R ggplot2带引线的堆叠条形图标签

我试图创建一个有标签的堆叠条形图，其中只有一个条形。我的堆栈并不总是足够大，无法容纳文本，因此我希望对于无法容纳在堆栈中的标签，使用指向堆栈右侧标签的引线。或者，如果所有标签都位于具有引线的堆栈的右侧，则可以

我的data.frame看起来像这样：

Regional.District   Municipality Population.2010        mp
Metro               Bowen Island            3678    1839.0
Metro                  Coquitlam          126594   66975.0
Metro                      Delta          100000  180272.0
Metro               Langley City           25858  243201.0
Metro                Maple Ridge           76418  294339.0
Metro                   New West           66892  365994.0
Metro     North Vancouver (City)           50725  424802.5
Metro             Port Coquitlam           57431  478880.5
Metro                 Port Moody           33933  524562.5
Metro                     Surrey          462345  772701.5
Metro             West Vancouver           44058 1025903.0
Metro                 White Rock           19278 1057571.0
Metro                     Anmore            2203 1068311.5
Metro                   Belcarra             690 1069758.0
Metro                    Burnaby          227389 1183797.5
Metro             Langley (Town)          104697 1349840.5
Metro                  Lions Bay            1395 1402886.5
Metro      Metro Vancouver-uninc           24837 1416002.5
Metro North Vancouver (District)           88370 1472606.0
Metro               Pitt Meadows           18136 1525859.0
Metro                   Richmond          196858 1633356.0
Metro           Vancouver (City)          642843 2053206.5

这就是我目前的工作：

这就是我想要的工作：

这是我的密码：

library(ggplot2)
ggplot(muns, aes(x = Regional.District, y = Population.2010, fill = Municipality)) +
    geom_bar(stat = 'identity', colour = 'gray32', width = 0.6, show_guide = FALSE) +
    geom_text(aes(y = muns$mp, label = muns$Municipality), colour = 'gray32')

这可以自动化吗？我可以不使用ggplot2来完成这项任务。

---

谢谢

这里有一种可能性。我认为这项工作确实需要一些手动工作，尽管您可以自动化一些过程。我最初调查了哪些标签必须留在酒吧外。然后，我看到一些标签相互重叠。我的解决方案是移动酒吧左侧的一些标签

Anmore

是个棘手的问题。我手动将其y位置移得更高一点，这样它就不会与白岩重叠

gg1

是基本图形。您在栏中有标签<创建代码>gg2是为了获取标签，标签应添加到条的右侧。在

dan

中，我查看了ggplots使用和修改x值（即x=1.35）的数据。我还删除了这里的三个地方。在

emo

和

dan2

中的三个地方也做了类似的工作。在

gg3

中，我添加了标签。最后的工作是添加段。我创建了三个新的数据帧来绘制线段

library(dplyr) # I use the dev version (dplyr 0.4)
library(ggplot2)

# as_data_frame() is available in dplyr 0.4
mydf <- as_data_frame(list(Regional.District = rep("Metro", times = 22),
                           Municipality = c("Bowen Island", "Coquitlam", "Delta",
                                            "Langley City", "Maple Ridge", "New West",
                                            "North Vancouver (City)", "Port Coquitlam", "Port Moody",
                                            "Surrey", "West Vancouver", "White Rock",
                                            "Anmore", "Belcarra", "Burnaby", "Langley (Town)",
                                            "Lions Bay", "Metro Vancouver-uninc",
                                            "North Vancouver (District)", "Pitt Meadows",
                                            "Richmond", "Vancouver (City)"),
                           Population = c(3678, 126594, 100000, 25858, 76418, 66892, 50725,
                                          57431, 33933, 462345, 44058, 19278, 2203, 690,
                                          227389, 104697, 1395, 24837, 88370, 18136, 196858,
                                          642843),
                           mp = c(1839.0, 66975.0, 180272.0, 243201.0, 294339.0, 365994.0,
                                  424802.5, 478880.5, 524562.5, 772701.5, 1025903.0, 1057571.0,
                                  1068311.5, 1069758.0, 1183797.5, 1349840.5, 1402886.5, 1416002.5,
                                  1472606.0, 1525859.0, 1633356.0, 2053206.5)))


# Get label for places which has more than or less than 60,000 people

ana <- mutate(mydf, foo = ifelse(Population > 60000, Municipality, NA))
bob <- mutate(mydf, foo = ifelse(Population > 60000, NA, Municipality))


# Plot with places which have more than 60,000 people
gg1 <- ggplot(mydf, aes(x = Regional.District, y = Population, fill = Municipality)) +
       geom_bar(stat = "identity", colour = "gray32", width = 0.4, show_guide = FALSE) +
       geom_text(aes(y = ana$mp, label = ana$foo), colour = "gray32", size = 3)

# Plot with places which have less than 60,000 people
gg2 <- ggplot(mydf, aes(x = Regional.District, y = Population, fill = Municipality)) +
       geom_bar(stat = "identity", colour = "gray32", width = 0.4, show_guide = FALSE) +
       geom_text(aes(y = bob$mp, label = bob$foo), colour = "gray32")

# Label for right
dan <- na.omit(ggplot_build(gg2)$data[[2]]) %>%
       filter(!label %in% c("Belcarra", "Metro Vancouver-uninc", "Anmore")) %>%
       mutate(x = 1.35)

# Label for left
emo <- filter(ggplot_build(gg2)$data[[2]],
              label %in% c("Belcarra", "Metro Vancouver-uninc")) %>%
       mutate(x = 0.65)

# Special label for right
dan2 <- filter(ggplot_build(gg2)$data[[2]], label == "Anmore") %>%
        mutate(x = 1.35, y = 1098312)

# Add labels
gg3 <- gg1 +
       annotate("text", x = dan$x, y = dan$y, label = dan$label, colour = "gray32", size = 3) +
       annotate("text", x = emo$x, y = emo$y, label = emo$label, colour = "gray32", size = 3) +
       annotate("text", x = dan2$x, y = dan2$y, label = dan2$label, colour = "gray32", size = 3)


# Create data frames for segments
# right seg
r.seg <- data.frame(x = rep(1.2, times = 9),
                    xend = rep(1.25, times = 9),
                    y = dan$y,
                    yend = dan$y) 

# left seg
l.seg <- data.frame(x = rep(0.76, times = 2),
                    xend = rep(0.8, times = 2),
                    y = emo$y,
                    yend = emo$y)

# Anmore seg
a.seg <- data.frame(x = 1.2,
                    xend = 1.25,
                    y = 1068312,
                    yend = dan2$y)

# Draw the segments                                        
gg3 +
annotate("segment", x = r.seg$x, xend = r.seg$xend, y = r.seg$y, yend = r.seg$yend) +
annotate("segment", x = l.seg$x, xend = l.seg$xend, y = l.seg$y, yend = l.seg$yend) +
annotate("segment", x = a.seg$x, xend = a.seg$xend, y = a.seg$y, yend = a.seg$yend) 

library（dplyr）#我使用dev版本（dplyr 0.4）
图书馆（GG2）
#dplyr 0.4中提供了as_data_frame（）
mydf