ggplot bar plot with facet-dependent order of categories
Ok, so all philosophizing aside, and in case anyone is interested, here is an ugly hack to do it. The idea is to use different labels (think paste(period, name) except I replace the period into 0-space, 1-space, etc. so that they don't show). I need this plot and I don't want to arrange grobs and the like, because I might want to share a common legend, etc.
The atomic example given earlier becomes:
df <- data.frame(name=c('foo','bar','foo','bar'),
period=c('old','old','recent','recent'),
val=c(1.23,2.17,4.15,3.65),
stringsAsFactors=F)
df$n = as.numeric(factor(df$period))
df = ddply(df,.(period,name),transform, x=paste(c(rep(' ',n-1), name), collapse=''))
df$x = factor(df$x, levels=df[order(df$val), 'x'])
p = ggplot(data = df, aes(x = x, y = val))
p = p + geom_bar(stat='identity')
p = p + facet_grid(~period, scale='free_x')
p
Another example, still a bit silly but closer to my actual use case, would be:
df <- ddply(mpg, .(year, manufacturer), summarize, mixmpg = mean(cty+hwy))
df$manufacturer = as.character(df$manufacturer)
df$n = as.numeric(factor(df$year))
df = ddply(df, .(year,manufacturer), transform,
x=paste(c(rep(' ',n-1), manufacturer), collapse=''))
df$x = factor(df$x, levels=df[order(df$mixmpg), 'x'])
p = ggplot(data = df, aes(x = x, y = mixmpg))
p = p + geom_bar(stat='identity')
p = p + facet_grid(~year, scale='free_x')
p = p + theme(axis.text.x=element_text(angle=90,hjust=1,vjust=.5,colour='gray50'))
p
Close your eyes, think of the Empire, and try to enjoy.
Try this, it's really simple (Just ignore the warnings)
df <-data.frame(name = c('foo', 'bar', 'foo', 'bar'),
period = c('old', 'old', 'recent', 'recent'),
val = c(1.23, 2.17, 4.15, 3.65))
d1 <- df[order(df$period, df$val), ]
sn <- factor(x = 1:4, labels = d1$name)
d1$sn <- sn
p <- ggplot(data = d1, aes(x = sn, y = val))
p <- p + geom_bar(stat = 'identity')
p <- p + facet_wrap(~ period, scale = 'free_x')
p
There are several different ways to achieve OP's goal per this answer
(1) reorder_within() function to reorder name within period facets.
library(tidyverse)
library(forcats)
df <- data.frame(
name = c("foo", "bar", "foo", "bar"),
period = c("old", "old", "recent", "recent"),
val = c(1.23, 2.17, 4.15, 3.65)
)
reorder_within <- function(x, by, within, fun = mean, sep = "___", ...) {
new_x <- paste(x, within, sep = sep)
stats::reorder(new_x, by, FUN = fun)
}
scale_x_reordered <- function(..., sep = "___") {
reg <- paste0(sep, ".+$")
ggplot2::scale_x_discrete(labels = function(x) gsub(reg, "", x), ...)
}
ggplot(df, aes(reorder_within(name, val, period), val)) +
geom_col() +
scale_x_reordered() +
facet_grid(period ~ ., scales = "free", space = "free") +
coord_flip() +
theme_minimal() +
theme(panel.grid.major.y = element_blank())
Or (2) similar idea
### https://trinkerrstuff.wordpress.com/2016/12/23/ordering-categories-within-ggplot2-facets/
df %>%
mutate(name = reorder(name, val)) %>%
group_by(period, name) %>%
arrange(desc(val)) %>%
ungroup() %>%
mutate(name = factor(paste(name, period, sep = "__"),
levels = rev(paste(name, period, sep = "__")))) %>%
ggplot(aes(name, val)) +
geom_col() +
facet_grid(period ~., scales = "free", space = 'free') +
scale_x_discrete(labels = function(x) gsub("__.+$", "", x)) +
coord_flip() +
theme_minimal() +
theme(panel.grid.major.y = element_blank()) +
theme(axis.ticks.y = element_blank())
Or (3) orders the entire data frame, and also orders the categories (period) within each facet group!
### https://drsimonj.svbtle.com/ordering-categories-within-ggplot2-facets
#
df2 <- df %>%
# 1. Remove any grouping
ungroup() %>%
# 2. Arrange by
# i. facet group (period)
# ii. value (val)
arrange(period, val) %>%
# 3. Add order column of row numbers
mutate(order = row_number())
df2
#> name period val order
#> 1 foo old 1.23 1
#> 2 bar old 2.17 2
#> 3 bar recent 3.65 3
#> 4 foo recent 4.15 4
ggplot(df2, aes(order, val)) +
geom_col() +
facet_grid(period ~ ., scales = "free", space = "free") +
coord_flip() +
theme_minimal() +
theme(panel.grid.major.y = element_blank())
# To finish we need to replace the numeric values on each x-axis
# with the appropriate labels
ggplot(df2, aes(order, val)) +
geom_col() +
scale_x_continuous(
breaks = df2$order,
labels = df2$name) +
# scale_y_continuous(expand = c(0, 0)) +
facet_grid(period ~ ., scales = "free", space = "free") +
coord_flip() +
theme_minimal() +
theme(panel.grid.major.y = element_blank()) +
theme(legend.position = "bottom",
axis.ticks.y = element_blank())
Created on 2018-11-05 by the reprex package (v0.2.1.9000)
This is an old question but it's being used as a dupe target. So it might be worthwhile to suggest a solution which utilizes the recent enhancements of the ggplot2 package, namely the labels parameter to scale_x_discrete(). This avoids to use duplicate levels which is deprecated or to manipulate factor labels by prepending a varying number of spaces.
Prepare data
Here, the mpg dataset is used to have a comparison to this answer. For data manipulation, the data.tablepackage is used here but feel free to use whatever package you prefer for this purpose.
library(data.table) # version 1.10.4
library(ggplot2) # version 2.2.1
# aggregate data
df <- as.data.table(mpg)[, .(mixmpg = mean(cty + hwy)), by = .(year, manufacturer)]
# create dummy var which reflects order when sorted alphabetically
df[, ord := sprintf("%02i", frank(df, mixmpg, ties.method = "first"))]
Create plot
# `ord` is plotted on x-axis instead of `manufacturer`
ggplot(df, aes(x = ord, y = mixmpg)) +
# geom_col() is replacement for geom_bar(stat = "identity")
geom_col() +
# independent x-axis scale in each facet,
# drop absent factor levels (actually not required here)
facet_wrap(~ year, scales = "free_x", drop = TRUE) +
# use named character vector to replace x-axis labels
scale_x_discrete(labels = df[, setNames(as.character(manufacturer), ord)]) +
# replace x-axis title
xlab(NULL) +
# rotate x-axis labels
theme(axis.text.x = element_text(angle = 90, hjust=1, vjust=.5))
