How to read a text file in R when data is not in the table

Question

I have a very long phonebook in the form of a text file, and I tried to read it in R, but it does not work. The text has a structure, but it is certainly not a table. Its structure is as follows

• Each entry consists of several lines, so readLines does not quite fit
• Each row of each record is a separate field.
• Some entries have an extra field after the second field
• Each new entry is marked with an empty line. readLines or scan would work if it could indicate that the records were split "\ n \ n" and that the fields (or columns) were split "\ n"

Here is an example:

 TheInstitute 5467 telephone line 4125526987 x 4567 datetime 2011110516 12:56 blay blay blah who knows what, but anyway it may have a comma TheInstitute 5467 telephone line 4125526987 x 4567 datetime 2011110516 12:58 blay blay blah who knows what TheInstitute 5467 telephone line 412552999 x 4999 bump phone line 4125527777 datetime 2011110516 12:59 blay blay blah who knows what TheInstitute 5467 telephone line 4125526987 x 4567 bump phone line 4125527777 datetime 2011110516 13:51 blay blay blah who knows what, but anyway it may have a comma TheInstitute 5467 telephone line 4125526987 x 4567 datetime 2011110516 14:56 blay blay blah who knows what 

How can I do this in R? I tried tricks with validation, insertion, strsplit, but I was spinning in a circle. I may have to list it, because it can handle an unequal number of elements. I would like all the records to have the same number of fields and for those records that don't have one field (here called bump phone), I would like them to just have the value NA as the value in this field. I would appreciate help even for a start. From there I can play and play.

Answer 1

With multi.line = TRUE in the scan function, the record should end with two end lines. I did this with textConnection around your file, but you would use a valid file name:

 inp <- scan(textConnection(txt), multi.line=TRUE, what=list(place="character", tline1="character", cline1="character", cline2 ="character", cline3="character"), sep="\n") Read 5 records > str(as.data.frame(inp)) 'data.frame': 5 obs. of 5 variables: $ place : Factor w/ 1 level "TheInstitute 5467": 1 1 1 1 1 $ tline1: Factor w/ 2 levels " telephone line 4125526987 x 4567",..: 1 1 2 1 1 $ cline1: Factor w/ 4 levels " bump phone line 4125527777",..: 2 3 1 1 4 $ cline2: Factor w/ 4 levels " blay blay blah who knows what",..: 2 1 3 4 1 $ cline3: Factor w/ 3 levels ""," blay blay blah who knows what",..: 1 1 2 3 1 > as.data.frame(inp) place tline1 1 TheInstitute 5467 telephone line 4125526987 x 4567 2 TheInstitute 5467 telephone line 4125526987 x 4567 3 TheInstitute 5467 telephone line 412552999 x 4999 4 TheInstitute 5467 telephone line 4125526987 x 4567 5 TheInstitute 5467 telephone line 4125526987 x 4567 cline1 1 datetime 2011110516 12:56 2 datetime 2011110516 12:58 3 bump phone line 4125527777 4 bump phone line 4125527777 5 datetime 2011110516 14:56 cline2 1 blay blay blah who knows what, but anyway it may have a comma 2 blay blay blah who knows what 3 datetime 2011110516 12:59 4 datetime 2011110516 13:51 5 blay blay blah who knows what cline3 1 2 3 blay blay blah who knows what 4 blay blay blah who knows what, but anyway it may have a comma 5