How to make boxplots with presorted data by R?

Question

I'm a beginner in R and is currently working on graph generating by R. Typically most data examples are as diamonds in ggplot2:

carat cut color clarity depth table price x y z

0.2 Ideal E SI2 61.5 55.0 326 3.95 3.98 2.43

0.2 Premium E SI1 59.8 61.0 326 3.89 3.84 2.31

0.2 Good E VS1 56.9 65.0 327 4.05 4.07 2.31

0.3 Premium I VS2 62.4 58.0 334 4.20 4.23 2.63

0.3 Good J SI2 63.3 58.0 335 4.34 4.35 2.75

0.2 Very Good J VVS2 62.8 57.0 336 3.94 3.96 2.48

Which means if a boxplot is plotted, R will initially sort the data according to cut. On the contrary, how about a dataset like:

cut price1 price2 price3

Good  0.68 0.89 0.74

Medium 0.12 0.35 0.26

Does this mean all of the values in each category is presorted? I wonder what method could be used to deal with this type of data to draw boxplot.

Answer 1

What you probably want to do is to "melt" your data (transform it from "wide" to "long" format). For example:

# Melt your dataset
library(reshape2)
# Here we melt dataset by "cut" (ie, we group by this column)
dataset_melt <- melt(dataset, "cut")

# How melted dataset looks like
#      cut variable value
# 1:   Good   price1  0.68
# 2: Medium   price1  0.12
# 3:   Good   price2  0.89
# 4: Medium   price2  0.35
# 5:   Good   price3  0.74
# 6: Medium   price3  0.26

# Plot melted dataset
library(ggplot2)
ggplot(dataset_melt, aes(cut, value)) + 
    geom_boxplot()