Getting Vote Data
The cartograms need data and the best way to do that is by obtaining roll call vote data from ProPublica via the roll_call() function. Data can be retrieved for any House or Senate vote by specificing the target vote parameters:
Their structures look the same and there is a print-method to make the console output easier on the eyes:
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 :Classes 'tbl_df', 'tbl' and 'data.frame': 100 obs. of 11 variables:
#> ..$ 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 x 11
#> bioguide_id role_id member_name sort_name party state_abbrev
#> * <chr> <int> <chr> <chr> <chr> <chr>
#> 1 A000360 526 Lamar Alexander Alexander R TN
#> 2 B001230 481 Tammy Baldwin Baldwin D WI
#> 3 B001261 498 John Barrasso Barrasso R WY
#> 4 B001267 561 Michael Bennet Bennet D CO
#> 5 B001277 535 Richard Blumenthal Blumenthal D CT
#> 6 B000575 547 Roy Blunt Blunt R MO
#> 7 B001288 507 Cory Booker Booker D NJ
#> 8 B001236 551 John Boozman Boozman R AR
#> 9 B000944 480 Sherrod Brown Brown D OH
#> 10 B001135 555 Richard M. Burr Burr R NC
#> # ... with 90 more rows, and 5 more variables: display_state_abbrev <chr>,
#> # district <chr>, position <chr>, dw_nominate <lgl>, pp_id <chr>
That data may be useful on its own (ouside of plotting).
Note, also, that ggplot2’s fortify() method uses the provided object class method for roll call objects to know how to extract the rectangular data necessary for plotting.
