对于两个分类变量的每个交叉分类,我有五个数据点.我试图在误差条之间添加一些均匀的间距,以便它们在刻面的ggplot2图中不重叠,但是失败了.数据很像这样…… library(ggplot2)library(dplyr
library(ggplot2)
library(dplyr)
df0 <- iris %>%
group_by(Species) %>%
mutate(long_sepal = ifelse(Sepal.Length > mean(Sepal.Length),
yes = "long", no = "short")) %>%
group_by(Species, long_sepal) %>%
mutate(petal_rank = order(Petal.Width)) %>%
filter(petal_rank <= 5)
> df0
# Source: local data frame [30 x 7]
# Groups: Species, long_sepal [6]
#
# Sepal.Length Sepal.Width Petal.Length Petal.Width Species long_sepal petal_rank
# (dbl) (dbl) (dbl) (dbl) (fctr) (chr) (int)
# 1 5.4 3.9 1.7 0.4 setosa long 1
# 2 4.6 3.4 1.4 0.3 setosa short 1
# 3 5.0 3.4 1.5 0.2 setosa short 2
# 4 4.4 2.9 1.4 0.2 setosa short 3
# 5 4.9 3.1 1.5 0.1 setosa short 4
# 6 5.4 3.7 1.5 0.2 setosa long 3
# 7 5.8 4.0 1.2 0.2 setosa long 4
# 8 5.2 4.1 1.5 0.1 setosa long 2
# 9 5.5 4.2 1.4 0.2 setosa long 5
# 10 4.5 2.3 1.3 0.3 setosa short 5
# .. ... ... ... ... ... ... ...
到目前为止绘制代码.
ggplot(data = df0,
aes(x = long_sepal, y = Petal.Width,
ymin = Petal.Width-0.05,
ymax = Petal.Width+0.05)) +
geom_pointrange(position = position_dodge(width = 0.4)) +
facet_wrap(~ Species, scales = "free")
我已经尝试过使用width参数,但无论值如何,我都会得到相同的图.
我相信你需要为df0添加一个因子变量,这将允许你在long_sepal中躲避观察.# Create new grouping column by which we can dodge df0$fac <- factor(unlist(sapply(as.vector(table(df0$long_sepal)), seq_len))) # Assign fac to "group = " inside the aes() ... aes(x = long_sepal, y = Petal.Width, group = fac, ...
