In jaytimm/wnomadds:

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "##",
  fig.path =  "figure-markdown_github/")

wnomadds

A simple collection of functions based on the wnominate package.

library(wnomadds)#devtools::install_github("jaytimm/wnomadds")
library(nmlegisdatr)#devtools::install_github("jaytimm/nmlegisdatr")

library(tidyverse)
library(wnominate)
library(pscl)

Prepare data & run model

datFile <- nmlegisdatr::nml_rollcall  %>%
  filter(Chamber =='House' & !grepl('^LT', Representative)) %>%
  dplyr::select(Representative, Bill_ID, Rep_Vote) %>%
  spread(key= Bill_ID, value = Rep_Vote)

datRC <- pscl::rollcall(datFile [,-1], 
                        yea='Yea',
                        nay='Nay',
                        missing=c('Excused', 'Absent', 'Rec'),
                        vote.names = colnames(datFile)[2:ncol(datFile)], 
                        legis.names = datFile$Representative)

Swap yea/nay to 1, 6, 9

datRC$votes [datRC$votes == 'Excused' | datRC$votes == 'Absent' | datRC$votes == 'Rec'] <- 9
datRC$votes [datRC$votes == 'Yea'] <- 1
datRC$votes [datRC$votes == 'Nay'] <- 6

resultd2 <- wnominate::wnominate (datRC, 
                       ubeta=15, 
                       uweights=0.5, 
                       dims=2, 
                       minvotes=20,
                       lop=0.025,trials=3, 
                       polarity=c(1,1),
                       verbose=FALSE)

Plot two-dimensional model

row.names(resultd2$rollcalls) <- colnames(datFile)[2:ncol(datFile)]

Extract legislators from nom object. And add legislator details from nmlegisdatr.

house_data <- resultd2$legislators %>% 
  bind_cols(nml_legislators %>% 
              filter(Chamber == 'House' & !grepl('^LT', Representative)))

library(ggthemes)

house_data%>%
  ggplot(aes(x=coord1D, y=coord2D)) +
  geom_point(aes(color = Party),
             size= 2.5, 
             shape= 17) +
  scale_colour_stata() + 
  #theme_fivethirtyeight() +
  theme(legend.position = 'bottom', 
        plot.title = element_text(size=13), 
        axis.title = element_text(size=10)) +
  geom_text(aes(label=Representative), 
            size=2.5, 
            check_overlap = TRUE, 
            hjust = 0, 
            nudge_x = 0.03)+
  labs(title="New Mexico 53rd House Roll Call - 2nd Session") +
  coord_equal(ratio=1)

Using `wnomadds`

Demonstrate how to extract cutting lines using wnom_adds.

with_cuts <- wnomadds::wnom_adds_get_cutlines(resultd2, rollcall_obj = datRC)
#Suppress warnings

The function returns cutline coordinates along with vote polarity.

head(with_cuts)

Plot legislators with cutting lines.

ggplot () + 
  scale_colour_stata() + 
  theme_fivethirtyeight() +
  theme(plot.title = element_text(size=13),
        legend.position = 'bottom') +
  geom_point(data=house_data, 
               aes(x=coord1D, y=coord2D,color = Party),
               size= 2.5, 
               shape= 17) +
  geom_segment(data=with_cuts, 
               aes(x = x_1, y = y_1, xend = x_2, yend = y_2)) +
  geom_segment(data=with_cuts, 
               aes(x = x_2, y = y_2, xend = x_2a, yend = y_2a), 
               arrow = arrow(length = unit(0.2,"cm"))) +
  geom_segment(data=with_cuts, 
               aes(x = x_1, y = y_1, xend = x_1a, yend = y_1a), 
               arrow = arrow(length = unit(0.2,"cm")))+
  geom_text(data=with_cuts, 
               aes(x = x_1a, y = y_1a, label = Bill_ID), 
               size=2.5, 
               nudge_y = 0.03,
               check_overlap = TRUE) +
  coord_fixed(ratio=1) + 
  labs(title="Cutting lines for New Mexico's 53rd Lower Chamber - 2nd Session")

Cutting line selections.

select_cuts <- c('HB0032')

sub <- nmlegisdatr::nml_rollcall %>%
  filter(Bill_ID %in% select_cuts) %>%
  inner_join(house_data)

cut_sub <- subset(with_cuts, Bill_ID %in% select_cuts)

sub %>%
ggplot(aes(x=coord1D, y=coord2D)) +
  geom_point(aes(color = Party_Vote, shape= Party_Vote, fill = Party_Vote),
             size= 2.5) +
  nmlegisdatr::nml_color_vote() +
  nmlegisdatr::nml_fill_vote() +
  nmlegisdatr::nml_shape_vote()+
  theme(legend.position = 'bottom', 
        plot.title = element_text(size=13), 
        axis.title = element_text(size=10)) +
  geom_text(aes(label=Representative), 
            size=2.5, 
            check_overlap = TRUE, 
            hjust = 0, 
            nudge_x = 0.03)+
  geom_segment(data=cut_sub, 
               aes(x = x_1, y = y_1, xend = x_2, yend = y_2)) +
  geom_segment(data=cut_sub, 
               aes(x = x_2, y = y_2, xend = x_2a, yend = y_2a), 
               arrow = arrow(length = unit(0.2,"cm"))) +
  geom_segment(data=cut_sub, 
               aes(x = x_1, y = y_1, xend = x_1a, yend = y_1a), 
               arrow = arrow(length = unit(0.2,"cm")))+
  geom_text(data=cut_sub, 
               aes(x = x_1a, y = y_1a, label = Bill_ID), 
               size=2.5, 
               nudge_y = 0.03,
               check_overlap = TRUE) +
  labs(title="New Mexico 53rd House Roll Call - 2nd Session") +
  coord_equal(ratio=1)

View multiple roll calls.

select_cuts <- c('HB0032', 'HB0064', 'HB0100', 'HB0049', 'HB0325', 'HJM010',
                 'HM106', 'SB0079')

sub <- nmlegisdatr::nml_rollcall %>%
  filter(Bill_ID %in% select_cuts) %>%
  inner_join(house_data)

cut_sub <- subset(with_cuts, Bill_ID %in% select_cuts)

sub %>%
ggplot(aes(x=coord1D, y=coord2D)) +
  geom_point(aes(color = Party_Vote, shape= Party_Vote, fill = Party_Vote),
             size= 1.5) +
  nmlegisdatr::nml_color_vote() +
  nmlegisdatr::nml_fill_vote() +
  nmlegisdatr::nml_shape_vote()+
  theme(legend.position = 'bottom', 
        plot.title = element_text(size=13), 
        axis.title = element_text(size=10)) +
  geom_text(aes(label=Representative), 
            size=1.5, 
            check_overlap = TRUE, 
            hjust = 0, 
            nudge_x = 0.03)+
  geom_segment(data=cut_sub, 
               aes(x = x_1, y = y_1, xend = x_2, yend = y_2)) +
  geom_segment(data=cut_sub, 
               aes(x = x_2, y = y_2, xend = x_2a, yend = y_2a), 
               arrow = arrow(length = unit(0.2,"cm"))) +
  geom_segment(data=cut_sub, 
               aes(x = x_1, y = y_1, xend = x_1a, yend = y_1a), 
               arrow = arrow(length = unit(0.2,"cm")))+
  geom_text(data=cut_sub, 
               aes(x = x_1a, y = y_1a, label = Bill_ID), 
               size=2.5, 
               nudge_y = 0.03,
               check_overlap = TRUE) +
  labs(title="New Mexico 53rd House Roll Call - 2nd Session") +
  coord_equal(ratio=1)+
  facet_wrap(~Bill_ID, ncol = 4)
  #