elections: MEDSL data in R

This is an R package for accessing data on U.S. elections from the MIT Election Data and Science Lab.

Installation

Install from GitHub:

if (!require('devtools', quietly = TRUE)) install.packages('devtools')
devtools::install_github('MEDSL/elections')

Use

library(elections)
# We'll use dplyr for ease of illustration below
library(dplyr)

The package makes available the following datasets:

• presidential_precincts_2016
• senate_precincts_2016
• house_precincts_2016
• state_precincts_2016
• local_precincts_2016
• state_ids
• county_ids
• county_sub_ids

presidential_precincts_2016 %>%
  select(state_postal, county_fips, precinct, candidate, party, votes)
#> # A tibble: 505,862 x 6
#>    state_postal county_fips precinct                candidate party  votes
#>    <chr>              <dbl> <chr>                   <chr>     <chr>  <dbl>
#>  1 AL                  1001 10.JONES.COMMUNITY.CTR  Alabama … demo…  119  
#>  2 AL                  1001 10.JONES.COMMUNITY.CTR  Alabama … repu…  120  
#>  3 AL                  1001 10.JONES.COMMUNITY.CTR  Over Vot… <NA>     0  
#>  4 AL                  1001 10.JONES.COMMUNITY.CTR  Under Vo… <NA>   119  
#>  5 AL                  1001 100.TRINITY.METHODIST   Alabama … demo…  127  
#>  6 AL                  1001 100.TRINITY.METHODIST   Alabama … repu…  759  
#>  7 AL                  1001 100.TRINITY.METHODIST   Over Vot… <NA>     0  
#>  8 AL                  1001 100.TRINITY.METHODIST   Under Vo… <NA>  1299  
#>  9 AL                  1001 110.CENTRAL.AL.ELECTRIC Alabama … demo…  173  
#> 10 AL                  1001 110.CENTRAL.AL.ELECTRIC Alabama … repu…   62.0
#> # ... with 505,852 more rows

senate_precincts_2016 %>%
  select(state_postal, county_fips, precinct, candidate, party, votes)
#> # A tibble: 257,278 x 6
#>    state_postal county_fips precinct                candidate party  votes
#>    <chr>              <dbl> <chr>                   <chr>     <chr>  <dbl>
#>  1 AL                  1001 10.JONES.COMMUNITY.CTR  Alabama … demo…  119  
#>  2 AL                  1001 10.JONES.COMMUNITY.CTR  Alabama … repu…  120  
#>  3 AL                  1001 10.JONES.COMMUNITY.CTR  Over Vot… <NA>     0  
#>  4 AL                  1001 10.JONES.COMMUNITY.CTR  Under Vo… <NA>   119  
#>  5 AL                  1001 100.TRINITY.METHODIST   Alabama … demo…  127  
#>  6 AL                  1001 100.TRINITY.METHODIST   Alabama … repu…  759  
#>  7 AL                  1001 100.TRINITY.METHODIST   Over Vot… <NA>     0  
#>  8 AL                  1001 100.TRINITY.METHODIST   Under Vo… <NA>  1299  
#>  9 AL                  1001 110.CENTRAL.AL.ELECTRIC Alabama … demo…  173  
#> 10 AL                  1001 110.CENTRAL.AL.ELECTRIC Alabama … repu…   62.0
#> # ... with 257,268 more rows

house_precincts_2016 %>%
  select(state_postal, county_fips, precinct, candidate, party, votes)
#> # A tibble: 179,316 x 6
#>    state_postal county_fips precinct                candidate party  votes
#>    <chr>              <dbl> <chr>                   <chr>     <chr>  <dbl>
#>  1 AL                  1001 10.JONES.COMMUNITY.CTR  Alabama … demo…  119  
#>  2 AL                  1001 10.JONES.COMMUNITY.CTR  Alabama … repu…  120  
#>  3 AL                  1001 10.JONES.COMMUNITY.CTR  Over Vot… <NA>     0  
#>  4 AL                  1001 10.JONES.COMMUNITY.CTR  Under Vo… <NA>   119  
#>  5 AL                  1001 100.TRINITY.METHODIST   Alabama … demo…  127  
#>  6 AL                  1001 100.TRINITY.METHODIST   Alabama … repu…  759  
#>  7 AL                  1001 100.TRINITY.METHODIST   Over Vot… <NA>     0  
#>  8 AL                  1001 100.TRINITY.METHODIST   Under Vo… <NA>  1299  
#>  9 AL                  1001 110.CENTRAL.AL.ELECTRIC Alabama … demo…  173  
#> 10 AL                  1001 110.CENTRAL.AL.ELECTRIC Alabama … repu…   62.0
#> # ... with 179,306 more rows

state_precincts_2016 %>%
  select(state_postal, county_fips, precinct, candidate, party, votes)
#> # A tibble: 1,619,465 x 6
#>    state_postal county_fips precinct                candidate party  votes
#>    <chr>              <dbl> <chr>                   <chr>     <chr>  <dbl>
#>  1 AL                  1001 10.JONES.COMMUNITY.CTR  Alabama … demo…  119  
#>  2 AL                  1001 10.JONES.COMMUNITY.CTR  Alabama … repu…  120  
#>  3 AL                  1001 10.JONES.COMMUNITY.CTR  Over Vot… <NA>     0  
#>  4 AL                  1001 10.JONES.COMMUNITY.CTR  Under Vo… <NA>   119  
#>  5 AL                  1001 100.TRINITY.METHODIST   Alabama … demo…  127  
#>  6 AL                  1001 100.TRINITY.METHODIST   Alabama … repu…  759  
#>  7 AL                  1001 100.TRINITY.METHODIST   Over Vot… <NA>     0  
#>  8 AL                  1001 100.TRINITY.METHODIST   Under Vo… <NA>  1299  
#>  9 AL                  1001 110.CENTRAL.AL.ELECTRIC Alabama … demo…  173  
#> 10 AL                  1001 110.CENTRAL.AL.ELECTRIC Alabama … repu…   62.0
#> # ... with 1,619,455 more rows

local_precincts_2016 %>%
  select(state_postal, county_fips, precinct, candidate, party, votes)
#> # A tibble: 497,659 x 6
#>    state_postal county_fips precinct                candidate party  votes
#>    <chr>              <dbl> <chr>                   <chr>     <chr>  <dbl>
#>  1 AL                  1001 10.JONES.COMMUNITY.CTR  Alabama … demo…  119  
#>  2 AL                  1001 10.JONES.COMMUNITY.CTR  Alabama … repu…  120  
#>  3 AL                  1001 10.JONES.COMMUNITY.CTR  Over Vot… <NA>     0  
#>  4 AL                  1001 10.JONES.COMMUNITY.CTR  Under Vo… <NA>   119  
#>  5 AL                  1001 100.TRINITY.METHODIST   Alabama … demo…  127  
#>  6 AL                  1001 100.TRINITY.METHODIST   Alabama … repu…  759  
#>  7 AL                  1001 100.TRINITY.METHODIST   Over Vot… <NA>     0  
#>  8 AL                  1001 100.TRINITY.METHODIST   Under Vo… <NA>  1299  
#>  9 AL                  1001 110.CENTRAL.AL.ELECTRIC Alabama … demo…  173  
#> 10 AL                  1001 110.CENTRAL.AL.ELECTRIC Alabama … repu…   62.0
#> # ... with 497,649 more rows

State identifiers:

head(state_ids)
#>        state state_icpsr state_postal state_fips
#> 1    Alabama          41           AL          1
#> 2     Alaska          81           AK          2
#> 3    Arizona          61           AZ          4
#> 4   Arkansas          42           AR          5
#> 5 California          71           CA          6
#> 6   Colorado          62           CO          8

County identifiers:

head(county_ids)
#>   state_postal county_fips county_ansi    county_name  land_area
#> 1           AL       01001    00161526 Autauga County 1539614693
#> 2           AL       01003    00161527 Baldwin County 4117605847
#> 3           AL       01005    00161528 Barbour County 2292144656
#> 4           AL       01007    00161529    Bibb County 1612165763
#> 5           AL       01009    00161530  Blount County 1670079465
#> 6           AL       01011    00161531 Bullock County 1613059168
#>   water_area land_area_sq_mi water_area_sq_mi county_lat county_long
#> 1   25744269         594.449            9.940   32.53224   -86.64644
#> 2 1133109409        1589.817          437.496   30.65922   -87.74607
#> 3   50538698         885.002           19.513   31.87025   -85.40510
#> 4    9603798         622.461            3.708   33.01589   -87.12715
#> 5   15039864         644.821            5.807   33.97736   -86.56644
#> 6    6054988         622.806            2.338   32.10176   -85.71726

County subdivision identifiers:

head(county_sub_ids)
#>   state_postal county_sub_fips county_sub_ansi  county_sub_name
#> 1           AL      0100190171        00161593 Autaugaville CCD
#> 2           AL      0100190315        00165647  Billingsley CCD
#> 3           AL      0100192106        00165648      Marbury CCD
#> 4           AL      0100192628        00165649   Prattville CCD
#> 5           AL      0100390207        00161594  Bay Minette CCD
#> 6           AL      0100390846        00165650       Daphne CCD
#>   functional_status  land_area water_area land_area_sq_mi water_area_sq_mi
#> 1                 S  478160386   13912232         184.619            5.372
#> 2                 S  386871321    1596305         149.372            0.616
#> 3                 S  292756921     516153         113.034            0.199
#> 4                 S  381826065    9719579         147.424            3.753
#> 5                 S 1338292029   27613551         516.717           10.662
#> 6                 S  297343727  142430774         114.805           54.993
#>   county_sub_lat county_sub_long
#> 1       32.45741       -86.72900
#> 2       32.60614       -86.74899
#> 3       32.63852       -86.51487
#> 4       32.47982       -86.50648
#> 5       30.80966       -87.70619
#> 6       30.66744       -87.90619