我创建了一个堆叠条形图，它描述了几年来(= x 轴)在一个自治市内的政党之间的议会席位(= y 轴)分布。使用的代码和一些数据如下。不幸的是，我还没有足够的点来发布图表。
不同的政党还与一个称为“意识形态”的变量相关联，作为不同政治倾向(“进步”、“温和”、“保守”)的类别。
我想以这样的方式修改颜色，例如保守党有不同类型的忧郁；所有进步党派不同种类的绿色；以及所有温和派，例如不同种类的红色；
意识形态上的变量在同一个数据框 (y) 中。
任何提示如何获得此修改？我已经尝试过 color=factor(ideology) 和 group=ideology 但无济于事。我也知道这个相关条目 Using a pre-defined color palette in ggplot但是它与我的问题无关。
非常感谢。
使用的命令:
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")
样本数据:
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
最佳答案
# 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)
关于r - 使用ggplot在一个堆叠条形图中的多个色阶，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/19568901/