U.S. House and Senate Voting Cartogram Generators
‘ProPublica’ https://projects.propublica.org/represent/ makes United States Congress member votes available and has developed their own unique cartogram to visually represent this data as has ‘GovTrack’ <URL_AT_SOME_POINT> . Tools are provided to retrieve voting data, prepare voting data for plotting with ‘ggplot2’, create vote cartograms and theme them.
Ref: (these are replicated below)
- https://projects.propublica.org/represent/votes/115/senate/1/110
- https://projects.propublica.org/represent/votes/115/house/1/256
- https://www.govtrack.us/congress/votes/115-2017/h256
You can grab the results of a roll call vote (House or Senate) with
roll_call(). It returns a list with a ton of information that you
can use outside this package. One element of that list is the
data.frame of vote results. You can pass in the entire object to
either _carto() function and it’ll “fortify” it before shunting it off
to ggplot2. Try to cache this data (I do, below, in R markdown chunk) as
you’re ticking credits off of ProPublica’s monthly free S3 allotment
each call. Consider donating to them if you’re too lazy to cache the
data).
House cartogram generatorParam bulletproofing (param checking, et al)Add in ability to retrieve votes from ProPublica.Make avoteogramthemeGovTrack Senate cartogram polygons(this is pretty much covered inggparliamentsince GT only has the seat view for the Senate)“Independent” colors for “not voting” & “present”Vignettehtmlwidgetversion
The following functions are implemented:
house_carto: Produce a ProPublica- or GovTrack-style House roll call vote cartogramsenate_carto: Produce a Senate cartogramroll_call: Get Voting Record for House or Senate By Number, Session & Roll Call Number
Helpers:
theme_voteogram: voteogram ggplot2 themeprint.pprc: Better default ‘print’ function forroll_call()(pprc) objectsfortify.pprc: In case you want to use the voting data frame from aroll_call()(pprc) object in your own plots and forget to just$votesit out. #helping
remotes::install_github("hrbrmstr/voteogram")library(voteogram)
library(hrbrthemes)
library(ggplot2)
# current verison
packageVersion("voteogram")## [1] '0.3.2'
sen <- roll_call("senate", 115, 1, 110)
rep <- roll_call("house", 115, 1, 256)str(sen)## List of 29
## $ vote_id : chr "S_115_1_110"
## $ chamber : chr "Senate"
## $ year : int 2017
## $ congress : chr "115"
## $ session : chr "1"
## $ roll_call : int 110
## $ needed_to_pass : int 51
## $ date_of_vote : chr "April 6, 2017"
## $ time_of_vote : chr "12:35 PM"
## $ result : chr "Cloture Motion Agreed to"
## $ vote_type : chr "1/2"
## $ question : chr "On the Cloture Motion"
## $ description : chr "Neil M. Gorsuch, of Colorado, to be an Associate Justice of the Supreme Court of the United States"
## $ nyt_title : chr "On the Cloture Motion"
## $ total_yes : int 55
## $ total_no : int 45
## $ total_not_voting : int 0
## $ gop_yes : int 52
## $ gop_no : int 0
## $ gop_not_voting : int 0
## $ dem_yes : int 3
## $ dem_no : int 43
## $ dem_not_voting : int 0
## $ ind_yes : int 0
## $ ind_no : int 2
## $ ind_not_voting : int 0
## $ dem_majority_position: chr "No"
## $ gop_majority_position: chr "Yes"
## $ votes : tibble [100 × 11] (S3: tbl_df/tbl/data.frame)
## ..$ bioguide_id : chr [1:100] "A000360" "B001230" "B001261" "B001267" ...
## ..$ role_id : int [1:100] 526 481 498 561 535 547 507 551 480 555 ...
## ..$ member_name : chr [1:100] "Lamar Alexander" "Tammy Baldwin" "John Barrasso" "Michael Bennet" ...
## ..$ sort_name : chr [1:100] "Alexander" "Baldwin" "Barrasso" "Bennet" ...
## ..$ party : chr [1:100] "R" "D" "R" "D" ...
## ..$ state_abbrev : chr [1:100] "TN" "WI" "WY" "CO" ...
## ..$ display_state_abbrev: chr [1:100] "Tenn." "Wis." "Wyo." "Colo." ...
## ..$ district : chr [1:100] "2" "1" "1" "1" ...
## ..$ position : chr [1:100] "Yes" "No" "Yes" "No" ...
## ..$ dw_nominate : logi [1:100] NA NA NA NA NA NA ...
## ..$ pp_id : chr [1:100] "TN" "WI" "WY" "CO" ...
## - attr(*, "class")= chr [1:2] "pprc" "list"
sen$votes## # A tibble: 100 × 11
## bioguide_id role_id member_name sort_name party state_abbrev display_state_ab…¹ distr…² posit…³ dw_no…⁴ pp_id
## <chr> <int> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <lgl> <chr>
## 1 A000360 526 Lamar Alexander Alexander R TN Tenn. 2 Yes NA TN
## 2 B001230 481 Tammy Baldwin Baldwin D WI Wis. 1 No NA WI
## 3 B001261 498 John Barrasso Barrasso R WY Wyo. 1 Yes NA WY
## 4 B001267 561 Michael Bennet Bennet D CO Colo. 1 No NA CO
## 5 B001277 535 Richard Blumenthal Blumenthal D CT Conn. 2 No NA CT
## 6 B000575 547 Roy Blunt Blunt R MO Mo. 2 Yes NA MO
## 7 B001288 507 Cory Booker Booker D NJ N.J. 2 No NA NJ
## 8 B001236 551 John Boozman Boozman R AR Ark. 1 Yes NA AR
## 9 B000944 480 Sherrod Brown Brown D OH Ohio 1 No NA OH
## 10 B001135 555 Richard M. Burr Burr R NC N.C. 1 Yes NA NC
## # … with 90 more rows, and abbreviated variable names ¹display_state_abbrev, ²district, ³position, ⁴dw_nominate
str(rep)## List of 29
## $ vote_id : chr "H_115_1_256"
## $ chamber : chr "House"
## $ year : int 2017
## $ congress : chr "115"
## $ session : chr "1"
## $ roll_call : int 256
## $ needed_to_pass : int 216
## $ date_of_vote : chr "May 4, 2017"
## $ time_of_vote : chr "02:18 PM"
## $ result : chr "Passed"
## $ vote_type : chr "RECORDED VOTE"
## $ question : chr "On Passage"
## $ description : chr "American Health Care Act"
## $ nyt_title : chr "On Passage"
## $ total_yes : int 217
## $ total_no : int 213
## $ total_not_voting : int 1
## $ gop_yes : int 217
## $ gop_no : int 20
## $ gop_not_voting : int 1
## $ dem_yes : int 0
## $ dem_no : int 193
## $ dem_not_voting : int 0
## $ ind_yes : int 0
## $ ind_no : int 0
## $ ind_not_voting : int 0
## $ dem_majority_position: chr "No"
## $ gop_majority_position: chr "Yes"
## $ votes : tibble [435 × 11] (S3: tbl_df/tbl/data.frame)
## ..$ bioguide_id : chr [1:435] "A000374" "A000370" "A000055" "A000371" ...
## ..$ role_id : int [1:435] 274 294 224 427 268 131 388 320 590 206 ...
## ..$ member_name : chr [1:435] "Ralph Abraham" "Alma Adams" "Robert B. Aderholt" "Pete Aguilar" ...
## ..$ sort_name : chr [1:435] "Abraham" "Adams" "Aderholt" "Aguilar" ...
## ..$ party : chr [1:435] "R" "D" "R" "D" ...
## ..$ state_abbrev : chr [1:435] "LA" "NC" "AL" "CA" ...
## ..$ display_state_abbrev: chr [1:435] "La." "N.C." "Ala." "Calif." ...
## ..$ district : int [1:435] 5 12 4 31 12 3 2 19 36 2 ...
## ..$ position : chr [1:435] "Yes" "No" "Yes" "No" ...
## ..$ dw_nominate : logi [1:435] NA NA NA NA NA NA ...
## ..$ pp_id : chr [1:435] "LA_5" "NC_12" "AL_4" "CA_31" ...
## - attr(*, "class")= chr [1:2] "pprc" "list"
fortify(rep)## # A tibble: 435 × 11
## bioguide_id role_id member_name sort_name party state_abbrev display_state_abb…¹ distr…² posit…³ dw_no…⁴ pp_id
## <chr> <int> <chr> <chr> <chr> <chr> <chr> <int> <chr> <lgl> <chr>
## 1 A000374 274 Ralph Abraham Abraham R LA La. 5 Yes NA LA_5
## 2 A000370 294 Alma Adams Adams D NC N.C. 12 No NA NC_12
## 3 A000055 224 Robert B. Aderholt Aderholt R AL Ala. 4 Yes NA AL_4
## 4 A000371 427 Pete Aguilar Aguilar D CA Calif. 31 No NA CA_31
## 5 A000372 268 Rick Allen Allen R GA Ga. 12 Yes NA GA_12
## 6 A000367 131 Justin Amash Amash R MI Mich. 3 Yes NA MI_3
## 7 A000369 388 Mark Amodei Amodei R NV Nev. 2 Yes NA NV_2
## 8 A000375 320 Jodey Arrington Arrington R TX Texas 19 Yes NA TX_19
## 9 B001291 590 Brian Babin Babin R TX Texas 36 Yes NA TX_36
## 10 B001298 206 Don Bacon Bacon R NE Neb. 2 Yes NA NE_2
## # … with 425 more rows, and abbreviated variable names ¹display_state_abbrev, ²district, ³position, ⁴dw_nominate
senate_carto(sen) +
labs(title="Senate Vote 110 - Invokes Cloture on Neil Gorsuch Nomination") +
theme_ipsum_rc(plot_title_size = 24) +
theme_voteogram()
house_carto(rep, pp_square=TRUE) +
labs(x=NULL, y=NULL,
title="House Vote 256 - Passes American Health Care Act,\nRepealing Obamacare") +
theme_ipsum_rc(plot_title_size = 24) +
theme_voteogram()
house_carto(rep, pp_square=FALSE) +
labs(x=NULL, y=NULL,
title="House Vote 256 - Passes American Health Care Act,\nRepealing Obamacare") +
theme_ipsum_rc(plot_title_size = 24) +
theme_voteogram()
house_carto(rep, "gt") +
labs(x=NULL, y=NULL,
title="House Vote 256 - Passes American Health Care Act,\nRepealing Obamacare") +
theme_ipsum_rc(plot_title_size = 24) +
theme_voteogram()
They can be shrunk down well (though that means annotating them in some other way):
senate_carto(sen) + theme_voteogram(legend=FALSE)
house_carto(rep) + theme_voteogram(legend=FALSE)
house_carto(rep, pp_square=TRUE) + theme_voteogram(legend=FALSE)
library(voteogram)
library(testthat)
date()## [1] "Wed Mar 8 06:36:49 2023"
test_dir("tests/")## ✔ | F W S OK | Context
## ⠏ | 0 | all [ FAIL 0 | WARN 0 | SKIP 0 | PASS 7 ]
##
## ══ Results ═════════════════════════════════════════════════════════════════════════════════════════════════════════════
## Duration: 0.8 s
##
## [ FAIL 0 | WARN 0 | SKIP 0 | PASS 0 ]
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