绘图示例

Jeason

654字约2分钟

2020-01-07

复合饼图

复合图形可以给出更多的信息，并且更能够观察数据之间的联系。一般所说的复合饼图包括以下两种：

散点复合饼图（compound scatter and pie chart）可以展示三个数据变量的信息：(x, y, P)，其中x和y决定气泡在直角坐标系中的位置，P表示饼图的数据信息，决定饼图中各个类别的占比情况，如图1(a)所示。

气泡复合饼图（compound bubble and pie chart）可以展示四个数据变量的信息：(x, y, z, P)，其中x和y决定气泡在直角坐标系中的位置，z决定气泡的大小，P表示饼图的数据信息，决定饼图中各个类别的占比情况，如图1(b)所示。

具体操作如下：

library(ggforce)
library(dplyr)
data_graph <- read.table(text = "x     y group    nb
1     0     0     1  1060
2     0     0     2   361
3     0     0     3   267
4     0     1     1   788
5     0     1     2   215
6     0     1     3    80
7     1     0     1   485
8     1     0     2   168
9     1     0     3   101
10     1     1     1  6306
11     1     1     2  1501
12     1     1     3   379", header = TRUE)

# make group a factor
data_graph$group <- factor(data_graph$group)

# add case variable that separates the four pies
data_graph <- cbind(data_graph, case = rep(c("Aaaa", "Bbbb", "Cccc", "Dddd"), each = 3))

# calculate the start and end angles for each pie
data_graph <- left_join(data_graph,
                        data_graph %>% 
                          group_by(case) %>%
                          summarize(nb_total = sum(nb))) %>%
  group_by(case) %>%
  mutate(nb_frac = 2*pi*cumsum(nb)/nb_total,
         start = lag(nb_frac, default = 0))

# position of the labels
data_labels <- data_graph %>% 
  group_by(case) %>%
  summarize(x = x[1], y = y[1], nb_total = nb_total[1])

# overall scaling for pie size
scale = .5/sqrt(max(data_graph$nb_total))

# draw the pies
ggplot(data_graph) + 
  geom_arc_bar(aes(x0 = x, y0 = y, r0 = 0, r = sqrt(nb_total)*scale,
                   start = start, end = nb_frac, fill = group)) +
  geom_text(data = data_labels,
            aes(label = case, x = x, y = y + scale*sqrt(nb_total) + .05),
            size =11/.pt, vjust = 0) +
  coord_fixed() +
  scale_x_continuous(breaks = c(0, 1), labels = c("X0", "X1"), name = "x axis") +
  scale_y_continuous(breaks = c(0, 1), labels = c("Y0", "Y1"), name = "y axis") +
  theme_minimal() +
  theme(panel.grid.minor = element_blank())

最终得到的图形如下所示：

多组比较box图

# 生成数据
set.seed(40)
data <- data.frame(exp=c(rnorm(30,0,1.3),rnorm(30,0.5,1.6),
                          rnorm(30,1,1.9),rnorm(30,1.5,1.9)),
                   Stage=c(rep(paste0('Stage-',1:4),each=30)))
data$Stage <- factor(data$Stage, levels = c("Stage-1", "Stage-2", "Stage-3", "Stage-4"))
# 绘制图片
library(ggplot2)
library(ggsci)
library(ggpubr)
ggplot(data,aes(Stage,exp,fill=Stage))+
  geom_boxplot(outlier.colour = NA,notch = T,size = 0.4)+ # 箱式图
  geom_jitter(shape = 21,size=2,width = 0.2)+             # 散点
  geom_violin(position = position_dodge(width = .75),
              size = 0.4,alpha = 0.4,trim = T)+           # 小提琴图
  theme_classic()+
  theme(legend.position = 'none',
        axis.title.y = element_text(size=12),
        axis.text = element_text(size=12),
        axis.title.x = element_blank())+
  scale_fill_npg()+
  stat_compare_means(comparisons = split(t(combn(levels(data$Stage),2)),1:nrow(t(combn(levels(data$Stage),2)))),
                     label = 'p.signif') +
  stat_compare_means(label.y = max(data$exp)+5.7)