Read a time series table using read.zoo

Question

I've looked all over the place, but I can't find where this question has been asked before.

What is a clean way to get this data into a proper zoo series? This version is a copy/paste to make this post easier, but it will always come in the following table form (from a text file). My read.zoo() statement reads the Year as the index but the quarters (Qtr1, Qtr2, etc) are read as column names. I've been trying to figure out a non-garbage way to read the columns as the "quarter" part of the index, but it's sloppy (too sloppy to post). I'm guessing this problem has already been solved, but I can't find it.

> texinp <- "   
+ Year   Qtr1  Qtr2  Qtr3  Qtr4   
+ 1992    566   443   329   341   
+ 1993    344   212   133   112   
+ 1994    252   252   199   207"   
> z <- read.zoo(textConnection(texinp), header=TRUE)
> z  

From the as.yearqtr() documentation, the target would look like:

1992 Q1 1992 Q2 1992 Q3 1992 Q4 1993 Q1 1993 Q2 1993 Q3 1993 Q4    
    566     443     329     341     344     212     133     112      

1994 Q1 1994 Q2 1994 Q3 1994 Q4     
    252     252     199     207    

Answer 1

Read in the data using read.zoo and then convert it to a zooreg object with yearqtr time index:

texinp <- "Year   Qtr1  Qtr2  Qtr3  Qtr4   
1992    566   443   329   341   
1993    344   212   133   112   
1994    252   252   199   207"

library(zoo)

z <- read.zoo(text = texinp, header=TRUE)
zz <- zooreg(c(t(z)), start = yearqtr(start(z)), freq = 4)

The result looks like this:

> zz

1992 Q1 1992 Q2 1992 Q3 1992 Q4 1993 Q1 1993 Q2 1993 Q3 1993 Q4 1994 Q1 1994 Q2 1994 Q3 1994 Q4 
    566     443     329     341     344     212     133     112     252     252     199     207 

Answer 2

read.zoo assumes your data has at most one time-index column, so you have to process this yourself. First read it in using read.table

zt <- read.table( textConnection( texinp ), header = TRUE)

then convert it to a "long table" using the melt function from the reshape package:

require(reshape)
zt.m <- melt( zt, id = 'Year', variable_name = 'Qtr')

> zt.m
   Year  Qtr value
1  1992 Qtr1   566
2  1993 Qtr1   344
3  1994 Qtr1   252
4  1992 Qtr2   443
5  1993 Qtr2   212
6  1994 Qtr2   252
7  1992 Qtr3   329
8  1993 Qtr3   133
9  1994 Qtr3   199
10 1992 Qtr4   341
11 1993 Qtr4   112
12 1994 Qtr4   207

and finally create your desired zoo object:

z <- with( zt.m, zoo( value, as.yearqtr(paste(Year, Qtr), format = '%Y Qtr%q')))

> z
1992 Q1 1992 Q2 1992 Q3 1992 Q4 1993 Q1 1993 Q2 1993 Q3 1993 Q4 1994 Q1 1994 Q2 
    566     443     329     341     344     212     133     112     252     252 
1994 Q3 1994 Q4 
    199     207