I have a text data file that I likely will read with readLines
. The initial portion of each string contains a lot of gibberish followed by the data I need. Th
This will get you most of the way there, and it will have no problems with numbers that include commas:
# First, use a regex to eliminate the bad pattern. This regex
# eliminates any three-character combination of periods, commas,
# and big dots (•), so long as the combination is followed by
# 0-2 spaces and then a digit.
aa.sub <- as.matrix(
apply(aa, 1, function (x)
gsub('[•.,]{3}(\\s{0,2}\\d)', '\\1', x, perl = TRUE)))
# Second: it looks as though you want your data split into columns.
# So this regex splits on spaces that are (a) preceded by a letter,
# digit, or space, and (b) followed by a digit. The result is a
# list, each element of which is a list containing the parts of
# one of the strings in aa.
aa.list <- apply(aa.sub, 1, function (x)
strsplit(x, '(?<=[\\w\\d\\s])\\s(?=\\d)', perl = TRUE))
# Remove the second element in aa. There is no space before the
# first data column in this string. As a result, strsplit() split
# it into three columns, not 4. That in turn throws off the code
# below.
aa.list <- aa.list[-2]
# Make the data frame.
aa.list <- lapply(aa.list, unlist) # convert list of lists to list of vectors
aa.df <- data.frame(aa.list)
aa.df <- data.frame(t(aa.df), row.names = NULL, stringsAsFactors = FALSE)
The only thing remaining is to modify the regex for strsplit()
so that it can handle the second string in aa
. Or perhaps it's better just to handle cases like that manually.