Create a tibble of precinct stats
Arguments
- shp
a tibble::tibble with precinct stats
- ...
named tidyselections
Value
A tibble::tibble with columns group, rowname, and one column
per precinct (V1, V2, ...). Groups are labeled with human-readable
names (e.g. "Total Population", "Voting Age Population").
Examples
hover_precinct(dc, pop = dplyr::starts_with('pop'), vap = dplyr::starts_with('vap'))
#> # A tibble: 18 × 145
#> group rowname V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 Total Po… Total 9944 6908 6354 6532 4823 10853 3327 6178 5809 5795
#> 2 Total Po… Hispan… 840 715 595 602 456 1023 330 434 684 608
#> 3 Total Po… White 4185 4090 3855 4375 3765 7405 2178 4662 3692 3952
#> 4 Total Po… Black 3418 644 367 286 103 579 208 275 489 391
#> 5 Total Po… Native 12 16 16 3 4 10 0 6 2 1
#> 6 Total Po… Asian 1020 1076 1251 954 266 1191 386 407 739 527
#> 7 Total Po… NH/PI 11 14 0 2 2 9 3 3 0 0
#> 8 Total Po… Other 39 31 44 27 25 60 25 55 15 21
#> 9 Total Po… Two+ 419 322 226 283 202 576 197 336 188 295
#> 10 Voting A… Total 8803 6804 6170 6225 4217 10004 2669 4780 5216 5018
#> 11 Voting A… Hispan… 778 701 572 566 371 929 237 322 624 509
#> 12 Voting A… White 4122 4045 3766 4202 3342 6818 1790 3616 3247 3455
#> 13 Voting A… Black 2509 630 365 263 92 556 176 228 480 351
#> 14 Voting A… Native 11 16 14 3 2 10 0 6 2 0
#> 15 Voting A… Asian 979 1059 1220 918 249 1156 321 378 718 475
#> 16 Voting A… NH/PI 11 11 0 2 1 9 3 3 0 0
#> 17 Voting A… Other 32 30 35 20 23 49 24 39 13 19
#> 18 Voting A… Two+ 361 312 198 251 137 477 118 188 132 209
#> # ℹ 133 more variables: V11 <dbl>, V12 <dbl>, V13 <dbl>, V14 <dbl>, V15 <dbl>,
#> # V16 <dbl>, V17 <dbl>, V18 <dbl>, V19 <dbl>, V20 <dbl>, V21 <dbl>,
#> # V22 <dbl>, V23 <dbl>, V24 <dbl>, V25 <dbl>, V26 <dbl>, V27 <dbl>,
#> # V28 <dbl>, V29 <dbl>, V30 <dbl>, V31 <dbl>, V32 <dbl>, V33 <dbl>,
#> # V34 <dbl>, V35 <dbl>, V36 <dbl>, V37 <dbl>, V38 <dbl>, V39 <dbl>,
#> # V40 <dbl>, V41 <dbl>, V42 <dbl>, V43 <dbl>, V44 <dbl>, V45 <dbl>,
#> # V46 <dbl>, V47 <dbl>, V48 <dbl>, V49 <dbl>, V50 <dbl>, V51 <dbl>, …
