如何在boxplot中添加一行？ [英] How to add a line in boxplot?
问题描述
我想在boxplot中的mean之间添加行。
我的代码：
<$ p $ g $ g $ b $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ g $ 80）））
Fc =因子（c（rep（c（rep（FC1，40），rep（FC2，40）），2）））
Z < （c（rep（c（rep（50，20），rep（100，20）），4）））
Y < - c（0.19,0.22,0.23,0.17,0.36， 0.30,0.31,0.33,0.30,0.39,0.35,0.27,0.20,0.22,0.24,0.16,0.36,0.30,0.31,0.39,0.33,0.25,0.23,0.13,0.16,0.18，0.20,0.16,0.15,0.09,0.18， 0.20,0.14,0.17,0.18,0.22,0.16,0.14,0.11,0.18,0.21,0.30,0.36,0.40,0.42,0.26,0.23,0.25,0.30,0.27,0.15,0.29,0.36,0.38,0.42， 0.23,0.23,0.26,0.29,0.24,0.17,0.24,0.14,0.17,0.16,0.15,0.21,0.19,0.15,0.16,0.13,0.25,0.12,0.15,0.15,0.14， 0.29，0.29，0.29，0.24，0.21，0.23，0.25，0.33，0.30，0.27，0.31，0.27，0.28，0.25，0.2 2,0.23,0.23,0.33,0.29,0.28,0.12,0.28,0.22,0.19,0.22,0.14,0.15,0.15,0.21,0.25,0.11,0.27,0.22,0.17， 0.24，0.24，0.21，0.25，0.26，0.23，0.28，0.24，0.23，0.09，0.16，0.24，0.23， （c（rep（c（rep（c（rep（c（rep（c（rep（t） B 1，10），rep（B2，10）），8）））
DATA = data.frame（Y，X，Z，Fc，Gp）
p < - qplot X，Y，data = DATA，geom =boxplot，fill = Z，na.rm = TRUE，
outlier.size = NA，outlier.colour = NA）+
facet_grid（Gp〜Fc ）+ theme_light（）+ scale_colour_gdocs（）+
主题（legend.position =bottom）+
stat_summary（fun.y = mean，geom =point，shape = 23，position = position_dodge （width = .75））
我有：
这个想法与d.b的答案相同。为geom_segment调用创建一个data.frame。优点是dplyr工作流程。所以一切都是一次完成的。
DATA％>％
group_by（X，Z，Gp，Fc）％>％
总结（M =平均（Y））％>％
ungroup（）％>>％
mutate（Z = paste0（C，Z））％>％
spread（Z，M）
＃A tibble：8 x 5
X Gp Fc C100 C50
*< fctr> < FCTR> < FCTR> < DBL> < DBL>
1 B1 G1 FC1 0.169 0.281
2 B1 G1 FC2 0.170 0.294
3 B1 G2 FC1 0.193 0.270
4 B1 G2 FC2 0.168 0.269
5 B2 G1 FC1 0.171 0.276
6 B2 G1 FC2 0.161 0.292
7 B2 G2 FC1 0.188 0.269
8 B2 G2 FC2 0.163 0.264
或者与Julius的答案相比，你可以尝试一种不同的方法。添加中断和标签以获得期望的输出，并在数字 X2 和boxplot函数内的宽度参数上播放一些偏移量，以便将这些框绘制在一起。
DATA％>％
mutate（X2 = as.numeric（interaction（Z，X）））％％ >％
mutate（X2 = ifelse（Z == 100，X2 + 0.2，X2-0.2））％>％
ggplot（aes（X2，Y，fill = Z，group = X2 ））+
geom_boxplot（width = 0.6）+
stat_summary（fun.y = mean，geom =point）+
stat_summary（aes（group = X），fun.y =平均值，geom =line）+
facet_grid（Gp_Fc）+
scale_x_continuous（breaks = c（1.5,3.5），labels = c（B1，B2），
minor_breaks = NULL，limits = c（0.5,4.5））
I would like to add lines between "mean" in my boxplot.
My code:
library(ggplot2)
library(ggthemes)
Gp=factor(c(rep("G1",80),rep("G2",80)))
Fc=factor(c(rep(c(rep("FC1",40),rep("FC2",40)),2)))
Z <-factor(c(rep(c(rep("50",20),rep("100",20)),4)))
Y <- c(0.19 , 0.22 , 0.23 , 0.17 , 0.36 , 0.33 , 0.30 , 0.39 , 0.35 , 0.27 , 0.20 , 0.22 , 0.24 , 0.16 , 0.36 , 0.30 , 0.31 , 0.39 , 0.33 , 0.25 , 0.23 , 0.13 , 0.16 , 0.18 , 0.20 , 0.16 , 0.15 , 0.09 , 0.18 , 0.21 , 0.20 , 0.14 , 0.17 , 0.18 , 0.22 , 0.16 , 0.14 , 0.11 , 0.18 , 0.21 , 0.30 , 0.36 , 0.40 , 0.42 , 0.26 , 0.23 , 0.25 , 0.30 , 0.27 , 0.15 , 0.29 , 0.36 , 0.38 , 0.42 , 0.28 , 0.23 , 0.26 , 0.29 , 0.24 , 0.17 , 0.24 , 0.14 , 0.17 , 0.16 , 0.15 , 0.21 , 0.19 , 0.15 , 0.16 , 0.13 , 0.25 , 0.12 , 0.15 , 0.15 , 0.14 , 0.21 , 0.20 , 0.13 , 0.14 , 0.12 , 0.29 , 0.29 , 0.29 , 0.24 , 0.21 , 0.23 , 0.25 , 0.33 , 0.30 , 0.27 , 0.31 , 0.27 , 0.28 , 0.25 , 0.22 , 0.23 , 0.23 , 0.33 , 0.29 , 0.28 , 0.12 , 0.28 , 0.22 , 0.19 , 0.22 , 0.14 , 0.15 , 0.15 , 0.21 , 0.25 , 0.11 , 0.27 , 0.22 , 0.17 , 0.21 , 0.15 , 0.16 , 0.15 , 0.20 , 0.24 , 0.24 , 0.25 , 0.36 , 0.24 , 0.34 , 0.22 , 0.27 , 0.26 , 0.23 , 0.28 , 0.24 , 0.23 , 0.36 , 0.23 , 0.35 , 0.21 , 0.25 , 0.26 , 0.23 , 0.28 , 0.24 , 0.23 , 0.09 , 0.16 , 0.16 , 0.14 , 0.18 , 0.18 , 0.18 , 0.12 , 0.22 , 0.23 , 0.09 , 0.17 , 0.15 , 0.13 , 0.17 , 0.19 , 0.17 , 0.11)
X <- factor(c(rep(c(rep("B1",10),rep("B2",10)),8)))
DATA=data.frame(Y,X,Z,Fc,Gp)
p <- qplot(X, Y, data=DATA, geom="boxplot", fill=Z, na.rm = TRUE,
outlier.size = NA, outlier.colour = NA) +
facet_grid(Gp ~ Fc)+ theme_light()+scale_colour_gdocs()+
theme(legend.position="bottom") +
stat_summary(fun.y=mean, geom="point", shape=23, position = position_dodge(width = .75))
I have:
And the expected plot I want:
I tried this
p + stat_summary(fun.y=mean, geom="line", aes(group = factor(Z)))
and this
p + stat_summary(fun.y=mean, geom="line", aes(group = factor(X)))
but none of the above worked. Instead, I received the following error message:
geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic? geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic? geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic? geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic?
You can try a tidyverse solution as well:
library(tidyverse)
DATA %>%
ggplot() +
geom_boxplot(aes(X, Y, fill=Z)) +
stat_summary(aes(X, Y,fill=Z),fun.y = mean, geom = "point",
position=position_nudge(x=c(-0.185,0.185))) +
geom_segment(data=. %>%
group_by(X, Z, Gp , Fc) %>%
summarise(M=mean(Y)) %>%
ungroup() %>%
mutate(Z=paste0("C",Z)) %>%
spread(Z, M), aes(x = as.numeric(X)-0.185, y = C100,
xend = as.numeric(X)+0.185, yend = C50)) +
facet_grid(Gp ~ Fc)
The idea is the same as in the answer of d.b.. Create a data.frame for the geom_segment call. the advantage is the dplyr workflow. So everything is done in one run.
DATA %>%
group_by(X, Z, Gp , Fc) %>%
summarise(M=mean(Y)) %>%
ungroup() %>%
mutate(Z=paste0("C",Z)) %>%
spread(Z, M)
# A tibble: 8 x 5
X Gp Fc C100 C50
* <fctr> <fctr> <fctr> <dbl> <dbl>
1 B1 G1 FC1 0.169 0.281
2 B1 G1 FC2 0.170 0.294
3 B1 G2 FC1 0.193 0.270
4 B1 G2 FC2 0.168 0.269
5 B2 G1 FC1 0.171 0.276
6 B2 G1 FC2 0.161 0.292
7 B2 G2 FC1 0.188 0.269
8 B2 G2 FC2 0.163 0.264
Or you can try a slighlty different approach compared to Julius' answer. Add breaks and labels to get the expected output and play around with some offset on a numeric X2 and the width parameter within the boxplot function to get the boxes plotted together.
DATA %>%
mutate(X2=as.numeric(interaction(Z, X))) %>%
mutate(X2=ifelse(Z==100, X2 + 0.2, X2 - 0.2)) %>%
ggplot(aes(X2, Y, fill=Z, group=X2)) +
geom_boxplot(width=0.6) +
stat_summary(fun.y = mean, geom = "point") +
stat_summary(aes(group = X),fun.y = mean, geom = "line") +
facet_grid(Gp ~ Fc) +
scale_x_continuous(breaks = c(1.5,3.5), labels = c("B1","B2"),
minor_breaks = NULL, limits=c(0.5,4.5))
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