In base R, the function to use would be reshape, and you would be converting your data from "long" to "wide".
reshape(mydf, direction = "wide", idvar="perid", timevar="date")
# perid rating.2005 rating.2006 rating.2007 rating.2008 rating.2009 rating.2010 rating.2011
# 1 10001 RD GN GD <NA> <NA> <NA> <NA>
# 4 10002 <NA> <NA> <NA> GD YW GN GN
# 8 10003 GD GN YW <NA> <NA> <NA> <NA>
Alternatively, you can look at dcast from the "reshape2" package and try:
library(reshape2)
dcast(mydf, perid ~ date, value.var="rating")
# perid 2005 2006 2007 2008 2009 2010 2011
# 1 10001 RD GN GD <NA> <NA> <NA> <NA>
# 2 10002 <NA> <NA> <NA> GD YW GN GN
# 3 10003 GD GN YW <NA> <NA> <NA> <NA>
For better speed, convert your data.frame to a data.table and use dcast.data.table instead.
library(reshape2)
library(data.table)
DT <- data.table(mydf)
dcast.data.table(DT, perid ~ date, value.var = "rating")
# perid 2005 2006 2007 2008 2009 2010 2011
# 1: 10001 RD GN GD NA NA NA NA
# 2: 10002 NA NA NA GD YW GN GN
# 3: 10003 GD GN YW NA NA NA NA
From your comments, it sounds like you have duplicated values among the combinations of column 1 and 2, which means that by default, dcast will use length as its aggregation function.
To get past this, you need to make a secondary ID (or "time", actually) column, which can be done like this.
First, some sample data. Note the duplicated combination of the first two columns in rows 1 and 2.
mydf <- data.frame(
period = c(10001, 10001, 10002, 10002, 10003, 10003, 10001, 10001),
date = c(2005, 2005, 2006, 2007, 2005, 2006, 2006, 2007),
rating = c("RD", "GN", "GD", "GD", "YW", "GN", "GD", "YN"))
mydf
# period date rating
# 1 10001 2005 RD
# 2 10001 2005 GN
# 3 10002 2006 GD
# 4 10002 2007 GD
# 5 10003 2005 YW
# 6 10003 2006 GN
# 7 10001 2006 GD
# 8 10001 2007 YN
When you try dcast, it just "counts" the number under each combination.
## Not what you want
dcast(mydf, period ~ date, value.var="rating")
# Aggregation function missing: defaulting to length
# period 2005 2006 2007
# 1 10001 2 1 1
# 2 10002 0 1 1
# 3 10003 1 1 0
Either decide which duplicated row should be dropped, or, if all the data belongs in your dataset, add a "time" variable, like this:
mydf$time <- ave(1:nrow(mydf), mydf$period, mydf$date, FUN = seq_along)
mydf
# period date rating time
# 1 10001 2005 RD 1
# 2 10001 2005 GN 2
# 3 10002 2006 GD 1
# 4 10002 2007 GD 1
# 5 10003 2005 YW 1
# 6 10003 2006 GN 1
# 7 10001 2006 GD 1
# 8 10001 2007 YN 1
Now, dcast should work fine. Here's a semi-long version...
dcast(mydf, period + time ~ date, value.var="rating")
# period time 2005 2006 2007
# 1 10001 1 RD GD YN
# 2 10001 2 GN <NA> <NA>
# 3 10002 1 <NA> GD GD
# 4 10003 1 YW GN <NA>
... and a semi-wide version.
dcast(mydf, period ~ date + time, value.var="rating")
# period 2005_1 2005_2 2006_1 2007_1
# 1 10001 RD GN GD YN
# 2 10002 <NA> <NA> GD GD
# 3 10003 YW <NA> GN <NA>
