[英]ggplot bar plot with facet-dependent order of categories
我已經看到很多關於如何(重新)排序條形圖中類別的問題(通常與ggplot2 條形圖中的訂單條相關聯)。
我所追求的只是一點點不同,但我還沒有找到一個好的方法來做到這一點:我有一個多面的條形圖,我想根據另一個變量(在我的情況下,該變量只是 y 值本身,即我只希望條形在每個方面的長度增加)。
簡單示例,例如ggplot2 條形圖中的訂單欄:
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))
p = ggplot(data = df, aes(x = reorder(name, val), y = val))
p = p + geom_bar(stat='identity')
p = p + facet_grid(~period)
p
我們得到的是以下內容:
而我想要的是:
好吧,拋開所有的哲學思考,如果有人感興趣,這里有一個丑陋的黑客來做到這一點。 這個想法是使用不同的標簽(想想paste(period, name)
除了我將句點替換為 0-space、1-space 等,以便它們不顯示)。 我需要這個情節,我不想安排grobs之類的,因為我可能想分享一個共同的傳說等。
前面給出的原子示例變為:
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$val), 'x'])
p = ggplot(data = df, aes(x = x, y = val))
p = p + geom_bar(stat='identity')
p = p + facet_grid(~period, scale='free_x')
p
另一個例子,仍然有點愚蠢但更接近我的實際用例,將是:
df <- ddply(mpg, .(year, manufacturer), summarize, mixmpg = mean(cty+hwy))
df$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
閉上你的眼睛,想想帝國,並嘗試享受。
這是一個老問題,但它被用作欺騙目標。 因此,建議使用ggplot2
包的最新增強功能的解決方案可能是值得的,即scale_x_discrete()
的labels
參數。 這避免了使用已棄用的重復級別或通過預先添加不同數量的空格來操縱因子標簽。
在這里, mpg
數據集用於與此答案進行比較。 對於數據操作,這里使用了data.table
包,但您可以隨意使用您喜歡的任何包。
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"))]
# `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))
根據這個答案,有幾種不同的方法可以實現 OP 的目標
(1) reorder_within()
函數在period
方面重新排序name
。
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, ".+$")
ggplot2::scale_x_discrete(labels = function(x) gsub(reg, "", x), ...)
}
ggplot(df, aes(reorder_within(name, val, period), val)) +
geom_col() +
scale_x_reordered() +
facet_grid(period ~ ., scales = "free", space = "free") +
coord_flip() +
theme_minimal() +
theme(panel.grid.major.y = element_blank())
或(2)類似的想法
### https://trinkerrstuff.wordpress.com/2016/12/23/ordering-categories-within-ggplot2-facets/
df %>%
mutate(name = reorder(name, val)) %>%
group_by(period, name) %>%
arrange(desc(val)) %>%
ungroup() %>%
mutate(name = factor(paste(name, period, sep = "__"),
levels = rev(paste(name, period, sep = "__")))) %>%
ggplot(aes(name, val)) +
geom_col() +
facet_grid(period ~., scales = "free", space = 'free') +
scale_x_discrete(labels = function(x) gsub("__.+$", "", x)) +
coord_flip() +
theme_minimal() +
theme(panel.grid.major.y = element_blank()) +
theme(axis.ticks.y = element_blank())
或者 (3) 對整個數據框進行排序,並對每個構面組內的類別 ( period
) 進行排序!
### 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())
由reprex 包(v0.2.1.9000) 於 2018 年 11 月 5 日創建
試試這個,它真的很簡單(忽略警告)
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
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