我想在保持秩序的同时创建分组条形图。如果是单列而不是分组条形图,则使用重新排序功能是显而易见的。但不确定如何在融化的data.frame上使用它。
以下是代码示例的详细说明:
让我们说我们有以下data.frame:
d.nfl <- data.frame(Team1=c("Vikings", "Chicago", "GreenBay", "Detroit"), Win=c(20, 13, 9, 12))
在翻转时绘制简单的条形图。
ggplot(d.nfl, aes(x = Team1, y=Win)) + geom_bar(aes(fill=Team1), stat="identity") + coord_flip()
上面的情节将没有订单,如果我想通过赢取订单,我可以做以下:
d.nfl$orderedTeam <- reorder(d.nfl$Team1, d.nfl$Win)
ggplot(d.nfl, aes(x = orderedTeam, y=Win)) + geom_bar(aes(fill=orderedTeam), stat="identity") + coord_flip()
现在假设我们添加另一列(到原始数据框)
d.nfl$points <- c(12, 3, 45, 5)
Team1 Win points
1 Vikings 20 12
2 Chicago 13 3
3 GreenBay 9 45
4 Detroit 12 5
要生成分组条形图,首先我们需要将其融合:
library(reshape2)
> d.nfl.melt <- melt(d.nfl[,c('Team1','Win','points')],id.vars = 1)
> ggplot(d.nfl.melt,aes(x = Team1,y = value)) + geom_bar(aes(fill = variable),position = "dodge", stat="identity") + coord_flip()
以上ggplot是无序的。
但我如何订购组合条形图(以升序方式)
答案 0 :(得分:3)
这不是问题。
最简单的方法是不要在融化中丢弃您订购的团队:
d.nfl.melt <- melt(d.nfl,id.vars = c("Team1", "orderedTeam"))
或者,我们可以在融化后使用reorder
,只使用Win
元素计算排序:
d.nfl.melt$ordered_after_melting = reorder(
d.nfl.melt$Team1,
X = d.nfl.melt$value * (d.nfl.melt$variable == "Win")
)
另一个想法是从原始有序列中取出levels
并将它们应用于融化因子:
d.nfl.melt$copied_levels = factor(
d.nfl.melt$Team1,
levels = levels(d.nfl$orderedTeam)
)
所有三种方法都给出了相同的结果。 (我省略了coord_flips,因为它们没有在问题中添加任何内容,但您当然可以将它们添加回来。)
gridExtra::grid.arrange(
ggplot(d.nfl.melt,aes(x = orderedTeam, y = value)) +
geom_bar(aes(fill = variable),position = "dodge", stat="identity"),
ggplot(d.nfl.melt,aes(x = ordered_after_melting, y = value)) +
geom_bar(aes(fill = variable),position = "dodge", stat="identity"),
ggplot(d.nfl.melt,aes(x = copied_levels, y = value)) +
geom_bar(aes(fill = variable),position = "dodge", stat="identity")
)
至于最简单的,我建议只在融化时保持orderedTeam
变量。你的代码似乎很难将它遗漏掉,很容易将其保留下来。
答案 1 :(得分:2)
您的问题提出的挑战是如何根据融化列中的子集值对因子Team1
重新排序。
来自@alistaire和@joran的问题评论链接到了很棒的答案。
tl; dr答案是使用levels()
将原始未融合数据框架的排序应用于新的。{/ p>
library(reshape2)
#Picking up from your example code:
d.nfl.melt <- melt(d.nfl[,c('Team1','Win','points')],id.vars = 1)
levels(d.nfl.melt$Team1)
#Current order is alphabetical
#[1] "Chicago" "Detroit" "GreenBay" "Vikings"
#Reorder based on Wins (using the same order from your earlier, unmelted data.frame)
d.nfl.melt$Team1 <- factor(d.nfl.melt$Team1, levels = levels(d.nfl$orderedTeam)) #SOLUTION
levels(d.nfl.melt$Team1)
#New order is ascending by wins
#[1] "GreenBay" "Detroit" "Chicago" "Vikings"
ggplot(d.nfl.melt,aes(x = Team1,y = value)) +
geom_bar(aes(fill = variable),position = "dodge", stat="identity") + coord_flip()