ggplot2:在每个方面从最高到最低重新排列条形 [英] ggplot2: reorder bars from highest to lowest in each facet
问题描述
在下面的 df 中，我想将条形从高到低重新排序在每个方面
In the df below, I want to reorder bars from highest to lowest in each facet
我试过了
df <- df %>% tidyr::gather("var", "value", 2:4)
ggplot(df, aes (x = reorder(id, -value), y = value, fill = id))+
geom_bar(stat="identity")+facet_wrap(~var, ncol =3)
它给了我
它没有对每个方面的条形从高到低进行排序.
It didn't order the bars from highest to lowest in each facet.
我想出了另一种方式来获得我想要的东西.我必须一次绘制每个变量，然后使用 grid.arrange()
I figured out another way to get what I want. I had to plot each variable at a time, then combine all plots using grid.arrange()
#I got this function from @eipi10's answer
#http://stackoverflow.com/questions/38637261/perfectly-align-several-plots/38640937#38640937
#Function to extract legend
# https://github.com/hadley/ggplot2/wiki/Share-a-legend-between-two-ggplot2-graphs
g_legend<-function(a.gplot) {
tmp <- ggplot_gtable(ggplot_build(a.gplot))
leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
legend <- tmp$grobs[[leg]]
return(legend)
}
p1 <- ggplot(df[df$var== "A", ], aes (x = reorder(id, -value), y = value, fill = id))+
geom_bar(stat="identity") + facet_wrap(~var, ncol =3)
fin_legend <- g_legend(p1)
p1 <- p1 + guides(fill= F)
p2 <- ggplot(df[df$var== "B", ], aes (x = reorder(id, -value), y = value, fill = id))+
geom_bar(stat="identity") + facet_wrap(~var, ncol =3)+guides(fill=FALSE)
p3 <- ggplot(df[df$var== "C", ], aes (x = reorder(id, -value), y = value, fill = id))+
geom_bar(stat="identity") + facet_wrap(~var, ncol =3)+guides(fill=FALSE)
grid.arrange(p1, p2, p3, fin_legend, ncol =4, widths = c(1.5, 1.5, 1.5, 0.5))
结果就是我想要的
我想知道是否有一种简单的方法可以帮助我在所有方面从最高到最低对条形进行排序，而不必单独绘制每个变量然后将它们组合起来.任何建议将不胜感激.
I wonder if there is a straightforward way that can help me order the bars from highest to lowest in all facets without having to plot each variable separtely and then combine them. Any suggestions will be much appreciated.
数据
df <- read.table(text = c("
id A B C
site1 10 15 20
site2 20 10 30
site3 30 20 25
site4 40 35 40
site5 50 30 35"), header = T)
推荐答案
下面的方法使用了一个专门为 x 轴准备的变量，带有 facet_wrap() 但使用了 labelscode> 参数给 scale_x_discrete() 以显示正确的 x 轴标签:
The approach below uses a specially prepared variable for the x-axis with facet_wrap() but uses the labels parameter to scale_x_discrete() to display the correct x-axis labels:
我对data.table 比较流利，所以这里用这个.随意使用您喜欢的任何数据处理包.
I'm more fluent in data.table, so this is used here. Feel free to use what ever package you prefer for data manipulation.
编辑:删除了第二个虚拟变量，只需要ord
Edit: Removed second dummy variable, only ord is required
library(data.table)
# reshape from wide to long
molten <- melt(setDT(df), id.vars = "id")
# create dummy var which reflects order when sorted alphabetically
molten[, ord := sprintf("%02i", frank(molten, variable, -value, ties.method = "first"))]
molten
# id variable value ord
# 1: site1 A 10 05
# 2: site2 A 20 04
# 3: site3 A 30 03
# 4: site4 A 40 02
# 5: site5 A 50 01
# 6: site1 B 15 09
# 7: site2 B 10 10
# 8: site3 B 20 08
# 9: site4 B 35 06
#10: site5 B 30 07
#11: site1 C 20 15
#12: site2 C 30 13
#13: site3 C 25 14
#14: site4 C 40 11
#15: site5 C 35 12
创建情节
library(ggplot2)
# `ord` is plotted on x-axis instead of `id`
ggplot(molten, aes(x = ord, y = value, fill = id)) +
# geom_col() is replacement for geom_bar(stat = "identity")
geom_col() +
# independent x-axis scale in each facet,
# drop absent factor levels (not the case here)
facet_wrap(~ variable, scales = "free_x", drop = TRUE) +
# use named character vector to replace x-axis labels
scale_x_discrete(labels = molten[, setNames(as.character(id), ord)]) +
# replace x-axis title
xlab("id")
df <- read.table(text = "
id A B C
site1 10 15 20
site2 20 10 30
site3 30 20 25
site4 40 35 40
site5 50 30 35", header = T)
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