我已经阅读了ggplot2 docs网站和其他问题,但我无法找到解决方案。我试图想象不同年龄组的一些数据。我有点成功,但看起来并不像我想要的那样。
这是我的情节的代码
p <- ggplot(suggestion, aes(interaction(Age,variable), value, color = Age, fill = factor(variable), group = Age))
p + geom_bar(stat = "identity")+
facet_grid(.~Age)![The facetting separates the age variables][1]
我的最终目标是创建一个堆栈条形图,这就是我使用填充的原因,但它没有将TDX值放在相应的Age组和Year中。 (有时TDX值== DX值,但我想要想象他们什么时候没有)
这里是dput(suggestion)
structure(list(Age = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L,
1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L,
3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L,
5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 1L, 2L, 3L, 4L, 5L, 6L,
7L), .Label = c("0-2", "3-9", "10-19", "20-39", "40-59", "60-64",
"65+", "UNSP", "(all)"), class = "factor"), variable = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
8L, 8L, 8L, 8L, 8L, 8L, 8L), .Label = c("Year.10.DX", "Year.11.DX",
"Year.12.DX", "Year.13.DX", "Year.10.TDX", "Year.11.TDX", "Year.12.TDX",
"Year.13.TDX"), class = "factor"), value = c(26.8648932910636,
30.487741796656, 31.9938838749782, 62.8189679326958, 72.8480838120064,
69.3044125928752, 36.9789457527416, 21.808001825378, 24.1073451428435,
40.3305134762935, 70.4486116545885, 68.8342676191755, 63.9227718107745,
34.6086468618636, 8.84033719571875, 13.2807072303835, 28.4781516422802,
55.139497471546, 59.7230544500003, 67.9448927372699, 37.7293286937066,
6.9507024051526, 17.4393054963572, 33.1485743479821, 61.198647580693,
58.6845873573852, 48.0073013177248, 28.4455801248562, 26.8648932910636,
19.8044453272475, 23.0189084635948, 53.7037832071889, 60.6516550126422,
58.1573725886767, 27.0791868812255, 21.808001825378, 19.8146296425633,
35.0587750051557, 62.3308555053346, 59.3299998610862, 56.5341245769817,
27.7229319271878, 8.84033719571875, 13.2807072303835, 22.4081606349585,
48.0252683906252, 52.7560684009579, 65.2890977685045, 32.4142337849399,
6.9507024051526, 15.2833655677215, 24.5268503180754, 52.536784326675,
51.4100599515986, 40.9609231655724, 18.1306673637441)), row.names = c(NA,
-56L), .Names = c("Age", "variable", "value"), class = "data.frame")
答案 0 :(得分:1)
目前还不清楚你需要什么,但也许这个。
ggplot(a,aes(x=variable,y=value,fill=Age)) + geom_bar(stat='identity')
+facet_wrap(~Age)
如果要单独显示TDX和DX条目,我们需要稍微更改数据框。
> head(a)
Age variable value
1 0-2 Year.10.DX 26.86489
2 3-9 Year.10.DX 30.48774
3 10-19 Year.10.DX 31.99388
4 20-39 Year.10.DX 62.81897
5 40-59 Year.10.DX 72.84808
6 60-64 Year.10.DX 69.30441
感兴趣的列variable
是年份和TDX / DX值的组合。我们将使用tidyr
包将其分为两列。
library(tidyr)
library(dplyr)
tidy_a<- a %>% separate(variable, into = c( 'nothing',"year",'label'), sep = "\\.")
这实际上将levels
列variable
拆分为三个组件,因为我们在.
上拆分,并且每个条目中的字符.
出现两次。
> head(tidy_a)
Age nothing year label value
1 0-2 Year 10 DX 26.86489
2 3-9 Year 10 DX 30.48774
3 10-19 Year 10 DX 31.99388
4 20-39 Year 10 DX 62.81897
5 40-59 Year 10 DX 72.84808
6 60-64 Year 10 DX 69.30441
因此,列nothing
相当无用,只是使用separate
并在.
上分隔的必要结果。现在,这将允许我们单独可视化TDX / DX。
ggplot(tidy_a,aes(x=year,y=value,fill=label)) + geom_bar(stat='identity') + facet_wrap(~Age)