Your data show a couple of difficulties which should be handled in a sequence, which means you should not try to read the entire file with one command:
Read plain lines and find start and stop row
Depending on the specification of the files you read in my suggestion is to first find the the first row you actually want to read in by any indicator. So this can be a lone number which is always the same or as in my example two lines after the line "TEAM STATS". Finding the last line is then simple again by just looking for the first line containing only whitespaces after the start line:
lines <- readLines( Datei )
start <- which(lines == "TEAM STATS") + 2
end <- start + min( grep( "^\\s+$", lines[ start:length(lines) ] ) ) -2
lines <- lines[start:end]
Read the data to data.frame
In your case you meet a couple of complications:
- Your header line starts with an
#
which is on default recognized as a comment character, ignoring the line. But even if you switch this behavior off (comment.char = ""
) it's not a valid column name.
- If we tell read.table to split the columns along whitespaces you end up with one more column in the data, than in the header since the Player column contains white spaces in the cells. So the best is at the moment to just ignore the header line and let
read.table
do this with it's default behavior (comment.char = "#"
). Also we let the PLAYER column be split into two and will fix this later.
- You won't be able to use the first column as
row.names
since they are not unique.
- The rows have unequal length, since the POS column is not filled everywhere.
:
tab <- read.table( text = lines[ start:end ], fill = TRUE, stringsAsFactors=FALSE )
# fix the PLAYER column
tab$V2 <- paste( tab$V2, tab$V3 )
tab <- tab[-3]
Fix the header
Just split the start line at multiple whitespaces and reset the first entry (#
) by a valid column name:
colns <- strsplit( lines[start], "\\s+" )[[1]]
colns[1] <- "code"
colnames(tab) <- colns
Fix cases were "POS" was empty
This is done by finding the rows which last cell contains NA
s and shift them by one cell to the right:
colsToFix <- which( is.na(tab[, "SHO%"]) )
tab[ colsToFix, 4:ncol(tab) ] <- tab[ colsToFix, 3:(ncol(tab)-1) ]
tab[ colsToFix, 3 ] <- NA
> str(tab)
'data.frame': 25 obs. of 20 variables:
$ code : chr "93" "91" "61" "88" ...
$ PLAYER: chr "Eichelkraut, Flori" "Müller, Lars" "Alt, Sebastian" "Gross, Arthur" ...
$ POS : chr "F" "F" "D" "F" ...
$ GP : chr "8" "6" "7" "8" ...
$ G : int 10 1 4 3 4 2 0 2 1 0 ...
$ A : int 5 11 5 5 3 4 6 3 3 4 ...
$ PTS : int 15 12 9 8 7 6 6 5 4 4 ...
$ PIM : int 12 10 12 6 2 36 37 29 6 0 ...
$ PPG : int 3 0 1 1 1 1 0 0 1 0 ...
$ PPA : int 1 5 2 2 1 2 4 2 1 1 ...
$ SHG : int 0 1 0 1 1 0 0 0 0 0 ...
$ SHA : int 0 0 1 0 1 0 0 1 0 0 ...
$ GWG : int 2 0 1 0 0 0 0 0 0 0 ...
$ FG : int 1 0 1 1 1 0 0 0 0 0 ...
$ OTG : int 0 0 0 0 0 0 0 0 0 0 ...
$ UAG : int 1 0 1 0 0 0 0 0 0 0 ...
$ ENG : int 0 0 0 0 0 0 0 0 0 0 ...
$ SHOG : int 0 0 0 0 0 0 0 0 0 0 ...
$ SHOA : num 0 0 0 0 0 0 0 0 0 0 ...
$ SHO% : num 0 0 0 0 0 0 0 0 0 0 ...