This post describes how to reorder a variable in a ggplot2
chart. Several methods are suggested, always providing examples with reproducible code chunks. Note that this course on data manipulation can be helpful here.
Reordering groups in a ggplot2
chart can be a struggle. This is due to the fact that ggplot2 takes into account the order of the factor
levels, not the order you observe in your data frame. You can sort your input data frame with sort()
or arrange()
, it will never have any impact on your ggplot2
output.
This post explains how to reorder the level of your factor through several examples. Examples are based on 2 dummy datasets:
# Library
library(ggplot2)
library(dplyr)
# Dataset 1: one value per group
<- data.frame(
data name=c("north","south","south-east","north-west","south-west","north-east","west","east"),
val=sample(seq(1,10), 8 )
)
# Dataset 2: several values per group (natively provided in R)
# mpg
forcats
libraryThe forcats library is a library from the tidyverse especially made to handle factors in R. It provides a suite of useful tools that solve common problems with factors. The fct_reorder()
function allows to reorder the factor (data$name
for example) following the value of another column (data$val
here).
# load the library
library(forcats)
# Reorder following the value of another column:
%>%
data mutate(name = fct_reorder(name, val)) %>%
ggplot( aes(x=name, y=val)) +
geom_bar(stat="identity", fill="#f68060", alpha=.6, width=.4) +
coord_flip() +
xlab("") +
theme_bw()
# Reverse side
%>%
data mutate(name = fct_reorder(name, desc(val))) %>%
ggplot( aes(x=name, y=val)) +
geom_bar(stat="identity", fill="#f68060", alpha=.6, width=.4) +
coord_flip() +
xlab("") +
theme_bw()
If you have several values per level of your factor, you can specify which function to apply to determine the order. The default is to use the median, but you can use the number of data points per group to make the classification:
# Using median
%>%
mpg mutate(class = fct_reorder(class, hwy, .fun='median')) %>%
ggplot( aes(x=reorder(class, hwy), y=hwy, fill=class)) +
geom_boxplot() +
xlab("class") +
theme(legend.position="none") +
xlab("")
# Using number of observation per group
%>%
mpg mutate(class = fct_reorder(class, hwy, .fun='length' )) %>%
ggplot( aes(x=class, y=hwy, fill=class)) +
geom_boxplot() +
xlab("class") +
theme(legend.position="none") +
xlab("") +
xlab("")
The last common operation is to provide a specific order to your levels, you can do so using the fct_relevel()
function as follow:
# Reorder following a precise order
<- data %>%
p mutate(name = fct_relevel(name,
"north", "north-east", "east",
"south-east", "south", "south-west",
"west", "north-west")) %>%
ggplot( aes(x=name, y=val)) +
geom_bar(stat="identity") +
xlab("")
#p
dplyr
onlyThe mutate()
function of dplyr
allows to create a new variable or modify an existing one. It is possible to use it to recreate a factor with a specific order. Here are 2 examples:
arrange()
to sort your data frame, and reorder the factor following this desired order.%>%
data arrange(val) %>% # First sort by val. This sort the dataframe but NOT the factor levels
mutate(name=factor(name, levels=name)) %>% # This trick update the factor levels
ggplot( aes(x=name, y=val)) +
geom_segment( aes(xend=name, yend=0)) +
geom_point( size=4, color="orange") +
coord_flip() +
theme_bw() +
xlab("")
%>%
data arrange(val) %>%
mutate(name = factor(name, levels=c("north", "north-east", "east", "south-east", "south", "south-west", "west", "north-west"))) %>%
ggplot( aes(x=name, y=val)) +
geom_segment( aes(xend=name, yend=0)) +
geom_point( size=4, color="orange") +
theme_bw() +
xlab("")
reorder()
function of base RIn case your an unconditional user of the good old R, here is how to control the order using the reorder()
function inside a with()
call:
# reorder is close to order, but is made to change the order of the factor levels.
$class = with(mpg, reorder(class, hwy, median))
mpg
<- mpg %>%
p ggplot( aes(x=class, y=hwy, fill=class)) +
geom_violin() +
xlab("class") +
theme(legend.position="none") +
xlab("")
#p