Ggplot kullanılarak bir yığılmış çubuk çizimde birden çok renk kümesi

Question

Bir belediyenin içindeki partiler arasında birkaç yıl boyunca (= x ekseni) konsey koltuklarının (= y ekseni) dağılımını gösteren yığılmış bir çubuk grafiği oluşturdum. Kullanılan kod ve bazı veriler aşağıdadır. Maalesef grafiğin yayınlanması için henüz yeterli puanım yok. Farklı partiler, farklı politik yönelimler için bir kategori olarak “ideoloji” adı verilen bir değişkenle de ilişkilidir (“ilerici”, “ılımlı”, “muhafazakar”).

Renkleri, örn. muhafazakâr partilerin farklı türde mavileri vardır; tüm ilerici partiler farklı yeşil türleri; ve tüm ılımlı partiler örn. farklı kırmızı çeşitleri;

İdeolojinin değişkeni aynı veri çerçevesindedir (y).

Bu değişiklik nasıl yapılır? Renk = faktör (ideoloji) ve grup = ideolojiyi zaten denedim ama boşuna. Ayrıca bu ilgili giriş Using a pre-defined color palette in ggplot farkındayım, ancak özellikle benim sorunumda değil.

Çok teşekkürler.

Kullanılan komut:

municipality.plot <- ggplot(y, aes(x=as.factor(year), y=seats, fill=party, color=party)) + 
     geom_bar(bandwidth=1, stat="identity", group="party", position="fill") + 
     labs(x="year", y="% of seats for municipality") 

Örnek veri:

year district.id               party seats ideology 
1 2012   127     Stranka Pravde I Razvoja Bosne I Hercegovine  1  p 
2 2012   127        Savez Za Bolju Buducnost (SBB)  3  p 
3 2008   127        Stranka Demokratske Akcije (SDA) 13  p 
4 2004   127        Stranka Demokratske Akcije (SDA) 14  p 
5 2008   127       Hrvatska Demokratska Zajednica (HDZ)  1  c 
6 2008   127     Stranka Pravde I Razvoja Bosne I Hercegovine  1  p 
7 2012   127      Stranka Za Bosnu I Hercegovinu (SzBiH)  4  p 
8 2000   127        Socijaldemokratska Partija (SDP)  8  m 
9 2012   127      Narodna Stranka Radom Za Boljitak (NSRzB)  2  m 
10 2012   127       Socijaldemokratska Unija Bih (SDU)  1  p 
11 2000   127           Koalicija - SDA, SBiH 15  p 
12 2008   127        Socijaldemokratska Partija (SDP)  5  m 
13 2008   127      Narodna Stranka Radom Za Boljitak (NSRzB)  1  m 
14 2008   127           Koalicija - LDS, SDU  2  m 
15 2000   127 Lgk-liberalno-gradanska Koalicija Bih (liberali Bih, Gds Bih)  1  m 
16 2000   127        Nova Hrvatska Inicijativa (NHI)  1  c 
17 1997   127        Socijaldemokratska Partija (SDP)  3  m 
18 2012   127        Socijaldemokratska Partija (SDP)  6  m 
19 2004   127      Stranka Za Bosnu I Hercegovinu (SzBiH)  5  p 
20 1997   127     Bosanskohercegovacka Patriotska Stranka (BPS)  9  p 
21 2000   127     Bosanskohercegovacka Patriotska Stranka (BPS)  3  p 
22 2008   127      Stranka Za Bosnu I Hercegovinu (SzBiH)  4  p 
23 1997   127       Hrvatska Demokratska Zajednica (HDZ)  5  c 
24 2000   127       Hrvatska Demokratska Zajednica (HDZ)  2  c 
25 2012   127        Stranka Demokratske Akcije (SDA) 10  p 
26 2004   127        Socijaldemokratska Partija (SDP)  6  m 
27 1997   127       Koalicija - SDA, SBiH, Liberali, GDS 13  p 

Answer 1

# load relevant packages 
library(scales) 
library(grid) 
library(ggplot2) 
library(plyr) 

# assume your data is called df 
# order data by year, ideology and party 
df2 <- arrange(df, year, ideology, party) 

######################################## 


# create one colour palette per ideology 

# count number of parties per ideology 
tt <- with(df2[!duplicated(df2$party), ], table(ideology)) 

# conservative parties blues 
# progressive parties green 
# moderate parties red  
blue <- brewer_pal(pal = "Blues")(tt[names(tt) == "c"]) 
green <- brewer_pal(pal = "Greens")(tt[names(tt) == "p"]) 
red <- brewer_pal(pal = "Reds")(tt[names(tt) == "m"]) 

# create data on party and ideology 
party_df <- df2[!duplicated(df2$party), c("party", "ideology")] 

# set levels of ideologies; c, p, m 
party_df$ideology <- factor(party_df$ideology, levels = c("c", "p", "m")) 

# order by ideology and party 
party_df <- arrange(party_df, ideology, party) 

# add fill colours 
party_df$fill <- c(blue, green, red) 

# set levels of parties based on the order of parties in party_df 
party_df$party <- factor(party_df$party, levels = party_df$party) 

# use same factor levels for parties in df2 
df2$party <- factor(df2$party, levels = party_df$party) 

################################## 


# Alternative 1. Plot with one legend 

g1 <- ggplot(data = df2, aes(x = as.factor(year), 
         y = seats, 
         fill = party)) + 
    geom_bar(stat = "identity", position = "fill") + 
    labs(x = "year", y = "% of seats for municipality") + 
    coord_cartesian(ylim = c(0, 1)) + 
    scale_fill_manual(values = party_df$fill, name = "Parties") + 
    theme_classic() 
g1 

#####################################3 
# alt 2. Plot with separate legends for each ideology 


# create separate plots for each ideology to get legends 

# conservative parties blue 
cons <- ggplot(data = df2[df2$ideology == "c", ], 
       aes(x = as.factor(year), 
        y = seats, 
        fill = party)) + 
    geom_bar(stat = "identity", position = "fill") + 
    scale_fill_manual(values = blue, name = "Conservative parties") 


# extract 'cons' legend 
tmp <- ggplot_gtable(ggplot_build(cons)) 
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box") 
legend_cons <- tmp$grobs[[leg]] 


# progressive parties green 
prog <- ggplot(data = df2[df2$ideology == "p", ], 
       aes(x = as.factor(year), 
        y = seats, 
        fill = party)) + 
    geom_bar(stat = "identity", position = "fill") + 
    scale_fill_manual(values = green, name = "Progressive parties") 

# extract 'prog' legend 
tmp <- ggplot_gtable(ggplot_build(prog)) 
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box") 
legend_prog <- tmp$grobs[[leg]] 


# moderate parties red 
mod <- ggplot(data = df2[df2$ideology == "m", ], 
       aes(x = as.factor(year), 
        y = seats, 
        fill = party)) + 
    geom_bar(stat = "identity", position = "fill") + 
    scale_fill_manual(values = red, name = "Moderate parties") 


# extract 'mod' legend 
tmp <- ggplot_gtable(ggplot_build(mod)) 
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box") 
legend_mod <- tmp$grobs[[leg]] 

####################################### 


# arrange plot and legends 

# define plotting regions (viewports) for plot and legends 
vp_plot <- viewport(x = 0.25, y = 0.5, 
        width = 0.5, height = 1) 

vp_legend_cons <- viewport(x = 0.66, y = 0.87, 
          width = 0.5, height = 0.15) 

vp_legend_prog <- viewport(x = 0.7, y = 0.55, 
          width = 0.5, height = 0.60) 

vp_legend_mod <- viewport(x = 0.75, y = 0.2, 
          width = 0.5, height = 0.30) 

# clear current device 
grid.newpage() 

# add objects to the viewports 
# plot without legend 
print(g1 + theme(legend.position = "none"), vp = vp_plot) 
upViewport(0) 

# legends 
pushViewport(vp_legend_cons) 
grid.draw(legend_cons) 
upViewport(0) 

pushViewport(vp_legend_prog) 
grid.draw(legend_prog) 
upViewport(0) 

pushViewport(vp_legend_mod) 
grid.draw(legend_mod)