cycling through a long list of files and names
The more R way to do something like this is to put all your dataframes into a list and then run
lappy(cityList, dataCleaning) # for example
To get them into a list in the first place try this
n = 1997:2011
cityList <- vector(length(n), 'list')
for (i in n){
cityList[[i]] <- get(paste("city", i, sep="")
}
Hope this helps,
Michael
On Oct 22, 2011, at 3:13 PM, Wet Bell Diver <wetbelldiver at gmail.com> wrote:
R2.13.2, W7x64 Dear list, Excuse my ignorance, but I have gone through the R help (?parse, ?eval, etc.) and still really don't know how to do the following. I have the general following structure that I would like to automate [edited to make it shorter]:
city1997 <- dataCleaning(read.csv2("C:\\city\\year1997.txt"))
city1997 <- wasteCalculations(city1997, year = 1997)
if (city1997[1,1] == "Time") {city1997 <- timeCalculations(city1997)}
city1998 <- dataCleaning(read.csv2("C:\\city\\year1998.txt"))
city1998 <- wasteCalculations(city1998, year = 1998)
if (city1998[1,1] == "Time") {city1998 <- timeCalculations(city1998)}
city1999 <- dataCleaning(read.csv2("C:\\city\\year1999.txt"))
city1999 <- wasteCalculations(city1999, year = 1999)
if (city1999[1,1] == "Time") {city1999 <- timeCalculations(city1999)}
[....etc., all the way through....]
city2011 <- dataCleaning(read.csv2("C:\\city\\year2011.txt"))
city2011<- wasteCalculations(city2011, year = 2011)
if (city2011[1,1] == "Time") {city2011 <- timeCalculations(city2011)}
city.df <- data.frame(city1997$waste, city1998$waste, city1999$waste, ...,city2011$waste)
save(city1997, city1998, city1999, ...., city2011, city.df, file = "city.Rdata")
and then the same thing with: municipality1981 through municipality2011
and then the same thing with: county1985 through county2011
So, for both city, municipality, and county, across a (varying) range of years the functions "dataCleaning", "wasteCalculations", and "timeCalculations" are called and the final objects are pulled together in a dataframe and are then all saved together. I can get all of this done manually (generating LONG repetitive code), but I have A LOT of data that needs to be processed like this and that becomes tedious and very repetitious. Besides, it feels silly to do such a task manually when using the powerful R language. Unfortunately, I have no clue how to do this. I have been wrestling with "parse", "eval", "substitute" but I have to admit that I just don't seem to really understand how they work. Anyway, I can't get this to work, but have the feeling it can be done in a few lines. Who can help me with the code and the explanation of why that code works? Thanks, Peter Verbeet
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