带标签的多级饼图答案

【问题标题】：Labelled multi-level pie chart带标签的多级饼图
【发布时间】：2018-02-02 17:51:44
【问题描述】：

我在 Rappid (https://resources.jointjs.com/docs/rappid/v2.2/shapes.html#shapes.chart.pie) 上找到了这张图片，并想用我自己的数据使用 R 来模拟它。我对图例和标签特别感兴趣，因为相关问题没有涵盖这一点 (@987654322 @)

下面是一些示例代码：

df <- data.frame(year = c(2014, 2014, 2014, 2014, 2014, 2013, 2013, 2013, 2013, 2013, 2012, 2012, 2012, 2012, 2012),
             browser = c("IE", "Firefox", "Chrome", "Safari", "Opera","IE", "Firefox", "Chrome", "Safari","Opera", "IE", "Firefox", "Chrome", "Safari", "Opera"),
             c = c("20.3", "18.3", "34.2", "17.8", "2.7", "27.5", "20.0","30.0", "14.8", "2.3", "30.9", "24.8", "24.6", "6.5","2.5"))

【问题讨论】：

你看到stackoverflow.com/questions/26748069/… 的 donuts_plot() 函数了吗——它看起来和你想做的很相似。
你能解释一下“对图例和标签感兴趣”是什么意思吗？顺便说一句，你的百分比不会增加到 100%
@PoGibas 我主要关注的代码是如何标记多级饼图并按年份拆分图例。数据是假的，我最终还是想用自己的
@Emily 是否有任何答案解决了您的问题？如果是，请接受，否则请更新您的问题。

标签： r ggplot2 pie-chart

【解决方案1】：

这是一个带有 ggplot2 的堆积饼图。数据中的百分比在每一年内都不会达到 100%，因此为了本示例的目的，我将它们缩放为 100%（如果您的真实数据没有耗尽，您可以改为添加“其他”类别所有选项）。我还将列的名称c 更改为cc，因为c 是一个R 函数。

library(tidyverse)

# Convert cc to numeric
df$cc = as.numeric(as.character(df$cc))

# Data for plot
pdat = df %>% 
  group_by(year) %>% 
  mutate(cc = cc/sum(cc)) %>% 
  arrange(browser) %>% 
  # Get cumulative value of cc
  mutate(cc_cum = cumsum(cc) - 0.5*cc) %>% 
  ungroup

ggplot(pdat, aes(x=cc_cum, y=year, fill=browser)) +
  geom_tile(aes(width=cc), colour="white", size=0.4) +
  geom_text(aes(label=sprintf("%1.1f", 100*cc)), size=3, colour="white") +
  geom_text(data=pdat %>% filter(year==median(year)), size=3.5, 
            aes(label=browser, colour=browser), position=position_nudge(y=0.5)) +
  scale_y_continuous(breaks=min(pdat$year):max(pdat$year)) +
  coord_polar() +
  theme_void() +
  theme(axis.text.y=element_text(angle=0, colour="grey40", size=9),
        axis.ticks.y=element_line(),
        axis.ticks.length=unit(0.1,"cm")) +
  guides(fill=FALSE, colour=FALSE) +
  scale_fill_manual(values=hcl(seq(15,375,length=6)[1:5],100,70)) +
  scale_colour_manual(values=hcl(seq(15,375,length=6)[1:5],100,50))

您也可以使用堆积条形图，这可能更清晰：

ggplot(pdat, aes(x=cc_cum, y=year, fill=browser)) +
  geom_tile(aes(width=cc), colour="white") +
  geom_text(aes(label=sprintf("%1.1f", 100*cc)), size=3, colour="white") +
  geom_text(data=pdat %>% filter(year == min(year)), size=3.2, 
            aes(label=browser, colour=browser), position=position_nudge(y=-0.6)) +
  scale_y_continuous(breaks=min(df$year):max(df$year)) +
  scale_x_continuous(expand=c(0,0)) +
  theme_void() +
  theme(axis.text.y=element_text(angle=0, colour="grey40", size=9),
        axis.ticks.y=element_line(),
        axis.ticks.length=unit(0.1,"cm")) +
  guides(fill=FALSE, colour=FALSE) +
  scale_fill_manual(values=hcl(seq(15,375,length=6)[1:5],100,70)) +
  scale_colour_manual(values=hcl(seq(15,375,length=6)[1:5],100,50))

线图可能是最清晰的：

library(scales)

ggplot(pdat, aes(year, cc, colour=browser)) +
  geom_line() +
  geom_label(aes(label=sprintf("%1.1f", cc*100)), size=3,
             label.size=0, label.padding=unit(1,"pt"), , colour="white") +
  geom_text(aes(label=sprintf("%1.1f", cc*100)), size=3) +
  geom_text(data=pdat %>% filter(year==max(year)), 
            aes(label=browser), hjust=0, nudge_x=0.08, size=3) +
  theme_classic() +
  expand_limits(x=max(pdat$year) + 0.3, y=0) +
  guides(colour=FALSE) +
  scale_x_continuous(breaks=min(pdat$year):max(pdat$year)) +
  scale_y_continuous(labels=percent)

【讨论】：

【解决方案2】：

另一种解决方案是创建两个图并将它们合并为一个。

# Modify your data

# Turn c to numeric (as @eipi10 has mentioned don't use c)
df$Y <- as.numeric(as.character(df$c))

# Create second dummy legend/plot
# Rows for year
foo <- data.frame(cumsum(table(df$year)) + 1:length(unique(df$year)))
foo$year <- rownames(foo)
colnames(foo)[1] <- "row"
# Rows for browsers
df$row <- which(do.call(rbind, by(df, df$year, rbind, ""))$year != "")

colors <- c("#56B998", "#ec3f52", "#8ac8ff", "#8a768a", "#E5CF00")
library(ggplot2)
p1 <- ggplot(df, aes(factor(year), Y, fill = browser)) + 
    geom_bar(stat = "identity", width = 1, size = 1, color = "white") +
    coord_polar("y") + 
    theme_void() +
    theme(legend.position = "none") +
    scale_fill_manual(values = colors)
p2 <- ggplot(df, aes(y = row)) + 
    geom_point(aes(0, color = browser), size = 4) +
    geom_text(data = foo, aes(0, label = rev(year)), size = 5, color = "grey50") +
    geom_text(aes(0.5, label = paste0(browser, ": ", c, "%"))) +
    theme_void() +
    theme(legend.position = "none") +
    scale_x_discrete() +
    scale_color_manual(values = colors)

# Combine two plots
library(egg)
ggarrange(p1, p2, nrow = 1, widths = c(3, 1))

【讨论】：

【解决方案3】：

另一种选择是使用ggforce-package：

library(dplyr)

df2 <- df %>% 
  mutate(r0 = (year - 2012)/n_distinct(year),
         r1 = (year - 2011)/n_distinct(year)) %>% 
  group_by(year) %>% 
  mutate(ends = 2 * pi * cumsum(share)/sum(share),
         starts = lag(ends, default = 0),
         mids = 0.5*(starts + ends))

library(ggforce)

ggplot(df2) +
  geom_arc_bar(aes(x0 = 0, y0 = 0, r0 = r0, r = r1, start = starts, end = ends, fill = browser), color = 'white') +
  geom_text(aes(x = (r1+r0)*sin(mids)/2, y = (r1+r0)*cos(mids)/2, label = lbl)) +
  coord_fixed() +
  labs(title = 'Browser marketshare', x = NULL, y = NULL) +
  scale_y_continuous(breaks = (1:3)/3 - 1/6, labels = 2012:2014) +
  theme_minimal() +
  theme(panel.grid = element_blank(),
        axis.text.x = element_blank())

给出：

【讨论】：