这是一个简单的问题,但我很难理解ggplot2所需的格式:
我在R中有以下data.table
print(dt)
ID category A B C totalABC
1: 10 group1 1 3 0 4
2: 11 group1 1 11 1 13
3: 12 group2 15 20 2 37
4: 13 group2 6 12 2 20
5: 14 group2 17 83 6 106
...
我的目标是创建一个比例堆积条形图,如下例所示:https://rpubs.com/escott8908/RGC_Ch3_Gar_Graphs
其中X / totalABC的百分比,其中X是category_type
A,B或C.我还想按类别执行此操作,例如: x轴值应为group1
,group2
等。
作为一个具体的例子,在group1
的情况下,总共有4 + 13 = 17个元素。
百分比为percent_A = 11.7%, percent_B = 82.3%, percent_C = 5.9%
正确的ggplot2解决方案似乎是:
library(ggplot2)
pp = ggplot(dt, aes(x=category, y=percentage, fill=category_type)) +
geom_bar(position="dodge", stat="identity")
我的困惑:如何创建一个对应三个分类值的percentage
列?
如果上述内容不正确,我将如何格式化data.table
以创建堆叠条形图?
答案 0 :(得分:3)
您可以使用以下代码:
docker images
将绘制:
<强> 数据:的强>
melt(data.frame( #melt to get each variable (i.e. A, B, C) in a single row
dt[,-1] %>% #get rid of ID
group_by(category) %>% #group by category
summarise_each(funs(sum))), #get the summation for each variable
id.vars=c("category", "totalABC")) %>%
ggplot(aes(x=category,y=value/totalABC,fill=variable))+ #define the x and y
geom_bar(stat = "identity",position="fill") + #make the stacked bars
scale_y_continuous(labels = scales::percent) #change y axis to % format
在这种情况下,您可以使用它来获取百分比:
dt <- structure(list(ID = 10:14, category = structure(c(1L, 1L, 2L,
2L, 2L), .Label = c("group1", "group2"), class = "factor"), A = c(1L,
1L, 15L, 6L, 17L), B = c(3L, 11L, 20L, 12L, 83L), C = c(0L, 1L,
2L, 2L, 6L), totalABC = c(4L, 13L, 37L, 20L, 106L)), .Names = c("ID",
"category", "A", "B", "C", "totalABC"), row.names = c(NA, -5L
), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x0000000000100788>)
但是需要修改你的df <- melt(data.frame( #melt to get each variable (i.e. A, B, C) in a single row
dt[,-1] %>% #get rid of ID
group_by(category) %>% #group by category
summarise_each(funs(sum))), #get the summation for each variable
id.vars=c("category", "totalABC")) %>%
mutate(percentage = dtf$value*100/dtf$totalABC)
才能正确显示堆积条:
ggplot
答案 1 :(得分:1)
这是一个解决方案:
require(data.table)
require(ggplot2)
require(dplyr)
melt(dt,measure.vars = c("A","B","C"),
variable.name = "groups",value.name = "nobs") %>%
ggplot(aes(x=category,y=nobs,fill=groups)) +
geom_bar(stat = "identity",position="fill")