similar to: Newbie wants to compare 2 huge RDSs row by row.

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. //

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 <-

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

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

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 >

Hi all, Is there any chance that readRDS and saveRDS might one day become read.rds and write.rds? That would make them more consistent with the other reading and writing functions. Hadley -- Assistant Professor / Dobelman Family Junior Chair Department of Statistics / Rice University http://had.co.nz/

I hardly know anything about the format used in (non-compressed) serialization/RDS, but hoping someone with more knowledge could give me some feedback; Consider two R processes running in parallel on the same unknown file system. Both of them write and read to the same RDS file foo.rds (without compression) at random times using saveRDS(object, file="foo.rds", compress=FALSE) and

The documentation for recordPlot says the following: > As of R 3.3.0, it is possible (again) to replay a plot from another R session using, for example, saveRDS and readRDS. However, I haven't been able to save and restore a plot displaylist and have it work within the same R session, using R 3.4.3 or 3.3.3. Here's an example: # Save displaylist for a simple plot

Hi there, I faced a weird problem doing a seemingly simple task in R. Specifically, when trying for reading an RDS file from the working directory, the following error is appeared. Code: records <- readRDS("tweets.rds") Error: Error in readRDS("tweets.rds") : error reading from connection In addition: Warning message: In readRDS("tweets.rds") : invalid or

Dear all I was thinking about efficient reading data into R and tried several ways to test if load(file.Rdata) or readRDS(file.rds) is faster. The files file.Rdata and file.rds contain the same data, the first created with save(d, ' file.Rdata', compress=F) and the second with saveRDS(d, ' file.rds', compress=F). First I used the function microbenchmark() and was a astonished

I use recordPlot() to save plots to disk that I render later to a variety of formats. This works fine for base R plots and ggplot2 plots, and also used to work for lattice plots. However somewhere in version 2.14 things stopped working for lattice plots. Here is an example: library(lattice); histogram(rnorm(100)); x <- recordPlot(); saveRDS(x, "myplot.rds"); y <-

Hello, I looked in the R-help but could not find an archive addressing the following. I would like to convert a character to numeric after reading a file with RDS extension. After using as.numeric, I checked if it is numeric. It was not converted. Please help. Here is my code >Report <- readRDS(file="RDS/Report.RDS") > Report[1:2,] dive_id date

>>>>> Paul Murrell <paul at stat.auckland.ac.nz> >>>>> on Tue, 3 Apr 2018 09:41:56 +1200 writes: > Hi What you are doing "wrong" is loading a recordedplot > into the same session that it was created in. The > saveRDS()/readRDS() works if you save in one R session and > then read in a different R session. The

Wouldn't the obvious problem be that your data file is corrupted or was never created using saveRDS in the first place? Can you show us a complete example of creating and attempting to read what was just created? On April 22, 2018 10:20:05 AM CDT, mohammad moradi <mri.moradi at gmail.com> wrote: >Hi there, > >I faced a weird problem doing a seemingly simple task in R.

I've tried to re-experiment the tutorial presented at http://www.rdatamining.com/docs/twitter-analysis-with-r and specifically aimed to use rds files (tweet records) at http://www.rdatamining.com/data/. On Sun, Apr 22, 2018 at 9:16 PM, Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote: > Wouldn't the obvious problem be that your data file is corrupted or was > never created

The large value for maximum time may be due to garbage collection, which happens periodically. E.g., try the following, where the unlist(as.list()) creates a lot of garbage. I get a very large time every 102 or 51 iterations and a moderately large time more often mb <- microbenchmark::microbenchmark({ x <- as.list(sin(1:5e5)); x <- unlist(x) / cos(1:5e5) ; sum(x) }, times=1000)

Note that if you force a garbage collection each iteration the times are more stable. However, on the average it is faster to let the garbage collector decide when to leap into action. mb_gc <- microbenchmark::microbenchmark(gc(), { x <- as.list(sin(1:5e5)); x <- unlist(x) / cos(1:5e5) ; sum(x) }, times=1000, control=list(order="inorder")) with(mb_gc,