Reputation: 21
I have seen this question asked by a number of people with different issues, but I have not found a response that fixes my problem.
I am having a problem with the following error when executing any of the grouped_* commands in ggstatsplot.
Error in unique.default(x, nmax = nmax) : unique() applies only to vectors
I have tried reinstalling R, reinstalling RStudio, and reinstalling all packages. I have also brought this up to the developer of ggstatsplot, but he said he cannot reproduce my error. I expect ggstatsplot to produce grouped plots based on the grouping variable. Instead, I receive the error above.
Here is a reprex with my sessionInfo and the traceback of the problem I am encountering.
If anyone has any idea what is going on here I would greatly appreciate it. Thank you.
Reprex with sessionInfo:
library(ggstatsplot)
#> You can cite this package as:
#> Patil, I. (2021). Visualizations with statistical details: The 'ggstatsplot' approach.
#> Journal of Open Source Software, 6(61), 3167, doi:10.21105/joss.03167
# Error in ggstatsplot grouping function
grouped_ggscatterstats(data = movies_long,
x = budget,
y = rating,
grouping.var = genre)
#> Error in unique.default(x, nmax = nmax): unique() applies only to vectors
Created on 2023-02-07 with reprex v2.0.2
Session infosessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.0.3 (2020-10-10)
#> os Ubuntu 20.04.5 LTS
#> system x86_64, linux-gnu
#> ui X11
#> language en_CA:en
#> collate en_CA.UTF-8
#> ctype en_CA.UTF-8
#> tz America/Edmonton
#> date 2023-02-07
#> pandoc 2.19.2 @ /usr/lib/rstudio/resources/app/bin/quarto/bin/tools/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> package * version date (UTC) lib source
#> BayesFactor 0.9.12-4.4 2022-07-05 [1] CRAN (R 4.0.3)
#> bayestestR 0.13.0 2022-09-18 [1] CRAN (R 4.0.3)
#> cli 3.6.0 2023-01-09 [1] CRAN (R 4.0.3)
#> coda 0.19-4 2020-09-30 [1] CRAN (R 4.0.3)
#> codetools 0.2-18 2020-11-04 [4] CRAN (R 4.0.3)
#> colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.0.3)
#> correlation 0.8.3 2022-10-09 [1] CRAN (R 4.0.3)
#> curl 5.0.0 2023-01-12 [1] CRAN (R 4.0.3)
#> datawizard 0.6.5 2022-12-14 [1] CRAN (R 4.0.3)
#> digest 0.6.31 2022-12-11 [1] CRAN (R 4.0.3)
#> dplyr 1.1.0 2023-01-29 [1] CRAN (R 4.0.3)
#> effectsize 0.8.3 2023-01-28 [1] CRAN (R 4.0.3)
#> emmeans 1.7.3 2022-03-27 [1] CRAN (R 4.0.3)
#> estimability 1.4.1 2022-08-05 [1] CRAN (R 4.0.3)
#> evaluate 0.20 2023-01-17 [1] CRAN (R 4.0.3)
#> fansi 1.0.4 2023-01-22 [1] CRAN (R 4.0.3)
#> farver 2.1.1 2022-07-06 [1] CRAN (R 4.0.3)
#> fastmap 1.1.0 2021-01-25 [1] CRAN (R 4.0.3)
#> fs 1.6.1 2023-02-06 [1] CRAN (R 4.0.3)
#> generics 0.1.3 2022-07-05 [1] CRAN (R 4.0.3)
#> ggplot2 3.4.0 2022-11-04 [1] CRAN (R 4.0.3)
#> ggside 0.2.2 2022-12-04 [1] CRAN (R 4.0.3)
#> ggstatsplot * 0.10.0 2022-11-27 [1] CRAN (R 4.0.3)
#> glue 1.6.2 2022-02-24 [1] CRAN (R 4.0.3)
#> gtable 0.3.1 2022-09-01 [1] CRAN (R 4.0.3)
#> highr 0.10 2022-12-22 [1] CRAN (R 4.0.3)
#> htmltools 0.5.4 2022-12-07 [1] CRAN (R 4.0.3)
#> httr 1.4.4 2022-08-17 [1] CRAN (R 4.0.3)
#> insight 0.19.0 2023-01-30 [1] CRAN (R 4.0.3)
#> knitr 1.42 2023-01-25 [1] CRAN (R 4.0.3)
#> labeling 0.4.2 2020-10-20 [1] CRAN (R 4.0.3)
#> lattice 0.20-45 2021-09-22 [4] CRAN (R 4.1.1)
#> lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.0.3)
#> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.0.3)
#> MASS 7.3-58.1 2022-08-03 [4] CRAN (R 4.2.1)
#> Matrix 1.5-3 2022-11-11 [1] CRAN (R 4.0.3)
#> MatrixModels 0.5-1 2022-09-11 [1] CRAN (R 4.0.3)
#> mgcv 1.8-41 2022-10-21 [4] CRAN (R 4.2.1)
#> mime 0.12 2021-09-28 [1] CRAN (R 4.0.3)
#> multcomp 1.4-20 2022-08-07 [1] CRAN (R 4.0.3)
#> munsell 0.5.0 2018-06-12 [1] CRAN (R 4.0.2)
#> mvtnorm 1.1-3 2021-10-08 [1] CRAN (R 4.0.3)
#> nlme 3.1-149 2020-08-23 [4] CRAN (R 4.0.2)
#> paletteer 1.5.0 2022-10-19 [1] CRAN (R 4.0.3)
#> parameters 0.20.2 2023-01-27 [1] CRAN (R 4.0.3)
#> patchwork 1.1.2 2022-08-19 [1] CRAN (R 4.0.3)
#> pbapply 1.7-0 2023-01-13 [1] CRAN (R 4.0.3)
#> performance 0.10.2 2023-01-12 [1] CRAN (R 4.0.3)
#> pillar 1.8.1 2022-08-19 [1] CRAN (R 4.0.3)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.0.2)
#> purrr 1.0.1 2023-01-10 [1] CRAN (R 4.0.3)
#> R.cache 0.16.0 2022-07-21 [1] CRAN (R 4.0.3)
#> R.methodsS3 1.8.2 2022-06-13 [1] CRAN (R 4.0.3)
#> R.oo 1.25.0 2022-06-12 [1] CRAN (R 4.0.3)
#> R.utils 2.12.2 2022-11-11 [1] CRAN (R 4.0.3)
#> R6 2.5.1 2021-08-19 [1] CRAN (R 4.0.3)
#> Rcpp 1.0.10 2023-01-22 [1] CRAN (R 4.0.3)
#> rematch2 2.1.2 2020-05-01 [1] CRAN (R 4.0.2)
#> reprex 2.0.2 2022-08-17 [1] CRAN (R 4.0.3)
#> rlang 1.0.6 2022-09-24 [1] CRAN (R 4.0.3)
#> rmarkdown 2.20 2023-01-19 [1] CRAN (R 4.0.3)
#> rstudioapi 0.14 2022-08-22 [1] CRAN (R 4.0.3)
#> sandwich 3.0-2 2022-06-15 [1] CRAN (R 4.0.3)
#> scales 1.2.1 2022-08-20 [1] CRAN (R 4.0.3)
#> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.0.3)
#> statsExpressions 1.4.0 2023-01-14 [1] CRAN (R 4.0.3)
#> stringi 1.7.12 2023-01-11 [1] CRAN (R 4.0.3)
#> stringr 1.5.0 2022-12-02 [1] CRAN (R 4.0.3)
#> styler 1.9.0 2023-01-15 [1] CRAN (R 4.0.3)
#> survival 3.4-0 2022-08-09 [4] CRAN (R 4.2.1)
#> TH.data 1.1-1 2022-04-26 [1] CRAN (R 4.0.3)
#> tibble 3.1.8 2022-07-22 [1] CRAN (R 4.0.3)
#> tidyr 1.3.0 2023-01-24 [1] CRAN (R 4.0.3)
#> tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.0.3)
#> utf8 1.2.3 2023-01-31 [1] CRAN (R 4.0.3)
#> vctrs 0.5.2 2023-01-23 [1] CRAN (R 4.0.3)
#> withr 2.5.0 2022-03-03 [1] CRAN (R 4.0.3)
#> xfun 0.37 2023-01-31 [1] CRAN (R 4.0.3)
#> xml2 1.3.3 2021-11-30 [1] CRAN (R 4.0.3)
#> xtable 1.8-4 2019-04-21 [1] CRAN (R 4.0.2)
#> yaml 2.3.7 2023-01-23 [1] CRAN (R 4.0.3)
#> zeallot 0.1.0 2018-01-28 [1] CRAN (R 4.0.3)
#> zoo 1.8-11 2022-09-17 [1] CRAN (R 4.0.3)
#>
#> [1] /media/user/4B/R/x86_64-pc-linux-gnu-library/4.0
#> [2] /usr/local/lib/R/site-library
#> [3] /usr/lib/R/site-library
#> [4] /usr/lib/R/library
#>
#> ──────────────────────────────────────────────────────────────────────────────
Traceback:
13: unique.default(x, nmax = nmax)
12: unique(x, nmax = nmax)
11: factor(x)
10: as.factor(f)
9: split.default(x = seq_len(nrow(x)), f = f, drop = drop, ...)
8: split(x = seq_len(nrow(x)), f = f, drop = drop, ...)
7: lapply(split(x = seq_len(nrow(x)), f = f, drop = drop, ...),
function(ind) x[ind, , drop = FALSE])
6: split.data.frame(., f = new_formula(NULL, enquo(grouping.var)),
drop = TRUE)
5: split(., f = new_formula(NULL, enquo(grouping.var)), drop = TRUE)
4: data %>% split(f = new_formula(NULL, enquo(grouping.var)), drop = TRUE)
3: .grouped_list(., {
{
grouping.var
}
})
2: data %<>% .grouped_list({
{
grouping.var
}
})
1: grouped_ggscatterstats(movies_long, budget, rating, grouping.var = genre)
Created on 2023-02-08 with reprex v2.0.2
Upvotes: 1
Views: 74
Reputation: 21
Yes, I think this was the issue @Phil and @Behnam Hedayat. I tried reinstalling RStudio, I tried updating RStudio, I tried different versions of ggstatsplot to no avail. Finally, I decided to try to upgrade my version of Ubuntu, which did not work due to other issues, but at least it did seem to catch some new updates to the r-base and a few other libraries I could see, I think that solved the issue because the grouped_* commands are now working as they should.
During this upgrade process R updated to R v4.2.2 as @Phil and @Behnam Hedayat suggested. Thank you both for your help.
For anyone that might have this problem in the future, the commands I ran in terminal were the following and I found them here:
sudo apt update
sudo apt upgrade && sudo apt dist-upgrade
sudo update-manager -d
Upvotes: 1