Question

I’m working through the examples in Kruschke’s Doing Bayesian Data Analysis and need a bit of help understanding how to get data into the format that his code examples require. In chapter 22 he has a table like this

         Blue  Brown  Green Hazel
Black    20    68     5     15
Blond    94    7      16    10
Brunette 84    119    29    54
Red      17    26     14    14

I’m comfortable with inputting the table into R by entering it into a spreadsheet and using read.table("clipboard", header=T, sep="\t") or typing it into R like this

con.table2 <- matrix(c(20,68,5,15,94,7,16,10,84,119,29,54,17,26,14,14),nrow=4,byrow=TRUE)
dimnames(con.table2) <- list(c("Black","Blond","Brunette","Red"),c("Blue","Brown","Green","Hazel"))

But in his code, he presents this table like so, ready for analysis (full code is here http://www.indiana.edu/~kruschke/DoingBayesianDataAnalysis/Programs/PoissonExponentialJagsSTZ.R)

Freq = c(68,119,26,7,20,84,17,94,15,54,14,10,5,29,14,16)
Eye = c("Brown","Brown","Brown","Brown","Blue","Blue","Blue","Blue","Hazel" # runs off the page of his book
Hair = c("Black","Brunette","Red","Blond","Black","Brunette","Red","Blond","Black" # runs off the page of his book

It looks like the table has been converted into three vectors. What’s the most efficient way to do this? I’d like to replace his data with my own, so it would be great to learn how to transform the data into the format needed for this analysis.

Answer 1

For this, I’d use melt() in the reshape2 package:

library(reshape2)
df <- melt(con.table2, varnames=c("Hair", "Eye"), value.name="Freq")

# df is a data frame, a list from which you can easily extract the
# component vectors "Hair", "Eye", and "Freq. 
# Try, for example:
str(df)
df$Hair