I couldn’t contain myself (other more pressing things to do, but…), so I just took a quick time out and a coffee to put together a quick and dirty R function that will let me run queries over Google spreadsheet data sources and essentially treat them as database tables (e.g. Using Google Spreadsheets as a Database with the Google Visualisation API Query Language).

Here’s the function:

library(RCurl)
gsqAPI = function(key,query,gid=0){ return( read.csv( paste( sep="",'http://spreadsheets.google.com/tq?', 'tqx=out:csv','&tq=', curlEscape(query), '&key=', key, '&gid=', gid) ) ) }

It requires the spreadsheet key value and a query; you can optionally provide a sheet number within the spreadsheet if the sheet you want to query is not the first one.

We can call the function as follows:

gsqAPI('tPfI0kerLllVLcQw7-P1FcQ','select * limit 3')

In that example, and by default, we run the query against the first sheet in the spreadsheet.

Alternatively, we can make a call like this, and run a query against sheet 3, for example:
tmpData=gsqAPI('0AmbQbL4Lrd61dDBfNEFqX1BGVDk0Mm1MNXFRUnBLNXc','select A,C where <= 10',3)
tmpData

The real question is, of course, could it be useful.. (or even OUseful?!)?

Here’s another example: a way of querying the Guardian Datastore list of spreadsheets:

gsqAPI('0AonYZs4MzlZbdFdJWGRKYnhvWlB4S25OVmZhN0Y3WHc','select * where A contains "crime" and B contains "href" order by C desc limit 10')

What that call does is run a query against the Guardian Datastore spreadsheet that lists all the other Guardian Datastore spreadsheets, and pulls out references to spreadsheets relating to “crime”.

The returned data is a bit messy and requires parsing to be properly useful.. but I haven’t started looking at string manipulation in R yet…(So my question is: given a dataframe with a column containing things like <a href=”http://example.com/whatever”>Some Page</a>, how would I extract columns containing http://example.com/whatever or Some Page fields?)

[UPDATE: as well as indexing a sheet by sheet number, you can index it by sheet name, but you’ll probably need to tweak the function to look end with '&gid=', curlEscape(gid) so that things like spaces in the sheet name get handled properly I’m not sure about this now.. calling sheet by name works when accessing the “normal” Google spreadsheets application, but I’m not sure it does for the chart query language call??? ]

[If you haven’t yet discovered R, it’s an environment that was developed for doing stats… I use the RStudio environment to play with it. The more I use it (and I’ve only just started exploring what it can do), the more I think it provides a very powerful environment for working with data in quite a tangible way, not least for reshaping it and visualising it, let alone doing stats with in. (In fact, don’t use the stats bit if you don’t want to; it provides more than enough data mechanic tools to be going on with;-)]

PS By the by, I’m syndicating my Rstats tagged posts through the R-Bloggers site. If you’re at all interested in seeing what’s possible with R, I recommend you subscribe to R-Bloggers, or at least have a quick skim through some of the posts on there…

PPS The RSpatialTips post Accessing Google Spreadsheets from R has a couple of really handy tips for tidying up data pulled in from Google Spreadsheets; assuming the spreadsheetdata has been loaded into ssdata: a) tidy up column names using colnames(ssdata) <- c("my.Col.Name1","my.Col.Name2",...,"my.Col.NameN"); b) If a column returns numbers as non-numeric data (eg as a string "1,000") in cols 3 to 5, convert it to a numeric using something like: for (i in 3:5) ssdata[,i] <- as.numeric(gsub(",","",ssdata[,i])) [The last column can be identifed as ncol(ssdata) You can do a more aggessive conversion to numbers (assuming no decimal points) using gsub("[^0-9]“,”",ssdata[,i])]

PPPS via Revolutions blog, how to read the https file into R (unchecked):

require(RCurl)
myCsv = getURL(httpsCSVurl)
read.csv(textConnection(myCsv))