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The anti_join from the package dplyr might also be handy. install.package("dplyr") library(dplyr) anti_join (x1, x2) You can get help on the different functions by ?function.name(), so ?anti_join() will bring you help - and examples - on the anti_join function. It might be worth testing your approach on a small subset of the data. That makes it easier for you to follow what happens

If your two objects have class "data.frame" (look at class(objectName)) and they both have the same number of columns and the same order of columns and the column types match closely enough (use all.equal(x1, x2) for that), then you can try which( rowSums( x1 != x2 ) > 0) E.g., > x1 <- data.frame(X=1:5, Y=rep(c("A","B"),c(3,2))) > x2 <-

Cool, looks like that'd do it, almost as if converting an entire record to a character string and comparing strings. -- M. B. Hardy, statistician work: Applied Research Associates, S. E. Div. 8537 Six Forks Rd., # 6000 / Raleigh, NC 27615-2963 (919) 582-3329, fax: 582-3301 home: 1020 W. South St. / Raleigh, NC 27603-2162 (919) 834-1245

Thanks, I think I've found the most succinct expression of differences in two data.frames... length(which( rowSums( x1 != x2 ) > 0)) gives a count of the # of records in two data.frames that do not match. // ________________________________________ From: Henrik Bengtsson [henrik.bengtsson at gmail.com] Sent: Sunday, January 28, 2018 11:12 AM To: Ulrik Stervbo Cc: Marsh Hardy ARA/RISK;

The diffobj package (https://cran.r-project.org/package=diffobj) is really helpful here. It provides "diff" functions diffPrint(), diffStr(), and diffChr() to compare two object 'x' and 'y' and provide neat colorized summary output. Example: > iris2 <- iris > iris2[122:125,4] <- iris2[122:125,4] + 0.1 > diffobj::diffPrint(iris2, iris) < iris2 >

Also, it will be easier to provide helpful information if you'd describe what in your data you want to compare and what you hope to get out of the comparison. Best wishes, Ulrik Eric Berger <ericjberger at gmail.com> schrieb am Sa., 27. Jan. 2018, 08:18: > Hi Marsh, > An RDS is not a data structure such as a data.frame. It can be anything. > For example if I want to save my

Hi Guys, I apologize for my rank & utter newness at R. I used summary() and found about 95 variables, both character and numeric, all with "Length:368842" I assume is the # of records. I'd like to know the record number (row #?) of any record where the data doesn't match in the 2 files of what should be the same output. Thanks in advance, M. //

Hi Marsh, An RDS is not a data structure such as a data.frame. It can be anything. For example if I want to save my objects a, b, c I could do: > saveRDS( list(a,b,c,), file="tmp.RDS") Then read them back later with > myList <- readRDS( "tmp.RDS" ) Do you have additional information about your "RDSs" ? Eric On Sat, Jan 27, 2018 at 6:54 AM, Marsh Hardy

Each RDS is 40 MBs. What's a slick code to compare them row by row, IDing row numbers with mismatches? Thanks in advance. //