hoc_attendance

# load the required libraries ---------------------------------------------

library(tidyverse)

# create the dataset of votes ---------------------------------------------

file_ext <- c(1997, 2001, 2005, 2010, 2015, 2017)

temp_list <- list()

for(i in 1:length(file_ext)){
        
        file <- read.delim(paste0("https://www.publicwhip.org.uk/data/votematrix-", file_ext[i], ".dat"), 
                           header = TRUE, fill = TRUE, sep = "\t", quote = "")

        last_mp <- length(file) - 1
        
        votes <- file %>% 
                pivot_longer(cols = 5:all_of(last_mp), 
                             names_to = "mpid", values_to = "vote") %>%
                mutate(term = file_ext[i]) %>% 
                select(term, date, voteno, vote)
                
        temp_list[[i]] <- votes
}

df <- as_tibble(do.call(rbind, temp_list))

# tidy the dataset --------------------------------------------------------

df_tidy <- df %>% 
        mutate(present = if_else(vote == -9, 0, 1),
               year = as.numeric(format(as.Date(date),"%Y")),
               month = as.numeric(format(as.Date(date), "%m")),
               day = as.numeric(format(as.Date(date), "%d"))) %>%
        filter(month == 6 & day < 15 | month < 6) %>% 
        group_by(date, year, voteno) %>% 
        summarise(attendance = case_when(term <= 2001 ~ sum(present) * 100 / 659,
                                         term == 2005 ~ sum(present) * 100 / 646,
                                         term > 2005 ~ sum(present) * 100 / 650))

# line plot ---------------------------------------------------------------

df_tidy %>% 
        group_by(year) %>% 
        summarise(mean_attendance = mean(attendance)) %>% 
        ggplot(aes(x = year, y = mean_attendance)) +
        geom_line(size = 1) +
        scale_y_continuous(labels = function(x) paste0(x, "%")) +
        labs(y = "Attendance to votes, \nJan to mid-June\n", x = "") +
        theme_minimal()

# density plot ------------------------------------------------------------

df_tidy %>% 
        mutate(category = case_when(year < 2020 ~ "1997-2019", 
                             year == 2020 ~ "2020",
                             year == 2021 ~ "2021")) %>% 
        ggplot(aes(x = attendance, color = category, group = factor(year))) +
        geom_density(size = 1, show.legend = FALSE) +
        stat_density(geom = "line", position="identity", size = 1) +
        scale_color_manual(name = "",
                           values = c("gray", "#F8766D", "#00BFC4")) +
        scale_x_continuous(labels = function(x) paste0(x, "%")) +
        labs(x = "\nAttendance to votes, Jan to mid-June", y = "Density\n") +
        theme_minimal() +
        theme(legend.position = "bottom")