I am trying to learn and use the tidyverse tools and one peculiarity that I seem to encounter is that converting some data frames to tibbles gives surprising results. I tried to make a toy example illustrates the problem but couldn't. Let me show some output that illustrates the problem. > str(bincrct) 'data.frame': 267 obs. of 4 variables: $ StudyID : num 20101 20102 20103 20104 20105 ... $ Intervention: Factor w/ 2 levels "Intervention",..: 2 2 2 2 2 1 1 1 1 1 ... $ Cluster : num 1 1 1 1 1 2 2 2 2 3 ... $ apptx : num 0 0 1 0 0 1 1 1 0 1 ... > as_tibble(bincrct) Error: `x` must be a numeric or a character vector > str(as_tibble(bincrct)) Classes ?tbl_df?, ?tbl? and 'data.frame': 267 obs. of 4 variables: $ StudyID : num 20101 20102 20103 20104 20105 ... $ Intervention: Factor w/ 2 levels "Intervention",..: 2 2 2 2 2 1 1 1 1 1 ... $ Cluster : num 1 1 1 1 1 2 2 2 2 3 ... $ apptx : num 0 0 1 0 0 1 1 1 0 1 ... When I tried to create a data frame and run as_tibble() on it, things behaved correctly. My best guess is that the old data frame I am using has some additional baggage with it that I am unaware of. I also tried manually creating a tibble as follows which also did not work. > with(bincrct, tibble(StudyID,Intervention,Cluster,apptx)) Error: `x` must be a numeric or a character vector Any ideas? Here is my sessionInfo(). I just updated my packages this morning to see if that was the issue. > sessionInfo() R version 3.5.0 Patched (2018-04-23 r74633) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Slackware 14.2 x86_64 (post 14.2 -current) Matrix products: default BLAS: /usr/local/lib64/R/lib/libRblas.so LAPACK: /usr/local/lib64/R/lib/libRlapack.so locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_US.UTF-8 LC_COLLATE=C [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 [7] LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] forcats_0.3.0 stringr_1.3.1 dplyr_0.7.5 purrr_0.2.5 [5] readr_1.1.1 tidyr_0.8.1 tibble_1.4.2 ggplot2_2.2.1 [9] tidyverse_1.2.1 knitr_1.20 loaded via a namespace (and not attached): [1] Rcpp_0.12.17 cellranger_1.1.0 pillar_1.2.3 compiler_3.5.0 [5] plyr_1.8.4 bindr_0.1.1 tools_3.5.0 lubridate_1.7.4 [9] jsonlite_1.5 nlme_3.1-137 gtable_0.2.0 lattice_0.20-35 [13] pkgconfig_2.0.1 rlang_0.2.1 psych_1.8.4 cli_1.0.0 [17] rstudioapi_0.7 parallel_3.5.0 haven_1.1.1 bindrcpp_0.2.2 [21] xml2_1.2.0 httr_1.3.1 hms_0.4.2 grid_3.5.0 [25] tidyselect_0.2.4 glue_1.2.0 R6_2.2.2 readxl_1.1.0 [29] foreign_0.8-70 modelr_0.1.2 reshape2_1.4.3 magrittr_1.5 [33] scales_0.5.0 rvest_0.3.2 assertthat_0.2.0 mnormt_1.5-5 [37] colorspace_1.3-2 stringi_1.2.3 lazyeval_0.2.1 munsell_0.5.0 [41] broom_0.4.4 crayon_1.3.4 -- Kevin E. Thorpe Head of Biostatistics, Applied Health Research Centre (AHRC) Li Ka Shing Knowledge Institute of St. Michael's Hospital Assistant Professor, Dalla Lana School of Public Health University of Toronto email: kevin.thorpe at utoronto.ca Tel: 416.864.5776 Fax: 416.864.3016