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Create a density plot with ggplot2 using a factor

Tags:

r

ggplot2

I'm using this data set (at the bottom) to create a density plot, but am having issue with the factor and getting it to aggregate properly. I want the graph to look like this:

ggplot(sample, aes(as.numeric(value), colour=shortname)) + geom_density()

But I want the x-axis to have the actual labels of the factors. But when I use this:

ggplot(sample, aes(value, colour=shortname)) + geom_density()

the graph doesn't aggregate them into the two distinct values of the shortname variable.

What am I doing wrong? I've read about using scale_x_discrete(), but I don't think I should need to since I already have a factor...

UPDATE: Even if I use scale_x_discrete in the following way:

ggplot(sample, aes(value, colour=shortname)) + geom_density() + scale_x_discrete(breaks=1:27, labels=c("<A",LETTERS))

that just removes the x-axis labels all together...

Thank you in advance!

sample <- structure(list(shortname = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("H1", 
"H2"), class = "factor"), value = structure(c(7L, 17L, 8L, 15L, 
18L, 17L, 14L, 19L, 20L, 17L, 17L, 12L, 16L, 21L, 2L, 21L, 19L, 
22L, 12L, 15L, 22L, 19L, 16L, 13L, 19L, 24L, 15L, 24L, 23L, 12L, 
24L, 21L, 15L, 16L, 16L, 18L, 18L, 8L, 23L, 8L, 21L, 24L, 13L, 
10L, 18L, 1L, 7L, 14L, 13L, 21L, 16L, 10L, 15L, 21L, 17L, 18L, 
18L, 21L, 14L, 9L, 22L, 14L, 11L, 16L, 13L, 18L, 12L, 1L, 23L, 
8L, 15L, 18L, 11L, 10L, 20L, 16L, 12L, 10L, 22L, 25L, 24L, 7L, 
19L, 13L, 16L, 16L, 20L, 3L, 13L, 21L, 12L, 16L, 13L, 15L, 1L, 
19L, 12L, 20L, 12L, 11L, 20L, 7L, 22L, 18L, 19L, 9L, 10L, 24L, 
10L, 13L, 5L, 16L, 19L, 20L, 19L, 18L, 19L, 19L, 13L, 12L, 21L, 
20L, 13L, 21L, 3L, 12L, 19L, 17L, 16L, 9L, 21L, 18L, 24L, 2L, 
12L, 13L, 14L, 7L, 16L, 10L, 21L, 15L, 21L, 11L, 18L, 3L, 16L, 
15L, 22L, 10L, 16L, 21L, 19L, 17L, 20L, 22L, 17L, 20L, 2L, 24L, 
12L, 18L, 19L, 24L, 26L, 17L, 20L, 15L, 12L, 10L, 16L, 12L, 12L, 
15L, 19L, 14L, 22L, 12L, 7L, 16L, 1L, 20L, 18L, 24L, 19L, 22L, 
3L, 16L, 19L, 22L, 5L, 19L, 17L, 16L, 13L, 22L, 3L, 14L, 12L, 
9L, 5L, 16L, 14L, 15L, 12L, 2L, 12L, 19L, 20L, 18L, 10L, 3L, 
20L, 4L, 16L, 19L, 1L, 14L, 24L, 9L, 14L, 1L, 12L, 6L, 1L, 22L, 
11L, 13L, 19L, 16L, 22L, 25L, 3L, 21L, 21L, 22L, 3L, 21L, 18L, 
23L, 24L, 2L, 21L, 15L, 15L, 16L, 11L, 13L, 25L, 11L, 17L, 15L, 
7L, 23L, 21L, 4L, 1L, 14L, 19L, 13L, 10L, 18L, 3L, 13L, 17L, 
12L, 7L, 21L, 17L, 17L, 17L, 17L, 10L, 21L, 24L, 22L, 12L, 22L, 
12L, 24L, 17L, 16L, 21L, 19L, 16L, 16L, 16L, 21L, 13L, 1L, 7L, 
21L, 11L, 13L, 10L, 21L, 11L, 25L, 1L, 11L, 3L, 24L, 13L, 13L, 
15L, 7L, 21L, 16L, 24L, 16L, 8L, 19L, 13L, 18L, 18L, 22L, 19L, 
16L, 16L, 15L, 5L, 4L, 14L, 8L, 15L, 18L, 13L, 14L, 12L, 19L, 
16L, 3L, 16L, 17L, 1L, 19L, 20L, 19L, 1L, 19L, 20L, 22L, 8L, 
12L, 13L, 24L, 16L, 14L, 21L, 25L, 22L, 4L, 16L, 16L, 15L, 16L, 
8L, 14L, 12L, 11L, 5L, 13L, 19L, 27L, 3L, 18L, 12L, 13L, 19L, 
7L, 10L, 15L, 23L, 11L, 3L, 24L, 18L, 15L, 16L, 14L, 16L, 22L, 
11L, 11L, 20L, 18L, 14L, 20L, 21L, 3L, 10L, 19L, 14L, 16L, 8L, 
12L, 16L, 8L, 21L, 26L, 13L, 6L, 9L, 2L, 15L, 1L, 12L, 24L, 3L, 
21L, 24L, 8L, 18L, 20L, 3L, 19L, 12L, 15L, 8L, 18L, 14L, 19L, 
10L, 20L, 17L, 12L, 17L, 19L, 14L, 10L, 7L, 11L, 12L, 3L, 19L, 
1L, 16L, 11L, 8L, 3L, 10L, 15L, 21L, 27L, 3L, 3L, 19L, 5L, 17L, 
22L, 10L, 3L, 15L, 19L, 19L, 18L, 23L, 1L, 22L, 9L, 22L, 19L, 
12L, 18L, 10L, 10L, 9L, 14L, 2L, 27L, 21L, 4L, 18L, 1L, 2L, 16L, 
3L, 21L, 19L, 24L, 12L, 12L, 19L, 13L, 16L, 19L, 20L, 12L, 20L, 
13L, 9L, 15L, 22L, 14L, 5L, 22L, 15L, 3L, 9L, 3L, 12L, 2L, 12L, 
12L, 22L, 15L, 9L, 3L, 21L, 14L, 5L, 5L, 10L, 5L, 5L, 1L, 7L, 
21L, 19L, 22L, 1L, 9L, 1L, 21L, 18L, 15L, 14L, 21L, 6L, 19L, 
15L, 16L, 5L, 5L, 10L, 20L, 5L, 8L, 19L, 3L, 16L, 5L, 7L, 17L, 
16L, 19L, 2L, 20L, 15L, 9L, 17L, 21L, 19L, 13L, 3L, 13L, 12L, 
21L, 16L, 15L, 17L, 16L, 19L, 8L, 17L, 14L, 1L, 1L, 22L, 19L, 
24L, 20L, 10L, 17L, 1L, 17L, 1L, 17L, 13L, 15L, 21L, 6L, 3L, 
18L, 20L, 15L, 4L, 16L, 8L, 12L, 10L, 13L, 13L, 22L, 11L, 12L, 
1L, 21L, 21L, 5L, 5L, 16L, 11L, 20L, 21L, 20L, 21L, 20L, 19L, 
20L, 15L, 25L, 9L, 1L, 12L, 21L, 9L, 24L, 3L, 12L, 24L, 8L, 16L, 
15L, 9L, 20L, 15L, 5L, 10L, 1L, 16L, 16L, 12L, 9L, 20L, 10L, 
19L, 12L, 3L, 20L, 22L, 11L, 16L, 16L, 22L, 19L, 19L, 22L, 14L, 
14L, 12L, 5L, 14L, 19L, 18L, 19L, 18L, 3L, 10L, 20L, 14L, 1L, 
13L, 18L, 13L, 1L, 22L, 23L, 19L, 13L, 18L, 9L, 16L, 15L, 17L, 
21L, 15L, 18L, 1L, 14L, 14L, 1L, 14L, 9L, 16L, 12L, 22L, 14L, 
2L, 22L, 19L, 21L, 16L, 16L, 11L, 19L, 13L, 3L, 16L, 16L, 20L, 
18L, 1L, 19L, 11L, 17L, 19L, 12L, 15L, 10L, 11L, 13L, 7L, 14L, 
14L, 14L, 15L, 15L, 16L, 14L, 22L, 20L, 17L, 19L, 19L, 13L, 16L, 
12L, 15L, 20L, 22L, 17L, 20L, 16L, 10L, 15L, 15L, 12L, 12L, 14L, 
20L, 5L, 19L, 2L, 13L, 15L, 17L, 9L, 14L, 18L, 2L, 10L, 14L, 
12L, 14L, 12L, 18L, 17L, 13L, 8L, 22L, 12L, 21L, 12L, 13L, 3L, 
14L, 26L, 4L, 3L, 1L, 7L, 10L, 19L, 16L, 16L, 15L, 13L, 15L, 
16L, 11L, 21L, 12L, 11L, 15L, 1L, 16L, 1L, 17L, 6L, 1L, 16L, 
7L, 11L, 2L, 5L, 16L, 5L, 12L, 13L, 12L, 13L, 13L, 12L, 20L, 
21L, 21L, 12L, 19L, 21L, 18L, 12L, 15L, 22L, 19L, 16L, 16L, 3L, 
14L, 1L, 7L, 13L, 16L, 11L, 7L, 12L, 16L, 16L, 12L, 22L, 1L, 
13L, 4L, 8L, 16L, 5L, 11L, 10L, 1L, 21L, 10L, 19L, 12L, 13L, 
16L, 12L, 15L, 19L, 13L, 1L, 1L, 2L, 6L, 16L, 14L, 15L, 15L, 
16L, 4L, 12L, 16L, 10L, 19L, 12L, 5L, 6L, 10L, 3L, 14L, 1L, 12L, 
4L, 11L, 16L, 10L, 20L, 4L, 13L, 10L, 1L, 9L, 2L, 7L, 9L, 18L, 
10L, 26L, 14L, 2L, 14L, 10L, 11L, 13L, 1L, 21L, 16L, 9L, 22L, 
12L, 12L, 16L, 15L, 12L, 8L, 15L, 20L, 11L, 16L, 15L, 12L, 12L, 
16L, 2L, 9L, 12L, 14L, 20L, 1L, 10L, 7L, 10L, 18L, 16L, 12L, 
15L, 12L, 14L, 3L, 14L, 6L, 10L, 1L, 11L, 9L, 5L, 12L, 12L, 1L, 
8L, 20L, 7L, 21L, 20L, 22L, 20L, 7L, 12L, 9L, 7L, 13L, 19L, 15L, 
15L, 18L, 16L, 1L, 10L, 19L, 2L, 13L, 6L, 24L, 1L, 22L, 16L, 
11L, 7L, 5L, 19L, 15L, 14L, 12L, 19L, 14L, 12L, 15L, 24L, 15L, 
10L, 4L, 14L, 16L, 3L, 21L, 1L, 19L, 14L, 17L, 12L, 21L, 3L, 
12L, 16L, 18L, 14L, 15L, 15L, 14L, 1L, 2L, 17L, 1L, 14L, 16L, 
15L, 14L, 10L, 14L, 17L, 17L, 12L, 17L, 11L, 14L, 16L, 1L, 1L, 
19L, 12L, 24L, 15L, 19L, 14L, 8L, 3L, 22L, 1L, 16L, 15L, 19L, 
8L, 15L, 12L, 8L, 14L, 8L, 12L, 7L, 13L, 2L, 13L, 10L, 15L, 15L, 
17L, 1L, 26L, 24L, 21L, 25L, 14L, 10L, 13L, 9L, 13L, 18L, 19L, 
16L, 21L, 16L, 17L, 14L, 14L, 11L, 17L, 16L, 12L, 17L, 14L, 6L, 
24L, 11L, 11L, 11L, 12L, 15L, 13L, 22L, 11L, 17L, 3L, 12L, 17L, 
14L, 10L, 11L, 9L, 21L, 18L, 19L, 20L, 24L, 7L, 12L, 22L, 3L, 
17L, 10L, 1L, 20L, 1L, 1L, 12L, 2L, 14L, 2L, 17L, 19L, 1L, 10L, 
12L, 16L, 15L, 3L, 12L, 16L, 12L, 15L, 17L, 24L, 15L, 16L, 8L, 
12L, 14L, 21L, 9L, 23L, 3L, 19L, 16L, 19L, 16L, 16L, 13L, 13L, 
3L, 9L, 17L, 1L, 1L, 16L, 11L, 15L, 7L, 7L, 14L, 8L, 14L, 20L, 
15L, 16L, 1L, 12L, 9L, 16L), .Label = c("<A", "A", "B", "C", 
"D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", 
"Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"), class = "factor")), .Names = c("shortname", 
"value"), row.names = c(NA, 1156L), class = "data.frame")
like image 841
Jeff Erickson Avatar asked Dec 24 '12 17:12

Jeff Erickson

People also ask

What is a density plot Ggplot?

A density plot is a representation of the distribution of a numeric variable. It is a smoothed version of the histogram and is used in the same kind of situation. Here is a basic example built with the ggplot2 library. Density Section Density theory. Density plots are built in ggplot2 thanks to the geom_density geom.

How density plot is created?

A density plot is constructed from a numeric variable. A second variable may be used to divide the first variable into groups (e.g., age group or gender). In the two-factor procedure, a third variable may be used to divide the groups into subgroups.

1 Answers

You can get the desired behavior with:

ggplot(sample, aes(value, colour=shortname, group=shortname)) + geom_density()

Note the letter labels at the bottom of the plot, which weren't present with the as.numeric solution:

enter image description here

like image 144
David Robinson Avatar answered Oct 03 '22 08:10

David Robinson
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How can I merge and maintain the row order of one input? [duplicate]
knitr and UTF8 encoding
How to create new polygons by simplifying from two SpatialPolygonsDataFrame objects in R?
Floating barcharts
Ordering bar plots with ggplot2 according to their size, i.e. numerical value
R: integer versus numeric
How to vectorize triple nested loops?
does the by( ) function make growing list
Interpolation of time series data with specific output time

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