Congress seats in Brazil

load libraries

library(tidyverse)
library(electionsBR)
library(ggparliament)
library(paletteer)

load data

d <- vote_mun_zone_fed(2018, uf = "ALL")

manipulating_1

eleitos <- c("ELEITO POR MÉDIA", "ELEITO POR QP", "ELEITO")

dep_ele <- d %>% 
  select(NOME_CANDIDATO, DESCRICAO_CARGO, SIGLA_PARTIDO, DESC_SIT_CAND_TOT) %>% 
  filter(DESC_SIT_CAND_TOT %in% eleitos, 
         DESCRICAO_CARGO == "Deputado Federal") %>% 
  distinct(NOME_CANDIDATO, .keep_all=T)

part_ele <- dep_ele %>% 
  group_by(SIGLA_PARTIDO) %>% 
  count() %>% 
  arrange(desc(n)) 

part_ele$SIGLA_PARTIDO <- recode(part_ele$SIGLA_PARTIDO, SOLIDARIEDADE = "SDD")

part_ele %>% 
  knitr::kable()

manipulating_2

seats <- ggparliament::parliament_data(election_data= part_ele,
                              type= "semicircle",
                              parl_rows=10,
                              party_seats=part_ele$n)

seats <- seats %>% 
  mutate(dest = 1, 
         rank = dense_rank(n),
         labels = paste(SIGLA_PARTIDO, paste0("(",n, ")")))

creating legend and labels

#dput(paletteer_d("pals::polychrome"))
#paletteer_d("pals::polychrome")
#dput(unique(seats$SIGLA_PARTIDO))

legend <- c("PT" = "#FF0000", 
            "PSL" = "#0000FF", 
            "PP" = "#87CEEB", 
            "PSD" = "#800080", 
            "MDB" = "#00FFFF", 
            "PR" = "#00FF00", 
            "PSB" = "#8B0000", 
            "PRB" = "#FFDEAD",  
            "DEM" = "#FF00FF",
            "PSDB" = "#3283FEFF", 
            "PDT" = "#FF6347", 
            "SDD" = "#B10DA1FF",  
            "PODE" = "#333300", 
            "PSOL" = "#FFD700",  
            "PTB" = "#B5EFB5FF", 
            "PC do B" = "#DC143C",
            "NOVO" = "#FF4500", 
            "PPS" = "#822E1CFF", 
            "PROS" = "#F8A19FFF", 
            "PSC" = "#BDCDFFFF", 
            "AVANTE" = "#325A9BFF", 
            "PHS" = "#1CFFCEFF", 
            "PATRI" = "#BC8F8F", 
            "PRP" = "#800000",
            "PV" = "#808000", 
            "PMN" = "#5A5156FF", 
            "PTC" = "hotpink", 
            "DC" = "gainsboro", 
            "PPL" = "#000000", 
            "REDE" = "#006400") 

labels <- unique(seats$labels)

plot graphic

ggplot(seats, aes(x,y, color=fct_reorder(SIGLA_PARTIDO, n, .desc=T)))+
  geom_parliament_seats(size=seats$rank/4)+
  scale_colour_manual("Parties (n. elected)", 
                      values = legend, 
                      labels = labels)+  
  theme_ggparliament(border=T)+
  theme(legend.position= "bottom",
        legend.background = element_blank(),
        legend.text = element_text(size = 12),
        legend.title = element_text(size=16),
        plot.title = element_text(hjust = 0.5, size = 20),
        plot.subtitle=element_text(hjust = 0.5, size = 14))+
  labs(title= "Chamber of Deputies in Brazil",
       subtitle= "Number of deputies elected by party")+
  guides(color = guide_legend(title.position="top", 
                              title.hjust = 0.5),
                              override.aes = list(size=8)) +
  annotate("text", label = "2018", x =0, y=0.3, size = 20)