Mutate: Divide the variable by minimum value in a group

tidyverse
#1

I would like to create a new variable by dividing the old variable by group means.

data <-
  data.frame(
    "Subgroup" = rep (1:2, c(10, 5)),
    "Observation" = c(rnorm(14), NA)
  )
data %>%
  group_by(Subgroup) %>%
  mutate("New variable" = Observation / mean(Observation, na.rm = TRUE),
                    GMean=mean(Observation, na.rm = TRUE))

I get the following output:

A tibble: 15 x 4

Groups: Subgroup [2]

Subgroup Observation New variable Gmean

1 1 0.185 -2.58 -0.0719
2 1 -0.0437 0.608 -0.0719
3 1 -0.216 3.00 -0.0719
4 1 1.46 -20.4 -0.0719
5 1 0.230 -3.19 -0.0719
6 1 0.108 -1.50 -0.0719
7 1 -1.38 19.2 -0.0719
8 1 -0.968 13.5 -0.0719
9 1 0.252 -3.50 -0.0719
10 1 -1.09 15.2 -0.0719
11 2 0.398 -5.53 -0.0719
12 2 -0.996 13.9 -0.0719
13 2 0.101 -1.40 -0.0719
14 2 0.954 -13.3 -0.0719
15 2 NA NA -0.0719

Since I have two groups I had expected to see the Gmean for group 1 and group 2 to be different but it appears the overal mean is used to divide. How can I get to divide bt the group mean?

#2

I can't reproduce your issue with the code or data you provided.
Gmean is showing two values

#3

You are right, I checked with R4.05 and R4.10 without using Rstudio and it is ok but when I run it via Rstudio I get a different result. My R sessionInfo from Rstudio is

sessionInfo()
R version 4.1.0 (2021-05-18)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252

attached base packages:
[1] grid stats graphics grDevices utils datasets methods base

other attached packages:
[1] doseResponse_0.0.1.8 minpack.lm_1.2-1 emmeans_1.6.2-1 data.table_1.14.0 msm_1.6.8 plyr_1.8.6
[7] drc_3.2-0 drcData_1.1-3 MASS_7.3-54 nlme_3.1-152 plotly_4.9.4.1 yardstick_0.0.8
[13] workflowsets_0.1.0 workflows_0.2.3 tune_0.1.6 rsample_0.1.0 recipes_0.1.16 parsnip_0.1.7
[19] modeldata_0.1.1 infer_0.5.4 dials_0.0.9 scales_1.1.1 tidymodels_0.1.3 broom_0.7.9
[25] forcats_0.5.1 dplyr_1.0.7 purrr_0.3.4 readr_2.0.0 tidyr_1.1.3 tibble_3.1.3
[31] tidyverse_1.3.1 kableExtra_1.3.4 knitr_1.33 pander_0.6.4 qdapRegex_0.7.2 stringr_1.4.0
[37] readxl_1.3.1 egg_0.4.5 ggplot2_3.3.5 gridExtra_2.3 gtable_0.3.0

loaded via a namespace (and not attached):
[1] backports_1.2.1 systemfonts_1.0.2 lazyeval_0.2.2 splines_4.1.0 listenv_0.8.0 TH.data_1.0-10 digest_0.6.27
[8] foreach_1.5.1 htmltools_0.5.1.1 fansi_0.5.0 magrittr_2.0.1 tzdb_0.1.2 openxlsx_4.2.4 globals_0.14.0
[15] modelr_0.1.8 gower_0.2.2 sandwich_3.0-1 svglite_2.0.0 hardhat_0.1.6 colorspace_2.0-2 rvest_1.0.1
[22] haven_2.4.2 xfun_0.24 crayon_1.4.1 jsonlite_1.7.2 survival_3.2-11 zoo_1.8-9 iterators_1.0.13
[29] glue_1.4.2 ipred_0.9-11 webshot_0.5.2 car_3.0-11 abind_1.4-5 mvtnorm_1.1-2 DBI_1.1.1
[36] Rcpp_1.0.7 plotrix_3.8-1 xtable_1.8-4 viridisLite_0.4.0 GPfit_1.0-8 foreign_0.8-81 lava_1.6.9
[43] prodlim_2019.11.13 htmlwidgets_1.5.3 httr_1.4.2 ellipsis_0.3.2 farver_2.1.0 pkgconfig_2.0.3 nnet_7.3-16
[50] dbplyr_2.1.1 utf8_1.2.2 labeling_0.4.2 tidyselect_1.1.1 rlang_0.4.11 DiceDesign_1.9 munsell_0.5.0
[57] cellranger_1.1.0 tools_4.1.0 cli_3.0.1 generics_0.1.0 evaluate_0.14 yaml_2.2.1 fs_1.5.0
[64] zip_2.2.0 future_1.21.0 xml2_1.3.2 compiler_4.1.0 rstudioapi_0.13 curl_4.3.2 reprex_2.0.0
[71] lhs_1.1.1 stringi_1.7.3 highr_0.9 lattice_0.20-44 Matrix_1.3-4 vctrs_0.3.8 pillar_1.6.2
[78] lifecycle_1.0.0 furrr_0.2.3 estimability_1.3 R6_2.5.0 rio_0.5.27 parallelly_1.27.0 codetools_0.2-18
[85] gtools_3.9.2 assertthat_0.2.1 withr_2.4.2 multcomp_1.4-17 expm_0.999-6 parallel_4.1.0 hms_1.1.0
[92] rpart_4.1-15 timeDate_3043.102 coda_0.19-4 class_7.3-19 rmarkdown_2.9 carData_3.0-4 pROC_1.17.0.1
[99] lubridate_1.7.10

#4

The first thing you should do is set.seed() on your script. That way you can make a plausible comparison between running in different environments. I.e Rstudio or Rterm or Rgui or what have you.

#5

Also check your dplyr package version across the differing environment's.

#6

Thank you for the suggestions.

Regards,

Luwis

#7

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