Extracting columns from text file - r

Question

I load a text file (tree.txt) to R, with the below content (copy pasted from JWEKA - J48 command).
I use the following command to load the text file:
data3 <-read.table (file.choose(), header = FALSE,sep = ",")
I would like to insert each column into a separate variables named like the following format COL1, COL2 ... COL8 (in this example since we have 8 columns). If you load it to EXCEL with delimited separation each row will be separated in one column (this is the required result).
Each COLn will contain the relevant characters of the tree in this example.
How can separate and insert the text file into these columns automatically while ignoring the header and footer content of the file?
Here is the text file content:
[[1]]
J48 pruned tree
------------------
MSTV <= 0.4
| MLTV <= 4.1: 3 -2
| MLTV > 4.1
| | ASTV <= 79
| | | b <= 1383:00:00 2 -18
| | | b > 1383
| | | | UC <= 05:00 1 -2
| | | | UC > 05:00 2 -2
| | ASTV > 79:00:00 3 -2
MSTV > 0.4
| DP <= 0
| | ALTV <= 09:00 1 (170.0/2.0)
| | ALTV > 9
| | | FM <= 7
| | | | LBE <= 142:00:00 1 (27.0/1.0)
| | | | LBE > 142
| | | | | AC <= 2
| | | | | | e <= 1058:00:00 1 -5
| | | | | | e > 1058
| | | | | | | DL <= 04:00 2 (9.0/1.0)
| | | | | | | DL > 04:00 1 -2
| | | | | AC > 02:00 1 -3
| | | FM > 07:00 2 -2
| DP > 0
| | DP <= 1
| | | UC <= 03:00 2 (4.0/1.0)
| | | UC > 3
| | | | MLTV <= 0.4: 3 -2
| | | | MLTV > 0.4: 1 -8
| | DP > 01:00 3 -8
Number of Leaves : 16
Size of the tree : 31
An example of the COL1 content will be:
MSTV
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MSTV
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COL2 content will be:
MLTV
MLTV
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>
DP
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DP
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Answer 1

Try this:
cleaned.txt <- capture.output(cat(paste0(tail(head(readLines("FILE_LOCATION"), -4), -4), collapse = '\n'), sep = '\n'))
cleaned.df <- read.fwf(file = textConnection(cleaned.txt),
header = FALSE,
widths = rep.int(4, max(nchar(cleaned.txt)/4)),
strip.white= TRUE
)
cleaned.df <- cleaned.df[,colSums(is.na(cleaned.df))<nrow(cleaned.df)]
For the cleaning process, I end up using a combination of head and tail to remove the 4 spaces on the top and the bottom. There's probably a more efficient way to do this outside of R, but this isn't so bad. Generally, I'm just making the file readable to R.
Your file looks like a fixed-width file so I use read.fwf, and use textConnection() to point the function to the cleaned output.
Finally, I'm not sure how your data is actually structured, but when I copied it from stackoverflow, it pasted with a bunch of whitespace at the end of each line. I'm using some tricks to guess at how long the file is, and removing extraneous columns over here
widths = rep.int(4, max(nchar(cleaned.txt)/4))
cleaned.df <- cleaned.df[,colSums(is.na(cleaned.df))<nrow(cleaned.df)]
Next, I'm creating the data in the way you would like it structured.
for (i in colnames(cleaned.df)) {
assign(i, subset(cleaned.df, select=i))
assign(i, capture.output(cat(paste0(unlist(get(i)[get(i)!=""])),sep = ' ', fill = FALSE)))
}
rm(i)
rm(cleaned.df)
rm(cleaned.txt)
What this does is it creates a loop for each column header in your data frame.
From there it uses assign() to put all the data in each column into its' own data frame. In your case, they are named V1 through V15.
Next, it uses a combination of cat() and paste() with unlist() an capture.output() to concatenate your list into a single character vectors, for each of the data frames, so they are now character vectors, instead of data frames.
Keep in mind that because you wanted a space at each new character, I'm using a space as a separator. But because this is a fixed-width file, some columns are completely blank, which I'm removing using
get(i)[get(i)!=""]
(Your question said you wanted COL2 to be: MLTV MLTV | | | | | | > DP | | | | | | | | | | | | DP | | | | | |).
If we just use get(i), there will be a leading whitespace in the output.