity", na.rm = FALSE, ...)
aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.
FALSE(the default), removes missing values with a warning. If
TRUEsilently removes missing values.
layer. This can include aesthetics whose values you want to set, not map. See
layerfor more details.
The point geom is used to create scatterplots.
The scatterplot is useful for displaying the relationship
between two continuous variables, although it can also be
used with one continuous and one categorical variable, or
two categorical variables. See
The bubblechart is a scatterplot with a third variable mapped to the size of points. There are no special names for scatterplots where another variable is mapped to point shape or colour, however.
The biggest potential problem with a scatterplot is
overplotting: whenever you have more than a few points,
points may be plotted on top of one another. This can
severely distort the visual appearance of the plot. There
is no one solution to this problem, but there are some
techniques that can help. You can add additional
stat_density2d. If you have few unique x
geom_boxplot may also be useful.
Alternatively, you can summarise the number of points at
each location and display that in some way, using
stat_sum. Another technique is to use
geom_point(alpha = 0.05).
geom_point understands the following aesthetics (required aesthetics are in bold):
# Set aesthetics to fixed value p + geom_point(colour = "red", size = 3)
# Varying alpha is useful for large datasets d <- ggplot(diamonds, aes(carat, price)) d + geom_point(alpha = 1/10)
d + geom_point(alpha = 1/20)
d + geom_point(alpha = 1/100)
# You can create interesting shapes by layering multiple points of # different sizes p <- ggplot(mtcars, aes(mpg, wt)) p + geom_point(colour="grey50", size = 4) + geom_point(aes(colour = cyl))
p + aes(shape = factor(cyl)) + geom_point(aes(colour = factor(cyl)), size = 4) + geom_point(colour="grey90", size = 1.5)
p + geom_point(colour="black", size = 4.5) + geom_point(colour="pink", size = 4) + geom_point(aes(shape = factor(cyl)))
# These extra layers don't usually appear in the legend, but we can # force their inclusion p + geom_point(colour="black", size = 4.5, show_guide = TRUE) + geom_point(colour="pink", size = 4, show_guide = TRUE) + geom_point(aes(shape = factor(cyl)))
# geom_point warns when missing values have been dropped from the data set # and not plotted, you can turn this off by setting na.rm = TRUE mtcars2 <- transform(mtcars, mpg = ifelse(runif(32) < 0.2, NA, mpg)) qplot(wt, mpg, data = mtcars2)Warning message: Removed 11 rows containing missing values (geom_point).
qplot(wt, mpg, data = mtcars2, na.rm = TRUE)
# Use qplot instead qplot(wt, mpg, data = mtcars)