In the df
below, I want to reorder bars from highest to lowest in each facet
I tried
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)
It didn't order the bars from highest to lowest in each facet.
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))
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.
DATA
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)
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:
I'm more fluent in data.table
, so this is used here. Feel free to use what ever package you prefer for data manipulation.
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
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)