我策划这个数据集 'DS'GGPLOT多面条形图:每个填充类别有多个“闪避”条形图?
ds <- structure(list(FN = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,
3L, 4L, 4L, 4L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L,
1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 1L, 1L, 1L, 2L,
2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L), .Label = c("FN=1", "FN=2", "FN=3",
"FN=4"), class = "factor"), fraction = structure(c(1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("serum",
"plasma"), class = "factor"), demographics = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("not adjusted",
"adjusted"), class = "factor"), freq = c(132, 47, 14, 30, 29,
19, 25, 14, 9, 5, 4, 4, 24, 21, 15, 6, 6, 5, 4, 4, 2, 2, 2, 2,
35, 28, 25, 68, 24, 11, 33, 15, 10, 12, 11, 8, 24, 16, 15, 13,
10, 6, 7, 6, 5, 4, 3, 3)), .Names = c("FN", "fraction", "demographics",
"freq"), class = "data.frame", row.names = c(NA, -48L))
使用此ggplot码
ggplot(ds, aes(x=fraction, y=freq, fill=factor(demographics, c("adjusted", "not adjusted")))) +
geom_bar(position=position_dodge(width=0.9), stat="identity", color="black") +
facet_grid(FN~., switch="y") +
scale_fill_manual("", values=c("not adjusted"="#e41a1c", "adjusted"="#377eb8"), guide=guide_legend(reverse = TRUE)) +
theme_bw() +
theme(legend.title=element_blank(), legend.position="bottom") +
theme(axis.title.x=element_text(face="bold")) +
theme(axis.title.y=element_blank()) +
theme(axis.ticks=element_blank()) +
theme(panel.background=element_blank()) +
theme(panel.grid=element_blank()) +
theme(strip.text.y = element_text(angle=180)) + coord_flip()
返回这个结果
正如你所看到的,每个x变量“分数”(血清/血浆)和填充类别“人口统计”(未调整/调整)是三个条形图。不过,我希望这些三个酒吧每个填充类别人口统计图并排绘制。这甚至有可能吗?
你的帮助是极大的赞赏!
感谢您的快速和准确的答案。还有一个问题,你知道我怎么能改变酒吧的顺序,以便'红色'(未调整)在'蓝色'之前或之上绘制? –
把你想要的第一个放在'scale_fill_manual'中,所以'scale_fill_manual(“”,values = c(“adjusted”=“#377eb8”,“not adjusted”=“#e41a1c”)...' –
听起来似乎是合理的,然而,这对我不起作用,也许是由于翻转了这个阴谋? –