R语言数据可视化tidyr与ggplot2多个变量分层展示举例实现

y1 <- rnORM(20)
y2 <- rnorm(20)
dat <- data.frame(y1, y2)

            y1          y2
1  -0.12781723 -2.39376880
2   0.50074083  0.72555237
3  -0.02419456  0.94721701
4  -0.26366759 -0.60006759
5   1.13042618 -0.07591046
6   0.04313160  1.18677742
7   0.01180343  0.17627700
8   0.15208821 -0.12472391
9  -0.72690758 -1.92233170
10  1.04903577 -0.66208974
11  0.89689082  0.16331929
12  0.28471495  2.00629127
13 -0.26956768 -0.11897779
14 -0.81699454 -1.05575302
15 -0.65923768  1.20971004
16  0.18237270  1.55745467
17 -0.52359358 -0.74253496
18  1.36949647  1.07759474
19 -0.39882438  0.83915414
20  0.92084949 -1.04859906

dat %>%
  gather(y1, y2, key = "var", value = "value")

   var       value
1   y1 -0.12781723
2   y1  0.50074083
3   y1 -0.02419456
4   y1 -0.26366759
5   y1  1.13042618
6   y1  0.04313160
7   y1  0.01180343
8   y1  0.15208821
9   y1 -0.72690758
10  y1  1.04903577
11  y1  0.89689082
12  y1  0.28471495
13  y1 -0.26956768
14  y1 -0.81699454
15  y1 -0.65923768
16  y1  0.18237270
17  y1 -0.52359358
18  y1  1.36949647
19  y1 -0.39882438
20  y1  0.92084949
21  y2 -2.39376880
22  y2  0.72555237
23  y2  0.94721701
24  y2 -0.60006759
25  y2 -0.07591046
26  y2  1.18677742
27  y2  0.17627700
28  y2 -0.12472391
29  y2 -1.92233170
30  y2 -0.66208974
31  y2  0.16331929
32  y2  2.00629127
33  y2 -0.11897779
34  y2 -1.05575302
35  y2  1.20971004
36  y2  1.55745467
37  y2 -0.74253496
38  y2  1.07759474
39  y2  0.83915414
40  y2 -1.04859906

dat %>%
  gather(y1, y2, key = "var", value = "value") %>%
  ggplot(aes(x = value)) + 
  geom_histogram(aes(fill = factor(var), y = ..density..),
                 alpha = 0.3, colour = 'black') +
  stat_density(geom = 'line', position = 'identity', size = 1.5,
               aes(colour = factor(var))) +
  facet_wrap(~ var, ncol = 2) + 
  labs(y = '直方图与密度曲线', x = '值',
       title = '标题', fill = '变量') +
  theme(plot.title = element_text(hjust = 0.5)) +
  guides(color = FALSE)