Error in Breaks not unique about skimr

[npjc]

👍

Would be great if pesky variables which do NOT vary would work:

library(skimr)
x = rep(0, 5)
d <- data.frame(x)
d
#>   x
#> 1 0
#> 2 0
#> 3 0
#> 4 0
#> 5 0

skim(d)
#> Error in cut.default(x, 10): 'breaks' are not unique

i.e. maybe fallback on something else when cut.default gets upset:

cut.default(x, 10)
#> Error in cut.default(x, 10): 'breaks' are not unique

session_info()

devtools::session_info()
#> Session info -------------------------------------------------------------
#>  setting  value                       
#>  version  R version 3.4.0 (2017-04-21)
#>  system   x86_64, darwin15.6.0        
#>  ui       X11                         
#>  language (EN)                        
#>  collate  en_CA.UTF-8                 
#>  tz       America/Vancouver           
#>  date     2017-05-31
#> Packages -----------------------------------------------------------------
#>  package    * version    date       source                             
#>  assertthat   0.2.0      2017-04-11 CRAN (R 3.4.0)                     
#>  backports    1.1.0      2017-05-22 CRAN (R 3.4.0)                     
#>  base       * 3.4.0      2017-04-21 local                              
#>  compiler     3.4.0      2017-04-21 local                              
#>  datasets   * 3.4.0      2017-04-21 local                              
#>  devtools     1.13.1     2017-05-13 CRAN (R 3.4.0)                     
#>  digest       0.6.12     2017-01-27 CRAN (R 3.4.0)                     
#>  dplyr        0.6.0      2017-06-01 Github (tidyverse/dplyr@b064c4b)   
#>  evaluate     0.10       2016-10-11 CRAN (R 3.4.0)                     
#>  glue         1.0.0.9000 2017-06-01 Github (tidyverse/glue@0479f1b)    
#>  graphics   * 3.4.0      2017-04-21 local                              
#>  grDevices  * 3.4.0      2017-04-21 local                              
#>  htmltools    0.3.6      2017-04-28 CRAN (R 3.4.0)                     
#>  knitr        1.16       2017-05-18 CRAN (R 3.4.0)                     
#>  magrittr     1.5        2014-11-22 CRAN (R 3.4.0)                     
#>  memoise      1.1.0      2017-04-21 CRAN (R 3.4.0)                     
#>  methods    * 3.4.0      2017-04-21 local                              
#>  purrr        0.2.2.2    2017-05-11 CRAN (R 3.4.0)                     
#>  R6           2.2.1      2017-05-10 cran (@2.2.1)                      
#>  Rcpp         0.12.11    2017-05-22 CRAN (R 3.4.0)                     
#>  rlang        0.1.1.9000 2017-05-27 Github (tidyverse/rlang@c351186)   
#>  rmarkdown    1.5        2017-04-26 CRAN (R 3.4.0)                     
#>  rprojroot    1.2        2017-01-16 CRAN (R 3.4.0)                     
#>  skimr      * 1.0        2017-06-01 Github (ropenscilabs/skimr@766cab0)
#>  stats      * 3.4.0      2017-04-21 local                              
#>  stringi      1.1.5      2017-04-07 CRAN (R 3.4.0)                     
#>  stringr      1.2.0      2017-02-18 CRAN (R 3.4.0)                     
#>  tibble       1.3.3      2017-05-28 cran (@1.3.3)                      
#>  tidyr        0.6.3      2017-05-15 CRAN (R 3.4.0)                     
#>  tools        3.4.0      2017-04-21 local                              
#>  utils      * 3.4.0      2017-04-21 local                              
#>  withr        1.0.2      2016-06-20 CRAN (R 3.4.0)                     
#>  yaml         2.1.14     2016-11-12 CRAN (R 3.4.0)

[gshotwell]

I think this is fixed here: gshotwell@e0071ea

I was waiting to bring it over in the grouped_df PR when we figure out the output stuff.

[elinw]

Why don't you do a separate PR for that?

[elinw]

From testing it seems like all 0s is the issue not having no variation in general.

Fixed by #81