Code to generate the tipping-point index from our model's simulations

tipping-point_states.R

library(pbapply)
library(tidyverse)

mod <- read_csv('~/Downloads/output/site_data/electoral_college_simulations.csv')
mod <- mod %>% gather(state,vote,4:ncol(.))
evs <- read_csv('data/prior/state_evs.csv')
mod <- mod %>% left_join(evs)

tp <- pblapply(1:max(mod$draw),
               cl = 12,
               function(x){
                 if(isTRUE(mod[mod$draw==x,]$dem_ev>=270)){
                   mod[mod$draw==x,] %>%
                     arrange(desc(vote)) %>% 
                     mutate(cum_ev = cumsum(ev)) %>%
                     filter(cum_ev >= 270) %>%
                     filter(row_number() == 1) %>% 
                     pull(state)
                 }else{
                   mod[mod$draw==x,] %>%
                     arrange(vote) %>% 
                     mutate(cum_ev = cumsum(ev)) %>%
                     filter(cum_ev >= 270) %>%
                     filter(row_number() == 1) %>% 
                     pull(state)
                 }
                 
               }) %>% 
  do.call('c',.) 

txt <- enframe(prop.table(table(tp)), 'state', 'chance') %>%
  arrange(desc(chance)) %>%
  apply(.,
        MARGIN = 1,
        FUN=function(x){
          trimws(sprintf('%s: %s%%', trimws(x[['state']]), trimws(round(as.numeric(x[['chance']])*100))))
        })

sprintf("Here is our model's \"tipping-point\" index, which shows the percentage of the time we think each state will provide the winner with their 270th electoral vote: 

%s


        
https://projects.economist.com/us-2020-forecast/president",
        paste0(txt,collapse = '\n')) %>% cat

beepr::beep(2)