A broad selection on the Web. For instance, here's a massive directory of sports databases (all providing the data free of charge, at least that's my experience). In that directory is databaseBaseball.com, which contains among other things, complete datasets for every player who has ever played professional baseball since about 1915.
StatLib is an other excellent resource--beautifully convenient. This single web page lists 4-5 line summaries of over a hundred databases, all of which are available in flat-file form just by clicking the 'Table' link at the beginning of each data set summary.
The base distribution of R comes pre-packaged with a large and varied collection of datasts (122 in R 2.10). To get a list of them (as well as a one-line description):
data(package="datasets")
Likewise, most packages come with several data sets (sometimes a lot more). You can see those the same way:
data(package="latticeExtra")
data(package="vcd")
These data sets are the ones mentioned in the package manuals and vignettes for a given package, and used to illustrate the package features.
A few R packages with a lot of datasets (which again are easy to scan so you can choose what's interesting to you): AER, DAAG, and vcd.
Another thing i find so impressive about R is its I/O. Suppose you want to get some very specific financial data via the yahoo finance API. Let's say closing open and closing price of S&P 500 for every month from 2001 to 2009, just do this:
tick_data = read.csv(paste("http://ichart.finance.yahoo.com/table.csv?",
"s=%5EGSPC&a=03&b=1&c=2001&d=03&e=1&f=2009&g=m&ignore=.csv"))
In this one line of code, R has fetched the tick data, shaped it to a dataframe and bound it to 'tick_data' all . (Here's a handy cheat sheet w/ the Yahoo Finance API symbols used to build the URLs as above)
