Nothing
## ----setup, include = FALSE----------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
library(ggparliament)
library(dplyr)
library(ggplot2)
require(tidyr)
require(magrittr)
source("../R/parliament_data.R")
source("../R/geom_parliament_seats.R")
source("../R/geom_highlight_government.R")
source("../R/helper_funcs.R")
source("../R/draw_majoritythreshold.R")
source("../R/draw_partylabels.R")
source("../R/draw_majoritythreshold.R")
source("../R/draw_totalseats.R")
source("../R/theme_ggparliament.R")
load("../R/sysdata.rda")
## ------------------------------------------------------------------------
us_rep <- election_data %>%
filter(country == "USA" &
year == 2016 &
house == "Representatives")
head(us_rep)
## ------------------------------------------------------------------------
us_house_semicircle <- parliament_data(election_data = us_rep,
type = "semicircle",
parl_rows = 10,
party_seats = us_rep$seats)
head(us_house_semicircle)
## ---- fig.width=6, fig.height=4------------------------------------------
us <- ggplot(us_house_semicircle, aes(x = x, y = y, colour = party_short)) +
geom_parliament_seats() +
theme_ggparliament() +
labs(colour = NULL,
title = "United States Congress") +
scale_colour_manual(values = us_house_semicircle$colour,
limits = us_house_semicircle$party_short)
us
## ------------------------------------------------------------------------
australia <- election_data %>%
filter(country == "Australia" &
house == "Representatives" &
year == 2016)
australia_horseshoe <- parliament_data(election_data = australia,
party_seats = australia$seats,
parl_rows = 4,
type = "horseshoe")
## ----fig.width=4, fig.height=4-------------------------------------------
au <- ggplot(australia_horseshoe, aes(x, y, colour = party_short)) +
geom_parliament_seats() +
theme_ggparliament() +
labs(colour = NULL,
title = "Australian Parliament") +
scale_colour_manual(values = australia$colour,
limits = australia$party_short) +
theme(legend.position = 'bottom')
au
## ---- fig.height=6, fig.width = 6----------------------------------------
#get the data for the last election
uk_data <- election_data %>%
filter(country == "UK") %>%
filter(year == 2017) %>% #parliament_data() can be called in a dplyr chain.
parliament_data(election_data = .,
party_seats = .$seats,
#need to include grouping for opposing benches by definition
group = .$government,
parl_rows = 12,
type = "opposing_benches")
#plot it
uk <- ggplot(uk_data, aes(x, y, colour = party_short)) +
scale_colour_manual(values = uk_data$colour, limits = uk_data$party_short) +
geom_parliament_seats() +
theme_ggparliament()
uk
## ------------------------------------------------------------------------
russia_classroom <- election_data %>%
filter(country == "Russia" &
house == "Duma" &
year == 2016) %>%
parliament_data(election_data = .,
party_seats = .$seats,
parl_rows = 11,
type = "classroom")
## ----fig.width=4, fig.height=4-------------------------------------------
rus <- ggplot(russia_classroom, aes(x, y, colour = party_short)) +
geom_parliament_seats() +
theme_ggparliament() +
labs(
colour = NULL,
title = "Russian Duma") +
scale_colour_manual(
values = russia_classroom$colour,
limits = russia_classroom$party_short) +
theme(legend.position = "bottom")
rus
## ------------------------------------------------------------------------
russia_circle <- election_data %>%
filter(country == "Russia" &
house == "Duma" &
year == 2016) %>%
parliament_data(election_data = .,
party_seats = .$seats,
parl_rows = 11,
type = "circle")
## ----fig.width=4, fig.height=4-------------------------------------------
russia_circle_example <- ggplot(russia_circle, aes(x, y, colour = party_short)) +
geom_parliament_seats() +
theme_ggparliament() +
scale_colour_manual(
values = russia_circle$colour,
limits = russia_circle$party_short) +
labs(colour = NULL) +
theme(legend.position = "bottom")
russia_circle_example
## ------------------------------------------------------------------------
#a made up example of a vector of seats
seats <- c(rep("democrats", 40), rep("republicans", 30), rep("socialists", 20), rep("nationalists", 10))
made_up_layout <- parliament_data(election_data = NULL,
party_seats = as.numeric(table(seats)),
parl_rows = 4,
type = "semicircle")
made_up_layout$party = seats
plot <- ggplot(made_up_layout, aes(x, y, colour = party)) +
geom_parliament_seats() +
theme_ggparliament() +
labs(colour = NULL) +
theme(legend.position = "bottom")
plot
## ------------------------------------------------------------------------
house_of_reps <- data.frame(
party = c("Vacancies","Republicans", "Democrats", "Vacancies"),
seats = c(3, 236, 193, 3),
color = c("gray", "red", "blue", "gray")
)
house_of_reps <- house_of_reps %>%
mutate(party = as.character(party), color = as.character(color)) %>%
parliament_data(election_data = .,
parl_rows = 8,
party_seats = .$seats,
type = 'semicircle')
ggplot(data = house_of_reps) +
geom_parliament_seats(aes(x = x, y = y, color = party)) +
theme_ggparliament() +
scale_color_manual(values = house_of_reps$color,
limits = house_of_reps$party)
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