Running examples in ‘sf-Ex.R’ failed
The error most likely occurred in:

> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: tidyverse
> ### Title: Tidyverse methods for sf objects (remove .sf suffix!)
> ### Aliases: tidyverse filter.sf arrange.sf group_by.sf ungroup.sf
> ###   mutate.sf transmute.sf select.sf rename.sf slice.sf summarise.sf
> ###   summarise distinct.sf gather.sf spread.sf sample_n.sf sample_frac.sf
> ###   nest.sf separate.sf separate_rows.sf unite.sf unnest.sf inner_join.sf
> ###   left_join.sf right_join.sf full_join.sf semi_join.sf anti_join.sf
> 
> ### ** Examples
> 
> library(dplyr)

Attaching package: ‘dplyr’

The following objects are masked from ‘package:stats’:

    filter, lag

The following objects are masked from ‘package:base’:

    intersect, setdiff, setequal, union

> nc = st_read(system.file("shape/nc.shp", package="sf"))
Reading layer `nc' from data source `/home/hornik/tmp/R.check/r-devel-gcc/Work/build/Packages/sf/shape/nc.shp' using driver `ESRI Shapefile'
Simple feature collection with 100 features and 14 fields
geometry type:  MULTIPOLYGON
dimension:      XY
bbox:           xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
geographic CRS: NAD27
> nc %>% filter(AREA > .1) %>% plot()
Warning: plotting the first 10 out of 14 attributes; use max.plot = 14 to plot all
> # plot 10 smallest counties in grey:
> st_geometry(nc) %>% plot()
> nc %>% select(AREA) %>% arrange(AREA) %>% slice(1:10) %>% plot(add = TRUE, col = 'grey')
> title("the ten counties with smallest area")
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc %>% group_by(area_cl) %>% class()
[1] "sf"         "grouped_df" "tbl_df"     "tbl"        "data.frame"
> nc2 <- nc %>% mutate(area10 = AREA/10)
> nc %>% transmute(AREA = AREA/10, geometry = geometry) %>% class()
[1] "sf"         "data.frame"
> nc %>% transmute(AREA = AREA/10) %>% class()
[1] "sf"         "data.frame"
> nc %>% select(SID74, SID79) %>% names()
[1] "SID74"    "SID79"    "geometry"
> nc %>% select(SID74, SID79, geometry) %>% names()
[1] "SID74"    "SID79"    "geometry"
> nc %>% select(SID74, SID79) %>% class()
[1] "sf"         "data.frame"
> nc %>% select(SID74, SID79, geometry) %>% class()
[1] "sf"         "data.frame"
> nc2 <- nc %>% rename(area = AREA)
> nc %>% slice(1:2)
Simple feature collection with 2 features and 15 fields
geometry type:  MULTIPOLYGON
dimension:      XY
bbox:           xmin: -81.74107 ymin: 36.23436 xmax: -80.90344 ymax: 36.58965
geographic CRS: NAD27
   AREA PERIMETER CNTY_ CNTY_ID      NAME  FIPS FIPSNO CRESS_ID BIR74 SID74
1 0.114     1.442  1825    1825      Ashe 37009  37009        5  1091     1
2 0.061     1.231  1827    1827 Alleghany 37005  37005        3   487     0
  NWBIR74 BIR79 SID79 NWBIR79    area_cl                       geometry
1      10  1364     0      19 (0.1,0.12] MULTIPOLYGON (((-81.47276 3...
2      10   542     3      12    (0,0.1] MULTIPOLYGON (((-81.23989 3...
> nc$area_cl = cut(nc$AREA, c(0, .1, .12, .15, .25))
> nc.g <- nc %>% group_by(area_cl)
> nc.g %>% summarise(mean(AREA))
`summarise()` ungrouping output (override with `.groups` argument)
Simple feature collection with 4 features and 2 fields
geometry type:  MULTIPOLYGON
dimension:      XY
bbox:           xmin: -84.32385 ymin: 33.88199 xmax: -75.45698 ymax: 36.58965
geographic CRS: NAD27
# A tibble: 4 x 3
  area_cl    `mean(AREA)`                                               geometry
  <fct>             <dbl>                                     <MULTIPOLYGON [°]>
1 (0,0.1]          0.0760 (((-77.96073 34.18924, -77.96587 34.24229, -77.97528 …
2 (0.1,0.12]       0.112  (((-84.29104 35.21054, -84.22594 35.2616, -84.17973 3…
3 (0.12,0.1…       0.134  (((-76.54427 34.58783, -76.55515 34.61066, -76.53775 …
4 (0.15,0.2…       0.190  (((-78.02592 34.32877, -78.01131 34.31261, -78.00702 …
> nc.g %>% summarise(mean(AREA)) %>% plot(col = grey(3:6 / 7))
`summarise()` ungrouping output (override with `.groups` argument)
> nc %>% as.data.frame %>% summarise(mean(AREA))
  mean(AREA)
1    0.12626
> nc[c(1:100, 1:10), ] %>% distinct() %>% nrow()
[1] 100
> library(tidyr)
Error in library(tidyr) : there is no package called ‘tidyr’
Execution halted