R - Loading in data for specific dates-CodePudding

I need to load a lot of files into R, all of these files have a date hidden in their name as follows: SD07_TWK_20190822_003004

I would like to select the files that are loaded based on these dates.

I load the files into R like this:

filenames = list.files(path=path, pattern=".txt") 
colnamesfull = c("time","v","a","t1","t2","t3","t4","t5","t6","t7","t8")

for(i in filenames){
  filepath = file.path(path, paste(i, sep=""))
  assign(i, read.table(filepath,
                       skip= 20, 
                       col.names= colnamesfull, 
                       sep=",")
                       )}

To filter on dates, I assume I need to add a date range in the 'pattern' within the list.files function. However, I can't get that to work.

Say I have the following dates:

date_start = "20190822"
date_end = "20190823"

How would I add a filter for these dates into the code above?

Example of code and files:

#path = "C:/path"
filenames = list.files(path=path, pattern=".txt")
names = substr(filenames,10,17) 
date_start = "20190822"
date_end = "20190822"

for(i in filenames){
  filepath = file.path(path, paste(i, sep=""))
  if( (date_start <= substr(filepath, 10, 17))  &  
      (substr(filepath, 10, 17) <= date_end  )){
    assign(i, read.table(filepath,
                         skip= 20, 
                         col.names= colnamesfull,
                         sep=","))}}

Some files:

> dput(file1)
structure(list(time = c(2, 3.9, 5.8, 7.8, 9.7, 11.7, 13.6, 15.5, 
17.5, 19.4), v = c(14.82, 14.804, 14.82, 14.82, 14.804, 14.82, 
14.812, 14.804, 14.8, 14.808), a = c(1.5, 1.476, 1.5, 1.491, 
1.452, 1.476, 1.478, 1.44, 1.454, 1.438), t1 = c(14.61, 14.61, 
14.61, 14.61, 14.61, 14.61, 14.61, 14.62, 14.62, 14.63), t2 = c(14.63, 
14.62, 14.62, 14.62, 14.62, 14.62, 14.62, 14.63, 14.63, 14.64
), t3 = c(14.63, 14.63, 14.63, 14.63, 14.63, 14.63, 14.63, 14.63, 
14.64, 14.65), t4 = c(14.65, 14.65, 14.65, 14.65, 14.64, 14.64, 
14.65, 14.65, 14.66, 14.67), t5 = c(14.65, 14.65, 14.65, 14.65, 
14.65, 14.65, 14.66, 14.66, 14.67, 14.69), t6 = c(14.63, 14.63, 
14.63, 14.63, 14.63, 14.63, 14.63, 14.64, 14.65, 14.66), t7 = c(14.64, 
14.64, 14.64, 14.64, 14.64, 14.64, 14.64, 14.64, 14.65, 14.66
), t8 = c(14.6, 14.6, 14.6, 14.6, 14.6, 14.6, 14.61, 14.61, 14.62, 
14.63)), row.names = c(NA, 10L), class = "data.frame")
> dput(file2)
structure(list(time = c(2, 3.9, 5.9, 7.8, 9.7, 11.7, 13.6, 15.6, 
17.5, 19.5), v = c(14.808, 14.808, 14.816, 14.816, 14.808, 14.804, 
14.816, 14.8, 14.808, 14.808), a = c(1.478, 1.472, 1.491, 1.49, 
1.47, 1.484, 1.452, 1.473, 1.465, 1.482), t1 = c(14.63, 14.63, 
14.63, 14.63, 14.62, 14.62, 14.63, 14.63, 14.63, 14.64), t2 = c(14.64, 
14.64, 14.64, 14.64, 14.64, 14.64, 14.64, 14.64, 14.65, 14.65
), t3 = c(14.65, 14.65, 14.65, 14.65, 14.65, 14.64, 14.65, 14.65, 
14.65, 14.66), t4 = c(14.66, 14.66, 14.66, 14.66, 14.66, 14.66, 
14.66, 14.67, 14.67, 14.68), t5 = c(14.67, 14.67, 14.67, 14.67, 
14.67, 14.67, 14.67, 14.68, 14.69, 14.7), t6 = c(14.65, 14.65, 
14.65, 14.65, 14.65, 14.65, 14.65, 14.65, 14.66, 14.67), t7 = c(14.65, 
14.65, 14.65, 14.65, 14.65, 14.65, 14.65, 14.66, 14.66, 14.67
), t8 = c(14.62, 14.62, 14.62, 14.62, 14.62, 14.62, 14.62, 14.62, 
14.63, 14.64)), row.names = c(NA, 10L), class = "data.frame")

CodePudding user response：

Starting with a filename following the pattern of "SD07_TWK_20190822_003004" you can extract the date as characters 10 through 17:

> substr("SD07_TWK_20190822_003004", 10, 17)
[1] "20190822"

Now this is a character string. But as someone clever ordered the year, month and date in a sensible order, you can compare these strings as if they were dates:

example <- substr("SD07_TWK_20190822_003004", 10, 17)
date_start = "20190822"
date_end = "20190823"

example >= date_start
example < date_end

Now if you want to see, whether a date is in between date_start and date_end this becomes something like

> date_start <= example & example <= date_end
[1] TRUE

Let's try it with a date a month early and a year late to see if we get the desired FALSE:

> example = "20190722"
> date_start <= example & example <= date_end
[1] FALSE
> example = "20200822"
> date_start <= example & example <= date_end
[1] FALSE

Great, now all you have to do is condition the assign in your loop with an if statement, something along the lines of

if( (start_date <= substr(filepath, 10, 17))  &  
    (substr(filepath, 10, 17) <= end_date  ) ){
        assign(....)
}

I cannot close without giving the advice to reconsider, whether assign is a good choice here. You should probably rather store those data.frames in a list, but that is not the topic of this question.