Get stats on minority government from ParlGov

minority_report.R

library(tidyverse)
### Make sure to download files from www.parlgov.org!

elec <- read.csv("view_election.csv")
cab <- read.csv("view_cabinet.csv")
party <- read.csv("view_party.csv")

### Date
cab$start_date <- as.Date(cab$start_date)

### Filter to post-1992 cabinets
cab <- subset(cab, start_date > as.Date("1992-01-01"))

nUnique <- length(unique(cab$cabinet_id))
### For each cabinet, get whether minority or not
cab <- cab %>% 
	group_by(cabinet_id) %>% 
	mutate(cabinet_seats = sum(seats[which(cabinet_party == 1)], na.rm = TRUE),
		isMinority = cabinet_seats < 0.5 * election_seats_total)

### What proportion of cabinets are minority cabinets?
min_pct <- cab %>% 
	distinct(cabinet_id, isMinority) %>% 
	ungroup() %>% 
	summarize(percentage = mean(isMinority))

min_pct2 <- cab %>% 
	filter(caretaker == 0) %>% 
	distinct(cabinet_id, isMinority) %>% 
	ungroup() %>% 
	summarize(percentage = mean(isMinority))

### Of these, what proportion are single party?
min_nparties <- cab %>% 
	filter(isMinority == TRUE & cabinet_party == 1) %>%
	distinct(cabinet_id, party_id) %>% 
	group_by(cabinet_id) %>% 
	summarize(nParties = length(unique(party_id))) %>% 
	group_by(nParties) %>% 
	summarize(n = n()) %>% 
	mutate(freq = n / sum(n))

### What about their duration?
### We need first to create a duration variable
### See https://gist.github.com/hdigital/9bdca6a2f605a27d5d28ca90b7752759
cab_dur <- cab %>%
  mutate(start_date = as.Date(start_date)) %>% 
  select(cabinet_id, previous_cabinet_id, start_date) %>%
  distinct

cab_dur <- cab_dur %>%
  inner_join(cab_dur, by = c('cabinet_id' = 'previous_cabinet_id')) %>% 
  mutate(duration = start_date.y - start_date.x) %>% 
  select(cabinet_id, duration)

cab <- cab %>% left_join(cab_dur)

min_durat <- cab %>% 
	distinct(isMinority, cabinet_id, duration) %>% 
	group_by(isMinority) %>% 
	summarize(n = n(),
		meanDurat = mean(duration, na.rm = TRUE),
		OverFour = sum(duration > 365.25 * 4, na.rm = TRUE))