Using Regex to clean a csv file in R - regex

Question

This is my first post so I hope it is clear enough.
I am having a problem regarding cleaning my CSV files before I can read them into R and have spent the entire day trying to find a solution.
My data is supposed to be in the form of two columns. The first column is a timestamp consisting of 10 digits and the second an ID consisting of 11 or 12 Letters and numbers (the first 6 are always numbers).
For example:
logger10 |
0821164100 | 010300033ADD
0821164523 | 010300033ADD
0821164531 | 010700EDDA0F0831102744
010700EDDA0F|
would become:
0821164100 | 010300033ADD
0821164523 | 010300033ADD
0821164531 | 010700EDDA0F
0831102744 | 010700EDDA0F
(please excuse the lines in the middle, that was my attempt at separating the columns...).
The csv file seems to occasionally be missing a comma which means that sometimes one row will end up like this:
0923120531,010300033ADD0925075301,010700EDD00A
My hardware also adds the word logger10 (or whichever number logger this is) whenever it restarts which gives a similar problem e.g. logger10logger100831102744.
I think I have managed to solve the logger text problem (see code) but I am sure this could be improved. Also, I really don't want to delete any of the data.
My real trouble is making sure there is a line break in the right place after the ID and, if not, I would like to add one. I thought I could use regex for this but I'm having difficulty understanding it.
Any help would be greatly appreciated!
Here is my attempt:
temp <- list.files(pattern="*.CSV") #list of each csv/logger file
for(i in temp){
#clean each csv
tmp<-readLines(i) #check each line in file
tmp<-gsub("logger([0-9]{2})","",tmp) #remove logger text
pattern <- ("[0-9]{10}\\,[0-9]{6}[A-Z,0-9]{5,6}") #regex pattern ??
if (tmp!= pattern){
#I have no idea where to start here...
}
}
here is some raw data:
logger01
0729131218,020700EE1961
0729131226,020700EE1961
0831103159,0203000316DB
0831103207,0203000316DB0831103253,010700EDE28C
0831103301,010700EDE28C
0831103522,010300029815
0831103636,010300029815
0831103657,020300029815

Answer 1

If you want to do this in a single pass:
(?:logger\d\d )?([\dA-F]{10}),?([\dA-F]{12}) ?
can be replaced with
\1\t\2\n
What this does is look for any of those rogue logger01 entries (including the space after it) optionally: That trailing ? after the group means that it can match 0 or 1 time: if it does match, it will. If it's not there, the match just keeps going anyway.
Following that, you look for (and capture) exactly 10 hex values (either digits or A-F). The ,? means that if a comma exists, it will match, but it can match 0 or 1 time as well (making it optional).
Following that, look for (and capture) exactly 12 hex values. Finally, to get rid of any strange trailing spaces, the ? (a space character followed by ?) will optionally match the trailing space.
Your replacement will replace the first captured group (the 10 hex digits), add in a tab, replace the second captured group (the 12 hex digits), and then a newline.
You can see this in use on regex101 to see the results. You can use code generator on the left side of that page to get some preformatted PHP/Javascript/Python that you can just drop into a script.
If you're doing this from the command line, perl could be used:
perl -pe 's/(?:logger\d\d )?([\dA-F]{10}),?([\dA-F]{12}) ?/\1\t\2\n/g'
If another language, you may need to adapt it slightly to fit your needs.
EDIT
Re-reading the OP and comments, a slightly more rigid regex could be
(?:logger\d\d\ )?([\dA-F]{10}),?(\d{6}[\dA-F]{5,6})\ ?
I updated the regex101 link with the changes.
This still looks for the first 10 hex values, but now looks for exactly 6 digits, followed by 5-6 hex values, so the total number of characters matched is 11 or 12.
The replacement would be the same.

Answer 2

Paste your regex here https://regex101.com/ to see whether it catches all cases. The 5 or 6 letters or digits could pose an issue as it may catch the first digit of the timestamp when the logger misses out a comma. Append an '\n' to the end of the tmp string should work provided the regex catches all cases.