我有以下数据框:
library(tidyverse)
plot_dat <- structure(list(sample_name = c("YY", "XX", "YY",
"XX"), interaction = c("Foo interaction", "Foo interaction",
"Bar interaction", "Bar interaction"), percent = c(9.54760559277962,
1.21705741166346, 58.1631385457859, 13.6359995314219)), row.names = c(NA,
-4L), .Names = c("sample_name", "interaction", "percent"), class = c("tbl_df",
"tbl", "data.frame"))
plot_dat
#> # A tibble: 4 x 3
#> sample_name interaction percent
#> <chr> <chr> <dbl>
#> 1 YY Foo interaction 9.55
#> 2 XX Foo interaction 1.22
#> 3 YY Bar interaction 58.2
#> 4 XX Bar interaction 13.6
我想要做的是创建一个相互重叠的条形图。我有以下代码:
plot_dat$interaction <- factor(plot_dat$interaction,
levels = c("Bar interaction", "Foo interaction") )
p <- ggplot(plot_dat,
aes(x = sample_name, y = percent, fill = interaction,
color = interaction, alpha = interaction)) +
geom_bar(stat = "identity", position = "identity") +
scale_alpha_manual(values = c(0.2, 1))
p
当前情节如下:
我希望Foo interaction
位于覆盖图的顶部。
目前不是这样。这样,我必须使用alpha
值来减轻Bar interaction
的亮度,以使Foo
可见。
如何不使用Foo
值而强制Bar
出现在顶部并将alpha
留在后面?
答案 0 :(得分:2)
以前在geom_bar fill order not maintained with stat='identity'处有报道。 Hadley的回应如下(为强调起见,添加了粗体):
使用stat =“ identity”,不会以任何方式处理数据,因此 条将按顺序显示在原始数据框中。
您可以在绘制之前尝试根据因子级别顺序排列数据框:
ggplot(plot_dat %>% arrange(interaction),
aes(x = sample_name, y = percent, fill = interaction)) +
geom_col(position = "identity")
答案 1 :(得分:1)
这不是最有效的答案,但是您可以将两个过滤器传递到代码中并分别进行绘制。这是我的有效代码:
library(tidyverse)
plot_dat <- structure(list(sample_name = c("YY", "XX", "YY", "XX"),
interaction = c("Foo interaction",
"Foo interaction",
"Bar interaction",
"Bar interaction"),
percent = c(9.54760559277962,
1.21705741166346,
58.1631385457859,
13.6359995314219)),
row.names = c(NA, -4L),
.Names = c("sample_name", "interaction", "percent"),
class = c("tbl_df", "tbl", "data.frame"))
plot_dat
plot_dat$interaction <- factor(plot_dat$interaction, levels = c("Foo interaction", "Bar interaction") )
cond1 <- plot_dat$interaction == 'Foo interaction'
cond2 <- plot_dat$interaction == 'Bar interaction'
ggplot(plot_dat[cond2,],
aes(x=sample_name, y=percent, fill=interaction)) +
geom_bar(stat='identity') +
geom_bar(mapping=aes(x=plot_dat$sample_name[cond1],
y=plot_dat$percent[cond1],
fill=plot_dat$interaction[cond1]),
stat='identity')