R Scatter Plot: Symbol Color Represents Number of Overlapping Points

R Scatter Plot: symbol color represents number of overlapping points

One option is to use densCols() to extract kernel densities at each point. Mapping those densities to the desired color ramp, and plotting points in order of increasing local density gets you a plot much like those in the linked article.

## Data in a data.frame
x1 <- rnorm(n=1E3, sd=2)
x2 <- x1*1.2 + rnorm(n=1E3, sd=2)
df <- data.frame(x1,x2)

## Use densCols() output to get density at each point
x <- densCols(x1,x2, colramp=colorRampPalette(c("black", "white")))
df$dens <- col2rgb(x)[1,] + 1L

## Map densities to colors
cols <-  colorRampPalette(c("#000099", "#00FEFF", "#45FE4F", 
                            "#FCFF00", "#FF9400", "#FF3100"))(256)
df$col <- cols[df$dens]

## Plot it, reordering rows so that densest points are plotted on top
plot(x2~x1, data=df[order(df$dens),], pch=20, col=col, cex=2)

R—Plotting the number of points that overlap rather than a symbol

Welcome to SO!

You need to get the "count" of observations for each x,y pair and then you can use annotation to get your plot. Here's an example using data.table and ggplot2:

library(data.table)
library(ggplot2)

# using a sample dataset 
dat <- as.data.table(mtcars)

# creating a variable called "count" for no. of overlaps for a given (gear,carb) pair 
ggplot(dat[, .(count = .N), by = .(gear, carb)]) + 
  geom_text(aes(x = gear, y= carb, label = count) )

You can format the text any way you want (font, size etc.) or combined with other items e.g. add geom_point so you see a point along with the text - you can set the transparency or size based on the number of overlapping points (count in this example).

# Using nudge_x, nudge_y to avoid marker and text overlap
ggplot(dat[, .(count = .N), by = .(gear, carb)]) + 
  geom_text(aes(x = gear, y= carb, label = count), nudge_x = 0.05, nudge_y = 0.05) + 
  geom_point(aes(x = gear, y = carb), color = 'dark red')

Hope this is helpful!

Scatterplot with too many points

One way to deal with this is with alpha blending, which makes each point slightly transparent. So regions appear darker that have more point plotted on them.

This is easy to do in ggplot2:

df <- data.frame(x = rnorm(5000),y=rnorm(5000))
ggplot(df,aes(x=x,y=y)) + geom_point(alpha = 0.3)

Another convenient way to deal with this is (and probably more appropriate for the number of points you have) is hexagonal binning:

ggplot(df,aes(x=x,y=y)) + stat_binhex()

And there is also regular old rectangular binning (image omitted), which is more like your traditional heatmap:

ggplot(df,aes(x=x,y=y)) + geom_bin2d()

Identify overlapping points in scatter plot

The sp package has a function point.in.polygon that does the trick

library(sp)
In1 = which(point.in.polygon(d1$x, d1$y, p3$X, p3$Y) != 0)
points(d1$x[In1], d1$y[In1], pch = 19, col = "orange")
In2 = which(point.in.polygon(d2$x, d2$y, p3$X, p3$Y) != 0)
points(d2$x[In2], d2$y[In2], pch = 19, col = "orange")

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