geom_point

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

Points, as for a scatterplot

The point geom is used to create scatterplots.

This page describes geom_point, see layer and qplot for how to create a complete plot from individual components.

Advice

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(colour=alpha('black', 0.05))

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Aesthetics

The following aesthetics can be used with geom_point. Aesthetics are mapped to variables in the data with the aes function: geom_point(aes(x = var)). Note that you do not need quotes around the variable name.

Scales control how the variable is mapped to the aesthetic and are listed after each aesthetic.

Aesthetic	Default	Related scales
x	required	continuous, date, datetime, discrete
y	required	continuous, date, datetime, discrete
shape	16	identity, manual, shape
colour	black	brewer, gradient, gradient2, gradientn, grey, hue, identity, manual
size	2	identity, manual, size
fill	NA	brewer, gradient, gradient2, gradientn, grey, hue, identity, manual
alpha	1

Layers are divided into groups by the group aesthetic. By default this is set to the interaction of all categorical variables present in the plot.

Parameters

Parameters control the appearance of the geom. In addition to the parameters listed below (if any), any aesthetic can be used as a parameter, in which case it will override any aesthetic mapping.

na.rm: NULL

Returns

This function returns a layer object.

Examples

> 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() 
  
> 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, legend = TRUE) + 
+   geom_point(colour="pink", size = 4, legend = 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: Removed 3 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"))