similar to: "note: symbols.rds is not available"

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

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.

Hi everybody, I have trouble installing my own package under R 2.1.0 (it is fine under R 2.0.1). My OS is Windows NT. I installed my package 'mag' by using menu "Packages/Install package from local zip files....". It's fine (html package description was updated). But when I typed in library(mag) it gave me error: Error in library(mag) : there is no package called

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

Hi. I'm on Windows 7 64-bit with latest R devel with and Rtools (2.16.0.1926). When I try to enable spell checking for 'R CMD check' by setting environment variable '_R_CHECK_CRAN_INCOMING_USE_ASPELL_' to 'true', I get: * checking CRAN incoming feasibility ...Warning in aspell(files, filter = "dcf", control = control, encoding = encoding, : The

Hi, I am writing a test that consults the serialization version of an `.rds` file. An attractive way to get this is: tools:::get_serialization_version() # reports just version which calls .Internal(serializeInfoFromConn() # reports much more but neither is truly exported for public use. Is there an official, exported way to get the serialization version? It is possible to get this

Hi all, I've noticed some peculiarities in the tools:::funAPI output that complicate its programmatic use a bit. - Is it for remapped symbol names (with Rf_ or the Fortran underscore), or for unmapped names (without Rf_ or the underscore)? I see that the functions marked in WRE are almost all (except Rf_installChar and Rf_installTrChar) unmapped. This makes a lot of sense because some

Hi, I have been using filehash for a while. It has performed very well. However, recently I found filehash gives an error when I need to do something like db[c("a", "b")] when the db is in RDS format. Does any one know a way to get around that? The code below reproduces the error thanks Jeff filehashOption(defaultType = "DB1") dbCreate("mydb3", type =

Hi, I'm trying to understand why/how absolute file paths are stored in .rdb[1] and .rds[2] files during package installation. As a consequence building the same r package in different directories does not produce identical .rdb and .rds files. The background is that I work on reproducible builds[3] of R packages. I think this is important from an engineering point of view but also from a

Ok, so this is not a users-list, but i really don't know where to ask. Maybe a future openssh-unix-users at mindrot.org will take this kind of problems... :-) So, i'm trying to forward a POP3 connection over a SSH tunnel, using openssh-1.2.3 both on server and on client. My host is atlanta.rds.ro and the mailserver is mail.rds.ro. I did like this: ssh -L 110:mail.rds.ro:110 mail.rds.ro

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

I ran into this behaviour when accidentally running a line of code that I shouldn't have. When saving over an rds with an object that's not found, I would have expected saveRDS to not touch the file. saveRDS(iris, "test.rds") file.size("test.rds") #> [1] 1080 saveRDS(no_object_here, "test.rds") #> Error in saveRDS(no_object_here, "test.rds"):

Le 07/07/2017 ? 16:52, Duncan Murdoch a ?crit : > On 07/07/2017 9:54 AM, Serguei Sokol wrote: >> Le 07/07/2017 ? 01:09, Duncan Murdoch a ?crit : >>> On 06/07/2017 6:44 PM, Sokol Serguei wrote: >>>> Duncan Murdoch has written at Thu, 6 Jul 2017 13:58:10 -0400 >>>>> On 06/07/2017 5:21 AM, Serguei Sokol wrote: >>>>>> I propose the

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

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

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

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)

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

Dear Aishwarya Priyadarshini, Welcome to R-help! Most people here aren't affiliated with R Foundation. ? Wed, 26 Jun 2024 17:03:37 +0000 "Priya, Aishwarya via R-help" <r-help at r-project.org> ?????: > I am reaching out to seek your guidance on addressing the security > vulnerability CVE-2024-27322. > To address this issue effectively, it appears that we need to

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,