Creating counties spatial dataframe produces a single row dataframe as output unlike the states spatial dataframe

Question

I am trying to replicate what I did for state level and works to county level. Once I have the states spatial data frame, I convert it to a simple features object because I can treat that more like a traditional data frame. Now it can be left_joined to our USArrests data set. When I am tryin to repeat the same ptocess for county level I get a single row dataframe back.More specifically :

library(tidyverse)
library(sf)
library(leaflet)
library(tigris)
options(tigris_use_cache = TRUE)

data("USArrests", package = "datasets")
USArrests <- USArrests %>% as_tibble(rownames = "state")
states_sf <- tigris::states() %>% 
  as("sf") %>% 
  rename(state=NAME) %>% 
  left_join(USArrests) %>% 
  na.omit()
#> Joining, by = "state"

states_sf
#> Simple feature collection with 50 features and 18 fields
#> geometry type:  MULTIPOLYGON
#> dimension:      XY
#> bbox:           xmin: -179.2311 ymin: 18.86546 xmax: 179.8597 ymax: 71.44106
#> epsg (SRID):    4269
#> proj4string:    +proj=longlat +ellps=GRS80 +towgs84=0,0,0,0,0,0,0 +no_defs
#> First 10 features:
#>    REGION DIVISION STATEFP  STATENS GEOID STUSPS          state LSAD MTFCC
#> 1       3        5      54 01779805    54     WV  West Virginia   00 G4000
#> 2       3        5      12 00294478    12     FL        Florida   00 G4000
#> 3       2        3      17 01779784    17     IL       Illinois   00 G4000
#> 4       2        4      27 00662849    27     MN      Minnesota   00 G4000
#> 5       3        5      24 01714934    24     MD       Maryland   00 G4000
#> 6       1        1      44 01219835    44     RI   Rhode Island   00 G4000
#> 7       4        8      16 01779783    16     ID          Idaho   00 G4000
#> 8       1        1      33 01779794    33     NH  New Hampshire   00 G4000
#> 9       3        5      37 01027616    37     NC North Carolina   00 G4000
#> 10      1        1      50 01779802    50     VT        Vermont   00 G4000
#>    FUNCSTAT        ALAND      AWATER    INTPTLAT     INTPTLON Murder
#> 1         A  62265597146   489902816 +38.6472854 -080.6183274    5.7
#> 2         A 138924199212 31386038155 +28.4574302 -082.4091478   15.4
#> 3         A 143788697679  6206693598 +40.1028754 -089.1526108   10.4
#> 4         A 206232257655 18929176411 +46.3158148 -094.1996628    2.7
#> 5         A  25147754905  6983312282 +38.9466584 -076.6744939   11.3
#> 6         A   2677898725  1323551636 +41.5974187 -071.5272723    3.4
#> 7         A 214042908012  2398669593 +44.3484222 -114.5588538    2.6
#> 8         A  23187396994  1028678842 +43.6726907 -071.5843145    2.1
#> 9         A 125921301190 13470062955 +35.5397100 -079.1308636   13.0
#> 10        A  23873467535  1031124865 +44.0604795 -072.6733274    2.2
#>    Assault UrbanPop Rape                       geometry
#> 1       81       39  9.3 MULTIPOLYGON (((-81.74725 3...
#> 2      335       80 31.9 MULTIPOLYGON (((-82.98624 2...
#> 3      249       83 24.0 MULTIPOLYGON (((-91.18529 4...
#> 4       72       66 14.9 MULTIPOLYGON (((-96.78438 4...
#> 5      300       67 27.8 MULTIPOLYGON (((-77.45881 3...
#> 6      174       87  8.3 MULTIPOLYGON (((-71.67264 4...
#> 7      120       54 14.2 MULTIPOLYGON (((-116.8997 4...
#> 8       57       56  9.5 MULTIPOLYGON (((-72.3299 43...
#> 9      337       45 16.1 MULTIPOLYGON (((-82.41674 3...
#> 10      48       32 11.2 MULTIPOLYGON (((-73.31328 4...

When I try to do the same with counties :

library(noncensus)
data(counties)

counties_sf <- counties %>% as_tibble()
counties_sf <- tigris::counties() %>% 
  as("sf") %>% 
  rename(county_name=NAME) %>% 
  left_join(counties) %>% 
  na.omit()

counties_sf

I get a single row dataset:

Answer 1

The function na.omit() will remove all rows with one missing value. That's why you have only one row at the end. Without it, your result has 3.233 rows.