How do use different points sizes to represent the amount in the location of that point

Question

I'm working with categorical data and I'm trying to plot a scatterplot where the size of the points should represent the frequencies on the location of that point.

I tried it first with jitter but I'm unhappy with that solution.

I thought I could create a Frequencies column but didn't manage to create a code for that.

    qplot(X, Y, data=datatable, geom=c("point"))

Has anyone an idea?

thx

Answer 1

Here's a guess at what you're after. In the df data frame below, x and y are your categorical variables. There are various ways to get the frequency counts. Here, the ddply() function from the plyr package is used. Followed by the plot. In the call to ggplot: the size aesthetic ensures that the point sizes represent the frequencies; and the scale_size_discrete() function controls the size of the points on the plot.

# Some toy data
df <- structure(list(x = structure(c(1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 
4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 
5L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 
4L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 1L, 2L, 1L, 2L, 
3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 4L, 5L, 1L, 2L, 3L, 
4L, 5L, 1L, 2L, 3L, 4L, 5L), .Label = c("1", "2", "3", "4", "5"
), class = "factor"), y = structure(c(1L, 1L, 1L, 1L, 1L, 2L, 
2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 
5L, 5L, 5L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 
4L, 4L, 4L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 
1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 4L, 
4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L), .Label = c("1", "2", "3", 
"4", "5"), class = "factor")), .Names = c("x", "y"), row.names = c(NA, 
79L), class = "data.frame")

# Required packages
library(plyr)
library(ggplot2)

# Get the frequency counts
dfc <- ddply(df, c("x", "y"), "nrow", .drop = FALSE)
#dfc

# The plot
ggplot(data = dfc, aes(x = x, y = y, size = factor(nrow))) + 
    geom_point() + 
    scale_size_discrete(range = c(1, 10))

Or the same plot using the df data frame - the unaggregated data.

ggplot(data = df, aes(x = x, y = y)) +
  stat_sum(aes(size = factor(..n..)), geom = "point") +
  scale_size_discrete(range = c(1, 10))