README.md
In jaytimm/uspoliticalextras:
uspoliticalextras
US political open source data & resources – an R data package
A simple cache of US political data, collated from resources available
on Git Hub & elsewhere. Big thanks to the folks at MIT Election Data
and Science Lab, Civil
Services, the Daily
Kos &
tidycensus for maintaining and
making publically available these lovely resources!
-
Election returns for House races (by congressional district), Senate
races (by state) & presidential races (by state), made available by
the MIT Election Data and Science Lab.
1976 - 2018.
-
Election returns for presidential races by congressional district,
made available by the Daily Kos.
-
Lawmaker biographical details for the 115th & 116th congresses, made
available by Civil Services
project.
-
Equal-area shapefiles (as sf objects) for US states &
congressional districts, made available by the Daily
Kos.
-
Demographic profiles for congressional districts based on ACS 2017
1-year estimates; accessed via
tidycensus.
I have simply aggregated these sources as an R package out of
convenience, making minor adjustments in data structure and column names
to facilitate joining among data sets.
Installation
library(devtools)
devtools::install_github("jaytimm/uspoliticalextras")
library(uspoliticalextras)
Usage
Election returns
-
uspol_medsl_returns_house_cd
-
uspol_medsl_returns_senate_state
-
uspol_medsl_returns_pres_state
uspoliticalextras::uspol_medsl_returns_house_cd %>% select(year,GEOID, totalvotes:party)
## # A tibble: 9,556 x 9
## year GEOID totalvotes democrat independent other republican candidate party
## <dbl> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <chr>
## 1 1976 0101 157170 37.5 0 0 62.5 EDWARDS, … Repu…
## 2 1976 0102 156362 42.4 0 0 57.6 DICKINSON… Repu…
## 3 1976 0103 108048 99.0 0 1.03 0 NICHOLS, … Demo…
## 4 1976 0104 176022 80.4 0 0 19.6 BEVILL, T… Demo…
## 5 1976 0105 113560 100. 0 0 0 FLIPPO, R… Demo…
## 6 1976 0106 162518 42.7 0 0 56.7 BUCHANAN,… Repu…
## 7 1976 0107 110501 100 0 0 0 FLOWERS, … Demo…
## 8 1976 0200 118208 28.9 0 0 70.8 YOUNG, Do… Repu…
## 9 1976 0401 168119 40.7 0.62 1.35 57.3 RHODES, J… Repu…
## 10 1976 0402 182128 58.2 0 2.37 39.4 UDALL, Mo… Demo…
## # … with 9,546 more rows
uspol_dkos_returns_pres_cd
Lawmaker biographical data
Lawmaker biographies via Civil Service. I have cleaned things up some,
and eliminated some columns that are generally not useful to me. I have
also joined icpsr values to facilitate joining with output from the
Rvoteview package.
colnames(uspoliticalextras::uspol_csusa_house_bios)
## [1] "congress" "chamber" "icpsr" "state_fips"
## [5] "state" "state_abbrev" "district_code" "bioguide_id"
## [9] "party" "first_name" "last_name" "gender"
## [13] "ethnicity" "religion" "date_of_birth" "entered_office"
## [17] "term_end" "biography" "twitter_handle"
File structure:
uspoliticalextras::uspol_csusa_house_bios
## # A tibble: 870 x 19
## congress chamber icpsr state_fips state state_abbrev district_code
## <dbl> <chr> <int> <int> <chr> <chr> <int>
## 1 115 House 21376 1 Alab… AL 1
## 2 115 House 21192 1 Alab… AL 2
## 3 115 House 20301 1 Alab… AL 3
## 4 115 House 29701 1 Alab… AL 4
## 5 115 House 21193 1 Alab… AL 5
## 6 115 House 21500 1 Alab… AL 6
## 7 115 House 21102 1 Alab… AL 7
## 8 115 House 14066 2 Alas… AK 0
## 9 115 House 21739 4 Ariz… AZ 1
## 10 115 House 21501 4 Ariz… AZ 2
## # … with 860 more rows, and 12 more variables: bioguide_id <chr>, party <chr>,
## # first_name <chr>, last_name <chr>, gender <chr>, ethnicity <chr>,
## # religion <chr>, date_of_birth <date>, entered_office <date>,
## # term_end <date>, biography <chr>, twitter_handle <chr>
Equal-area polygons
names(uspol_dkos_equalarea_sf)
## [1] "tile_inner" "tile_outer" "hex_cds" "hex_states"
Congressional district demographic profiles
American Community Survey variables included in the profile include:
unique(uspoliticalextras::uspol_dems2017_house$variable)
## [1] "Median_HH_Income" "Per_BachelorsHigher"
## [3] "Per_BachelorsHigher_White" "Per_Black"
## [5] "Per_clf_unemployed" "Per_ForeignBorn"
## [7] "Per_Hispanic" "Per_LessHS"
## [9] "Per_LessHS_White" "Per_VotingAge"
## [11] "Per_White" "CD_AREA"
File structure:
uspoliticalextras::uspol_dems2017_house
## # A tibble: 5,232 x 6
## GEOID state_fips district_code state_abbrev variable estimate
## <chr> <int> <int> <chr> <chr> <dbl>
## 1 0101 1 1 AL Median_HH_Income 47984
## 2 0102 1 2 AL Median_HH_Income 46579
## 3 0103 1 3 AL Median_HH_Income 46484
## 4 0104 1 4 AL Median_HH_Income 43218
## 5 0105 1 5 AL Median_HH_Income 54707
## 6 0106 1 6 AL Median_HH_Income 65170
## 7 0107 1 7 AL Median_HH_Income 35988
## 8 0200 2 0 AK Median_HH_Income 73181
## 9 0401 4 1 AZ Median_HH_Income 50303
## 10 0402 4 2 AZ Median_HH_Income 53516
## # … with 5,222 more rows
jaytimm/uspoliticalextras documentation built on March 17, 2020, 3:44 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
uspoliticalextras
US political open source data & resources – an R data package
A simple cache of US political data, collated from resources available on Git Hub & elsewhere. Big thanks to the folks at MIT Election Data and Science Lab, Civil Services, the Daily Kos & tidycensus for maintaining and making publically available these lovely resources!
-
Election returns for House races (by congressional district), Senate races (by state) & presidential races (by state), made available by the MIT Election Data and Science Lab. 1976 - 2018.
-
Election returns for presidential races by congressional district, made available by the Daily Kos.
-
Lawmaker biographical details for the 115th & 116th congresses, made available by Civil Services project.
-
Equal-area shapefiles (as
sfobjects) for US states & congressional districts, made available by the Daily Kos. -
Demographic profiles for congressional districts based on ACS 2017 1-year estimates; accessed via tidycensus.
I have simply aggregated these sources as an R package out of convenience, making minor adjustments in data structure and column names to facilitate joining among data sets.
Installation
library(devtools)
devtools::install_github("jaytimm/uspoliticalextras")
library(uspoliticalextras)
Usage
Election returns
-
uspol_medsl_returns_house_cd -
uspol_medsl_returns_senate_state -
uspol_medsl_returns_pres_state
uspoliticalextras::uspol_medsl_returns_house_cd %>% select(year,GEOID, totalvotes:party)
## # A tibble: 9,556 x 9
## year GEOID totalvotes democrat independent other republican candidate party
## <dbl> <chr> <int> <dbl> <dbl> <dbl> <dbl> <chr> <chr>
## 1 1976 0101 157170 37.5 0 0 62.5 EDWARDS, … Repu…
## 2 1976 0102 156362 42.4 0 0 57.6 DICKINSON… Repu…
## 3 1976 0103 108048 99.0 0 1.03 0 NICHOLS, … Demo…
## 4 1976 0104 176022 80.4 0 0 19.6 BEVILL, T… Demo…
## 5 1976 0105 113560 100. 0 0 0 FLIPPO, R… Demo…
## 6 1976 0106 162518 42.7 0 0 56.7 BUCHANAN,… Repu…
## 7 1976 0107 110501 100 0 0 0 FLOWERS, … Demo…
## 8 1976 0200 118208 28.9 0 0 70.8 YOUNG, Do… Repu…
## 9 1976 0401 168119 40.7 0.62 1.35 57.3 RHODES, J… Repu…
## 10 1976 0402 182128 58.2 0 2.37 39.4 UDALL, Mo… Demo…
## # … with 9,546 more rows
uspol_dkos_returns_pres_cd
Lawmaker biographical data
Lawmaker biographies via Civil Service. I have cleaned things up some,
and eliminated some columns that are generally not useful to me. I have
also joined icpsr values to facilitate joining with output from the
Rvoteview package.
colnames(uspoliticalextras::uspol_csusa_house_bios)
## [1] "congress" "chamber" "icpsr" "state_fips"
## [5] "state" "state_abbrev" "district_code" "bioguide_id"
## [9] "party" "first_name" "last_name" "gender"
## [13] "ethnicity" "religion" "date_of_birth" "entered_office"
## [17] "term_end" "biography" "twitter_handle"
File structure:
uspoliticalextras::uspol_csusa_house_bios
## # A tibble: 870 x 19
## congress chamber icpsr state_fips state state_abbrev district_code
## <dbl> <chr> <int> <int> <chr> <chr> <int>
## 1 115 House 21376 1 Alab… AL 1
## 2 115 House 21192 1 Alab… AL 2
## 3 115 House 20301 1 Alab… AL 3
## 4 115 House 29701 1 Alab… AL 4
## 5 115 House 21193 1 Alab… AL 5
## 6 115 House 21500 1 Alab… AL 6
## 7 115 House 21102 1 Alab… AL 7
## 8 115 House 14066 2 Alas… AK 0
## 9 115 House 21739 4 Ariz… AZ 1
## 10 115 House 21501 4 Ariz… AZ 2
## # … with 860 more rows, and 12 more variables: bioguide_id <chr>, party <chr>,
## # first_name <chr>, last_name <chr>, gender <chr>, ethnicity <chr>,
## # religion <chr>, date_of_birth <date>, entered_office <date>,
## # term_end <date>, biography <chr>, twitter_handle <chr>
Equal-area polygons
names(uspol_dkos_equalarea_sf)
## [1] "tile_inner" "tile_outer" "hex_cds" "hex_states"
Congressional district demographic profiles
American Community Survey variables included in the profile include:
unique(uspoliticalextras::uspol_dems2017_house$variable)
## [1] "Median_HH_Income" "Per_BachelorsHigher"
## [3] "Per_BachelorsHigher_White" "Per_Black"
## [5] "Per_clf_unemployed" "Per_ForeignBorn"
## [7] "Per_Hispanic" "Per_LessHS"
## [9] "Per_LessHS_White" "Per_VotingAge"
## [11] "Per_White" "CD_AREA"
File structure:
uspoliticalextras::uspol_dems2017_house
## # A tibble: 5,232 x 6
## GEOID state_fips district_code state_abbrev variable estimate
## <chr> <int> <int> <chr> <chr> <dbl>
## 1 0101 1 1 AL Median_HH_Income 47984
## 2 0102 1 2 AL Median_HH_Income 46579
## 3 0103 1 3 AL Median_HH_Income 46484
## 4 0104 1 4 AL Median_HH_Income 43218
## 5 0105 1 5 AL Median_HH_Income 54707
## 6 0106 1 6 AL Median_HH_Income 65170
## 7 0107 1 7 AL Median_HH_Income 35988
## 8 0200 2 0 AK Median_HH_Income 73181
## 9 0401 4 1 AZ Median_HH_Income 50303
## 10 0402 4 2 AZ Median_HH_Income 53516
## # … with 5,222 more rows
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