Improving Plot Information via Plot Order

The provided example data for elections is in order of country, year, winning power, and then seats. However, this need not be so. It's easy to imagine downloading data in (e.g.) alphabetical order

unformatted_data <- election_data %>%
  filter(country == "Germany" & year == "2017") %>%
  arrange(party_long)
head(unformatted_data)
#>   year country     house                        party_long party_short
#> 1 2017 Germany Bundestag            Alliance 90/The Greens       GRUNE
#> 2 2017 Germany Bundestag           Alternative for Germany         AFD
#> 3 2017 Germany Bundestag        Christian Democratic Union         CDU
#> 4 2017 Germany Bundestag Christian Social Union in Bavaria         CSU
#> 5 2017 Germany Bundestag             Free Democratic Party         FDP
#> 6 2017 Germany Bundestag           Social Democratic Party         SDP
#>   seats government  colour
#> 1    67          0 #64A12D
#> 2    94          1 #009EE0
#> 3   200          1 #000000
#> 4    46          0 #008AC5
#> 5    80          1 #FFED00
#> 6   153          0 #EB001F

One simple way to deal with this is to arrange the data before piping it through ggparliament. For instance, in the order I prefer (government on the left, starting with the largest party):

formatted_data <- unformatted_data %>%
  arrange(-government, -seats)
formatted_parl_data <- formatted_data %>%
  parliament_data(.,
                  parl_rows = 12,
                  party_seats = .$seats,
                  type = "semicircle")
german_parliament <- ggplot(formatted_parl_data, aes(x, y, colour = party_short)) +
  geom_parliament_seats() +
  geom_highlight_government(government == 1) + 
  draw_majoritythreshold(n = 355, label = FALSE, type = "semicircle") + 
  labs(colour="Party", 
       title="Germany 2017 Election Results") + 
  theme_ggparliament() +
  scale_colour_manual(values = formatted_parl_data$colour, 
                      limits = formatted_parl_data$party_short)
german_parliament

However, for whatever reason this might not be possible, or just undesirable. To deal with this, parliament_data also includes the ability to order the data for plotting using plot_order. If this is left as NULL, no ordering takes place.

german_parliament <- unformatted_data %>%
  parliament_data(.,
                  parl_rows = 12,
                  party_seats = .$seats,
                  plot_order = .$seats,
                  type = "semicircle") %>%
  ggplot(., aes(x, y, colour = party_short)) +
  geom_parliament_seats() +
  geom_highlight_government(government == 1) + 
  draw_majoritythreshold(n = 355, label = FALSE, type = "semicircle") + 
  labs(colour="Party", 
       title="Germany 2017 Election Results Arranged by Seats per Party") + 
  theme_ggparliament() +
  scale_colour_manual(values = unformatted_data$colour, 
                      limits = unformatted_data$party_short)
german_parliament

Given that government is a binary variable, the simplest way to order as in the first plot is to multiple this by the number of seats, i.e.:

german_parliament <- unformatted_data %>%
  parliament_data(.,
                  parl_rows = 12,
                  party_seats = .$seats,
                  plot_order = .$seats * .$government,
                  type = "semicircle") %>%
  ggplot(., aes(x, y, colour = party_short)) +
  geom_parliament_seats() +
  geom_highlight_government(government == 1) + 
  draw_majoritythreshold(n = 355, label = FALSE, type = "semicircle") + 
  labs(colour="Party", 
       title="Germany 2017 Election Results Arranged by Seats per Party") + 
  theme_ggparliament() +
  scale_colour_manual(values = unformatted_data$colour, 
                      limits = unformatted_data$party_short)
german_parliament