Points, as for a scatterplot


geom_point(mapping = NULL, data = NULL, stat = "identity", position = "identity",
  na.rm = FALSE, ...)


The aesthetic mapping, usually constructed with aes or aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.
A layer specific dataset - only needed if you want to override the plot defaults.
The statistical transformation to use on the data for this layer.
The position adjustment to use for overlappling points on this layer
If FALSE (the default), removes missing values with a warning. If TRUE silently removes missing values.
other arguments passed on to layer. This can include aesthetics whose values you want to set, not map. See layer for 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 geom_jitter for possibilities.

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 information with stat_smooth, stat_quantile or stat_density2d. If you have few unique x values, 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 transparent points, geom_point(alpha = 0.05).


geom_point understands the following aesthetics (required aesthetics are in bold):

  • x
  • y
  • alpha
  • colour
  • fill
  • shape
  • size


p <- ggplot(mtcars, aes(wt, mpg)) p + geom_point()

# Add aesthetic mappings p + geom_point(aes(colour = qsec))

p + geom_point(aes(alpha = qsec))

p + geom_point(aes(colour = factor(cyl)))

p + geom_point(aes(shape = factor(cyl)))

p + geom_point(aes(size = qsec))

# Change scales p + geom_point(aes(colour = cyl)) + scale_colour_gradient(low = "blue")

p + geom_point(aes(size = qsec)) + scale_area()
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)

p + geom_point(aes(shape = factor(cyl))) + scale_shape(solid = FALSE)

# Set aesthetics to fixed value p + geom_point(colour = "red", size = 3)

qplot(wt, mpg, data = mtcars, colour = I("red"), size = I(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)))

# Transparent points: qplot(mpg, wt, data = mtcars, size = I(5), alpha = I(0.2))

# 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)

qplot(wt, mpg, data = mtcars, colour = factor(cyl))

qplot(wt, mpg, data = mtcars, colour = I("red"))

See also

scale_size to see scale area of points, instead of radius, geom_jitter to jitter points to reduce (mild) overplotting