r - Add selection crteria to read.table -


let's take following simplified version of dataset import using read.table:

a<-as.data.frame(c("m","m","f","f","f")) b<-as.data.frame(c(25,22,33,17,18)) df<-cbind(a,b) colnames(df)<-c("sex","age")

in reality dataset extremely large , i'm interested in small proportion of data i.e. data concerning females aged 18 or under. in example above last 2 observations.

my question is, can import these observations without importing rest of data using subset refine database. computer's capacities limited , have been using scan import data in chunks extremely time consuming.

is there better solution?

some approaches might work:

1 - use packages ff can ram issues.

2 - use other tools/languages clean data before load r.

3 - if file not big (i.e., can load without crashing), save .rdata file , read file (instead of calling read.table):

 # save each txt file once...  save.rdata = function(filepath, filebin) {      dataset = read.table(filepath)      save(dataset, paste(filebin, ".rdata", sep = ""))  }   # read .rdata  get.dataset = function(filebin) {      load(filebin)      return(dataset)  }

this faster read txt file, i'm not sure if applies case.


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