I can confirm that this happens only with 3.3.0 32 bit. It does not occur with 64 bit 3.3.0 or with 32-bit 3.2.4. I am not able to confirm the exact circumstances under which it happens.
library(dplyr)
tst <- data.frame(
grp = c(rep("A", 16), rep("B", 16), rep("C", 16)),
x = rnorm(16*3),
y = rnorm(16*3)
)
tst %>%
mutate(corr = cor(x, y, na.rm = T))
Using the 64-bit 3.3.0, the second chuck of code correctly returns the helpful error:
Error: unused argument (na.rm = TRUE)
. Under 32-bit 3.3.0, R instead crashes.
@pkoki @daltonhance I delete the irrelevant stuff to make it easier to see the actual issue
But it's unlikely I'll have the time to fix given that it doesn't reproduce on my computer.
I agree with the bug.
Summarize does not work in the new 3.3 version
R.version
_
platform x86_64-w64-mingw32
arch x86_64
os mingw32
system x86_64, mingw32
status
major 3
minor 3.0
year 2016
month 05
day 03
svn rev 70573
language R
version.string R version 3.3.0 (2016-05-03)
nickname Supposedly Educational
iris %>% group_by(Species) %>% summarize(avg =mean(Sepal.Width)) %>% arrange(avg)
avg
1 3.057333R.version
_
platform x86_64-pc-linux-gnu
arch x86_64
os linux-gnu
system x86_64, linux-gnu
status
major 3
minor 1.2
year 2014
month 10
day 31
svn rev 66913
language R
version.string R version 3.1.2 (2014-10-31)
nickname Pumpkin Helmet
iris %>% group_by(Species) %>% summarize(avg =mean(Sepal.Width)) %>% arrange(avg)
Source: local data frame [3 x 2]
Species avg
(fctr) (dbl)
1 versicolor 2.770
2 virginica 2.974
3 setosa 3.428
I was initially able to reproduce this crash on 32bit R, but it went away after reinstalling both Rcpp and dplyr.
I faced this problem on
and this is my code that causes crash.
iris %>%
group_by(Sepal.Length, Sepal.Width, some_not_existing_colname) %>%
summarise(sum(Petal.Width))
this code works(with proper columns)
iris %>%
group_by(Sepal.Length, Sepal.Width) %>%
summarise(sum(Petal.Width))
hope this helps.
Same here on Win7, 32bit, R3.3.0. dplyr errors crash R entirely. Tried a reinstall of dplyr and Rcpp, but no dice yet.
This is indeed a bad interaction between 32bit versions of R 3.3.x and RStudio. Hopefully, this will be fixed on the RStudio side soon.
Had the same problem and same OS/software conditions (Windows 7, 32 bit, R 3.3.1 ...). I installed the preview version of RStudio from
https://www.rstudio.com/products/rstudio/download/preview/
as suggested, now it works again. I get proper error messages instead of the R Session and/or RStudio crashing. Just some feedback, if this was already known, feel free to delete this comment.
Thanks for the confirmation @CBSti -- indeed, this should now be resolved in the RStudio preview release.
To anyone stumbling upon this issue, please install the preview release of RStudio to resolve these crashes.
I experienced these fatal error crashes today and would like to try the preview release but I'm using RStudio Portable (v 0.99.902).
Does anyone know if (and how) I can install?
Both installers and portable versions of the preview release of RStudio are available at https://www.rstudio.com/products/rstudio/download/preview/.
Many thanks for rapid response!
On 7 Sep 2016 10:57 p.m., Kevin Ushey [email protected] wrote:Both installers and portable versions of the preview release of RStudio are available at https://www.rstudio.com/products/rstudio/download/preview/.
鈥擸ou are receiving this because you commented.Reply to this email directly, view it on GitHub, or mute the thread.
Installed the preview version today and I'm not crashing any more. Thank you!
I noticed this new version runs the whole of a dplyr piped chain too - that caught me off guard :)
Me too was facing the same issue. While using mutate() in dplyr, the rstudio crashed completely.
Installed the preview version and now its working. Thanks!!!
Seems to be resolved by the RStudio preview release. Can we close this?
Yes indeed (the fixes are also part of the current RStudio release, v1.0.44).
Instead of reinstalling RStudio, try removing all your packges. That worked for me! I used this code:
ip <- installed.packages()
pkgs.to.remove <- ip[!(ip[,"Priority"] %in% c("base", "recommended")), 1]
sapply(pkgs.to.remove, remove.packages)