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cycling through a long list of files and names

9 messages · michael.weylandt at gmail.com (R. Michael Weylandt, Joshua Wiley, R. Michael Weylandt +2 more

Wet Bell Diver
# 
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
michael.weylandt at gmail.com (R. Michael Weylandt
# 
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:

            

      
      
      
    

        

      
      
    

  
  


  


      

    

    

      
      

        


  

        

      R. Michael Weylandt
    

    

      
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A small clarification: the correct syntax would have been

vector("list", length(n))

Michael

On Sat, Oct 22, 2011 at 4:29 PM, R. Michael Weylandt

        
<michael.weylandt at gmail.com> <michael.weylandt at gmail.com> wrote:

            

      
      
      
    

        

      
      
    

            

      
      
      
    

  
  


  


      

    

    

      
      

        


  

        

      Joshua Wiley
    

    

      
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Or simplify things down:

cityList <- mget(paste("city", 1997:2011, sep = ''), envir = .GlobalEnv)

mget returns a list, all in one step.

Cheers,

Josh

On Sat, Oct 22, 2011 at 6:19 PM, R. Michael Weylandt

        
<michael.weylandt at gmail.com> wrote:

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        

      
      
    

        

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      R. Michael Weylandt
    

    

      
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I had no idea mget() existed. How helpful!

Thanks,

MW

        
On Sat, Oct 22, 2011 at 9:27 PM, Joshua Wiley <jwiley.psych at gmail.com> wrote:

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        

      
      
    

            

      
      
      
    

  
  


  


      

    

    
1 day later

    

      
      

        


  

        

      Wet Bell Diver
    

    

      
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Thanks so much, this is very very helpful.

I do have one remaining question here. I definitely see the value of 
making a list of the datasets, an advise I will definitely follow. 
However, for educational purposes, I would still like to know how to 
automate the following without using a list:

city1997<- dataCleaning(read.csv2("C:\\city\\year1997.txt"))
city1997.waste<- wasteCalculations(city1997, year = 1997)
if (city1997.waste[1,1] == "Time") {city1997.time<- timeCalculations(city1997)}
city1998<- dataCleaning(read.csv2("C:\\city\\year1998.txt"))
city1998.waste<- wasteCalculations(city1998, year = 1998)
if (city1998.waste[1,1] == "Time") {city1998.time<- timeCalculations(city1998)}
city1999<- dataCleaning(read.csv2("C:\\city\\year1999.txt"))
city1999.waste<- wasteCalculations(city1999, year = 1999)
if (city1999.waste[1,1] == "Time") {city1999.time<- timeCalculations(city1999)}
save(city1997, city1998, city1999, city1997.waste, city1998.waste, city1999.waste, city1997.time, city1998.time, city1999.time, file = "cities.Rdata")

so, how do I create objects with appropriate names and then have 
functions applied to them. (this is only an example of the kinds of 
manipulations I need to do, but if I can get the above to work, then I 
can figure out the rest for myself).
Thanks for your help, can you solve this final piece of the puzzle as well?

--Peter



Op 23-10-2011 3:51, R. Michael Weylandt schreef:

            

      
      
      
    

        

      
      
    

        

      
      
    

            

      
      
      
    

  
  


  


      

    

    

      
      

        


  

        

      jim holtman
    

    

      
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Write a function that encapsulates the following three lines:


city1997<- dataCleaning(read.csv2("C:\\city\\year1997.txt"))
city1997<- wasteCalculations(city1997, year = 1997)
if (city1997[1,1] == "Time") {city1997<- timeCalculations(city1997)}

and then pass in the appropriate parameters.

        
On Mon, Oct 24, 2011 at 12:09 PM, Wet Bell Diver <wetbelldiver at gmail.com> wrote:

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        

      
      
    

        

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      R. Michael Weylandt
    

    

      
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You might also need the assign() function which is sort of the opposite of get()

Michael

        
On Mon, Oct 24, 2011 at 12:15 PM, jim holtman <jholtman at gmail.com> wrote:

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        

      
      
    

            

      
      
      
    

        

      
      
    

  
  


  


      

    

    

      
      

        


  

        

      Wet Bell Diver
    

    

      
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Thanks all, for your great help!
--Peter

Op 24-10-2011 18:23, R. Michael Weylandt schreef: