"Oh, no!", a hint and a quiery

Remember the superbook on Spatial Statistics? The guy who wrote it (co-), gave a talk in the Universitat Politécnica de Catalunya last Friday. And... your obedient servant was late there while drying here hair at home and looking for a parking spot. NB: Be punctual!

Then, I have a funky dataset of 400 obs and trying to make it more...er... vivid! The point is that I have a Mac, and my only spreadsheet application is the "Numbers" from the iWork package. As far as I know it, it saves data only in its internal format that has a ".numbers" what-a-large extension, or in ".xls". Forget the ".csv"s, ".dbf"s and all extensions you are used to. The data we don't compile, however (God bless the databases administrators!), we receive it as it is. And, if your ".csv"-data is er... laconic you could make it more vivid by making some data mining on your own and adding what you found to your set. For doing that with Mac you have to be able to open your ".csv" as a spreadsheet. You could do that using "Google Docs" by uploading the data, editing it online, and then downloading the vivid dataset as what you want. But you fully depend on your internet connection and the size of your set. Another option is that you use the R command write, save the data as an ".xls"-file, edit it in your "Numbers", then save the result as an ".xls" and read it to R as a new object. Or, if the data is big, you can download one variable, add the data to it in the corresponding order (so you don't have to further sort) and then, read the result to R and merge the two datasets by a key.

Do you have your less lamer tricks to add data to the existing dataset in R? Directly?

Thanks, and don't miss interesting talks!