brexit vote prediction

prediction

library(tidyverse)

brexit_bill <- data.frame(
  
  date = c("2019-01-15",
           "2019-03-12",
           "2019-03-29"),
                          
  votes_lost_by = c(230,
                    149,
                    58)
  )

# Convert text to Date format
brexit_bill$date <- as.Date(brexit_bill$date, format = "%Y-%m-%d")

# Calculate linear model: Date related to votes
model <- lm(date ~ votes_lost_by, data = brexit_bill)

# new data to generate predictions line - needs to included start point and end point
newdata <-
  data.frame(votes_lost_by = c(
    max(brexit_bill$votes_lost_by), # start point
    0 # end point - zero votes
  ))

# use the model to predict dates for new data
predicted_date <- predict(model, newdata)

# combine predicted dates and votes
predicted_data <- data.frame(
  pred_date = as.Date(predicted_date, origin = "1970-01-01"),
  pred_votes_lost_by = newdata$votes_lost_by
)

# plot observed
plot <- ggplot(brexit_bill, aes(date, votes_lost_by)) +
          geom_point() +
          ggtitle(paste('...If current trends continue, brexit vote will pass in Commons by', 
                        predicted_data$pred_date[2])) +
          xlab('Date')  +
          ylab('Votes needed') 

# add predicted to plot
plot +
  geom_line(aes(pred_date, pred_votes_lost_by), 
  # need to remove NAs because line is broken/disappears where NAs present
            predicted_data,
            linetype = 2, colour = "blue") +
  theme_bw()