Extract from a text file
Thank you so much Jeff. It worked for this example. When I read it from a file (c:\data\test.txt) it did not work KLEM="c:\data" KR=paste(KLEM,"\test.txt",sep="") indta <- readLines(KR, skip=46) # not interested in the first 46 lines) pattern <- "^.*group (\\d+)[^:]*: *([-+0-9.eE]*).*$" firstlines <- grep( pattern, indta ) # Replace the matched portion (entire string) with the first capture # string v1 <- as.numeric( sub( pattern, "\\1", indta[ firstlines ] ) ) # Replace the matched portion (entire string) with the second capture # string v2 <- as.numeric( sub( pattern, "\\2", indta[ firstlines ] ) ) # Convert the lines just after the first lines to numeric v3 <- as.numeric( indta[ firstlines + 1 ] ) # put it all into a data frame result <- data.frame( Group = v1, Mean = v2, SE = v3 ) result [1] Group Mean SE <0 rows> (or 0-length row.names) Thank you in advance On Tue, May 31, 2016 at 1:12 AM, Jeff Newmiller
<jdnewmil at dcn.davis.ca.us> wrote:
Please learn to post in plain text (the setting is in your email client... somewhere), as HTML is "What We See Is Not What You Saw" on this mailing list. In conjunction with that, try reading some of the fine material mentioned in the Posting Guide about making reproducible examples like this one: # You could read in a file # indta <- readLines( "out.txt" ) # but there is no "current directory" in an email # so here I have used the dput() function to make source code # that creates a self-contained R object indta <- c( "Mean of weight group 1, SE of mean : 72.289037489555276", " 11.512956539215610", "Average weight of group 2, SE of Mean : 83.940053900595013", " 10.198495690144522", "group 3 mean , SE of Mean : 78.310441258245469", " 13.015876679555", "Mean of weight of group 4, SE of Mean : 76.967516495101669", " 12.1254882985", "") # Regular expression patterns are discussed all over the internet # in many places OTHER than R # You can start with ?regex, but there are many fine tutorials also pattern <- "^.*group (\\d+)[^:]*: *([-+0-9.eE]*).*$" # For this task the regex has to match the whole "first line" of each set # ^ =match starting at the beginning of the string # .* =any character, zero or more times # "group " =match these characters # ( =first capture string starts here # \\d = any digit (first backslash for R, second backslash for regex) # + =one or more of the preceding (any digit) # ) =end of first capture string # [^:] =any non-colon character # * =zero or more of the preceding (non-colon character) # : =match a colon exactly # " *" =match zero or more spaces # ( =second capture string starts here # [ =start of a set of equally acceptable characters # -+ =either of these characters are acceptable # 0-9 =any digit would be acceptable # . =a period is acceptable (this is inside the []) # eE =in case you get exponential notation input # ] =end of the set of acceptable characters (number) # * =number of acceptable characters can be zero or more # ) =second capture string stops here # .* =zero or more of any character (just in case) # $ =at end of pattern, requires that the match reach the end # of the string # identify indexes of strings that match the pattern firstlines <- grep( pattern, indta ) # Replace the matched portion (entire string) with the first capture # string v1 <- as.numeric( sub( pattern, "\\1", indta[ firstlines ] ) ) # Replace the matched portion (entire string) with the second capture # string v2 <- as.numeric( sub( pattern, "\\2", indta[ firstlines ] ) ) # Convert the lines just after the first lines to numeric v3 <- as.numeric( indta[ firstlines + 1 ] ) # put it all into a data frame result <- data.frame( Group = v1, Mean = v2, SE = v3 ) Figuring out how to deliver your result (output) is a separate question that depends where you want it to go. On Mon, 30 May 2016, Val wrote:
Hi all,
I have a messy text file and from this text file I want extract some
information
here is the text file (out.txt). One record has tow lines. The mean comes
in the first line and the SE of the mean is on the second line. Here is
the
sample of the data.
Mean of weight group 1, SE of mean : 72.289037489555276
11.512956539215610
Average weight of group 2, SE of Mean : 83.940053900595013
10.198495690144522
group 3 mean , SE of Mean : 78.310441258245469
13.015876679555
Mean of weight of group 4, SE of Mean : 76.967516495101669
12.1254882985
I want produce the following table. How do i read it first and then
produce a
Gr1 72.289037489555276 11.512956539215610
Gr2 83.940053900595013 10.198495690144522
Gr3 78.310441258245469 13.015876679555
Gr4 76.967516495101669 12.1254882985
Thank you in advance
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