Calling tibble::rowid_to_column on an object of class "sf" before dplyr::rename will cause " internal error: can't find agr columns"

[LDalby]

I reported this on the sf repo where Edzer remarked that it was an issue with rowid_to_column messing up the agr attribute.
So I thought I would report it here.

I use this in my spatial workflow quite often, so I was wondering if it is possible to fix somehow? There are workarounds of course, but if that could be avoided it would be great!

Issue on the sf repo is here

library(sf)
#> Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUE

read_sf(system.file("shape/nc.shp", package = "sf")) |>
  tibble::rowid_to_column(var = "object_id") |>
  dplyr::rename(a_r_e_a = AREA)
#> Error in rename.sf(tibble::rowid_to_column(read_sf(system.file("shape/nc.shp", : internal error: can't find `agr` columns

read_sf(system.file("shape/nc.shp", package = "sf")) |>
  # tibble::rowid_to_column(var = "object_id") |>
  dplyr::rename(a_r_e_a = AREA)
#> Simple feature collection with 100 features and 14 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
#> Geodetic CRS:  NAD27
#> # A tibble: 100 × 15
#>    a_r_e_a PERIMETER CNTY_ CNTY_ID NAME        FIPS  FIPSNO CRESS_ID BIR74 SID74
#>      <dbl>     <dbl> <dbl>   <dbl> <chr>       <chr>  <dbl>    <int> <dbl> <dbl>
#>  1   0.114      1.44  1825    1825 Ashe        37009  37009        5  1091     1
#>  2   0.061      1.23  1827    1827 Alleghany   37005  37005        3   487     0
#>  3   0.143      1.63  1828    1828 Surry       37171  37171       86  3188     5
#>  4   0.07       2.97  1831    1831 Currituck   37053  37053       27   508     1
#>  5   0.153      2.21  1832    1832 Northampton 37131  37131       66  1421     9
#>  6   0.097      1.67  1833    1833 Hertford    37091  37091       46  1452     7
#>  7   0.062      1.55  1834    1834 Camden      37029  37029       15   286     0
#>  8   0.091      1.28  1835    1835 Gates       37073  37073       37   420     0
#>  9   0.118      1.42  1836    1836 Warren      37185  37185       93   968     4
#> 10   0.124      1.43  1837    1837 Stokes      37169  37169       85  1612     1
#> # ℹ 90 more rows
#> # ℹ 5 more variables: NWBIR74 <dbl>, BIR79 <dbl>, SID79 <dbl>, NWBIR79 <dbl>,
#> #   geometry <MULTIPOLYGON [°]>

^{Created on 2023-08-15 with reprex v2.0.2}

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.3.1 (2023-06-16)
#>  os       macOS Ventura 13.5
#>  system   aarch64, darwin20
#>  ui       X11
#>  language (EN)
#>  collate  en_US.UTF-8
#>  ctype    en_US.UTF-8
#>  tz       Europe/Copenhagen
#>  date     2023-08-15
#>  pandoc   3.1.1 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package     * version date (UTC) lib source
#>  class         7.3-22  2023-05-03 [1] CRAN (R 4.3.1)
#>  classInt      0.4-9   2023-02-28 [1] CRAN (R 4.3.0)
#>  cli           3.6.1   2023-03-23 [1] CRAN (R 4.3.0)
#>  DBI           1.1.3   2022-06-18 [1] CRAN (R 4.3.0)
#>  digest        0.6.33  2023-07-07 [1] CRAN (R 4.3.0)
#>  dplyr         1.1.2   2023-04-20 [1] CRAN (R 4.3.0)
#>  e1071         1.7-13  2023-02-01 [1] CRAN (R 4.3.0)
#>  evaluate      0.21    2023-05-05 [1] CRAN (R 4.3.0)
#>  fansi         1.0.4   2023-01-22 [1] CRAN (R 4.3.0)
#>  fastmap       1.1.1   2023-02-24 [1] CRAN (R 4.3.0)
#>  fs            1.6.3   2023-07-20 [1] CRAN (R 4.3.0)
#>  generics      0.1.3   2022-07-05 [1] CRAN (R 4.3.0)
#>  glue          1.6.2   2022-02-24 [1] CRAN (R 4.3.0)
#>  htmltools     0.5.6   2023-08-10 [1] CRAN (R 4.3.0)
#>  KernSmooth    2.23-22 2023-07-10 [1] CRAN (R 4.3.0)
#>  knitr         1.43    2023-05-25 [1] CRAN (R 4.3.0)
#>  lifecycle     1.0.3   2022-10-07 [1] CRAN (R 4.3.0)
#>  magrittr      2.0.3   2022-03-30 [1] CRAN (R 4.3.0)
#>  pillar        1.9.0   2023-03-22 [1] CRAN (R 4.3.0)
#>  pkgconfig     2.0.3   2019-09-22 [1] CRAN (R 4.3.0)
#>  proxy         0.4-27  2022-06-09 [1] CRAN (R 4.3.0)
#>  purrr         1.0.2   2023-08-10 [1] CRAN (R 4.3.0)
#>  R.cache       0.16.0  2022-07-21 [1] CRAN (R 4.3.0)
#>  R.methodsS3   1.8.2   2022-06-13 [1] CRAN (R 4.3.0)
#>  R.oo          1.25.0  2022-06-12 [1] CRAN (R 4.3.0)
#>  R.utils       2.12.2  2022-11-11 [1] CRAN (R 4.3.0)
#>  R6            2.5.1   2021-08-19 [1] CRAN (R 4.3.0)
#>  Rcpp          1.0.11  2023-07-06 [1] CRAN (R 4.3.0)
#>  reprex        2.0.2   2022-08-17 [1] CRAN (R 4.3.0)
#>  rlang         1.1.1   2023-04-28 [1] CRAN (R 4.3.0)
#>  rmarkdown     2.23    2023-07-01 [1] CRAN (R 4.3.0)
#>  rstudioapi    0.15.0  2023-07-07 [1] CRAN (R 4.3.0)
#>  sessioninfo   1.2.2   2021-12-06 [1] CRAN (R 4.3.0)
#>  sf          * 1.0-14  2023-07-11 [1] CRAN (R 4.3.0)
#>  styler        1.10.1  2023-06-05 [1] CRAN (R 4.3.0)
#>  tibble        3.2.1   2023-03-20 [1] CRAN (R 4.3.0)
#>  tidyselect    1.2.0   2022-10-10 [1] CRAN (R 4.3.0)
#>  units         0.8-3   2023-08-10 [1] CRAN (R 4.3.0)
#>  utf8          1.2.3   2023-01-31 [1] CRAN (R 4.3.0)
#>  vctrs         0.6.3   2023-06-14 [1] CRAN (R 4.3.0)
#>  withr         2.5.0   2022-03-03 [1] CRAN (R 4.3.0)
#>  xfun          0.40    2023-08-09 [1] CRAN (R 4.3.0)
#>  yaml          2.3.7   2023-01-23 [1] CRAN (R 4.3.0)
#> 
#>  [1] /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/library
#> 
#> ──────────────────────────────────────────────────────────────────────────────

[krlmlr]

This seems to be the underlying issue:

options(conflicts.policy = list(warn = FALSE))

library(sf)
#> Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUE
library(dplyr)

input <- read_sf(system.file("shape/nc.shp", package = "sf"))

x1 <-
  input |>
  dplyr::mutate(var = row_number(), .before = 1)

x2 <-
  input |>
  tibble::rowid_to_column("var")

waldo::compare(x1, x2)
#> `names(attr(old, 'agr'))[1:4]`: "var" "AREA" "PERIMETER" "CNTY_"
#> `names(attr(new, 'agr'))[1:3]`:       "AREA" "PERIMETER" "CNTY_"
#> 
#> `attr(old, 'agr')[12:15]`: "NA" "NA" "NA" "NA"
#> `attr(new, 'agr')[12:14]`: "NA" "NA" "NA"

^{Created on 2023-08-15 with reprex v2.0.2}

I don't know about the semantics of the "agr" attribute, and doesn't seem to be too much I can do here. The sf package could override [<- and [[<- for its class to ensure that x2 has the same shape as x1, without changing tibble's implementation.

[edzer]

Thanks, but adding a [<-.sf that takes care of the agr attributes makes sure that here the attributes get set correctly in new_data and out, but here they're being set back to the previous, non-modified version.

[edzer]

Removing the call to vectbl_restore leads to the correct result.

[krlmlr]

Thanks. I agree that it's not this function's business to call vectbl_restore() .

[krlmlr]

Over the last years, various variants were tried to preserve the "class" attribute after add_column() . To be fully consistent, we'd need to build this on top of mutate() . What if this function required dplyr for non-data-frame and non-tibble objects?