Exploring Wisconsin's Legislative Records

I wanted to explore the voting history of members of Wisconsin’s State House and Senate. Voting history is accessible for one member or one vote at a time on-line, but I couldn’t find any readily available summary data for download. So I thought I’d try scraping the data from the web.

To visualize the votes of the senators, I created a matrix of the votes of each senator on each issue (1 = YAY, 0 = Nay).

library(tidyverse)


smry <- dflong %>%
  mutate(
    sia = paste(Source, Session, Issue, Action, sep="-"),
  ) %>%
  group_by(sia, Representative) %>%
  summarise(mean.aye = mean(Vote=="Aye", na.rm=TRUE))

i.mean <- with(smry, tapply(mean.aye, sia, mean, na.rm=TRUE))
r.mean <- with(smry, tapply(mean.aye, Representative, mean, na.rm=TRUE))

library(stringdist)
one.match <- amatch(casefold(names(r.mean)), casefold(info$Last), maxDist=1)
name.match <- amatch(casefold(smry$Representative), casefold(info$Last), 
  maxDist=1)
smry$Representative <- info$Last[name.match]





missed.vote.count <- with(dflong, 
  tapply(is.na(Vote), Representative, sum))

r.ord <- order(r.mean, info$Party[one.match], missed.vote.count)
i.ord <- order(i.mean)

m <- with(smry, tapply(mean.aye, list(Representative, sia), mean))[
  r.ord, i.ord]

library(iheatmapr)
main_heatmap(m, name="Aye", colors=c("navy", "gold")) %>% 
  add_row_annotation(data.frame("Party"=info$Party[one.match][r.ord]),
    colors=list("Party"=c("blue", "red"))) %>% 
  add_row_barplot(
    x=missed.vote.count[r.ord],
    tracename="Missed votes", layout=list(title="Missed votes"))