Barplot与SError从表
我试图从我生成的表格中绘制分组条形图,如下所示.
Group.1 S.obs se.obs S.chao1 se.chao1
Cliona celata complex 499.7143 59.32867 850.6860 65.16366
Cliona viridis 285.5000 51.68736 462.5465 45.57289
Dysidea fragilis 358.6667 61.03096 701.7499 73.82693
Phorbas fictitius 525.9167 24.66763 853.3261 57.73494
到目前为止,我已经尝试了以下但没有取得好成绩:
library(dplyr)
library(tidyr)
library(ggplot2)
data.frame(t(agg_media)) %>%
add_rownames() %>%
gather(group, value, - c(rowname, se.chao1)) -> media_2
gather(group, value, - c(rowname, se.obs)) -> media_3
#take out error bars from S.obs
# mutate(media2, se.chao1 = replace(se.chao1, which(group == "S.obs"),NA)) -> media3
dodge <- position_dodge(width=0.9)
g <- ggplot(data = agg_media, aes(x = rowname, y = value, fill = group)) +
geom_bar(position = "dodge", stat = "identity") +
geom_errorbar(data = media_2, aes(ymax = value + se.chao1, ymin = value - se.chao1),
position = dodge, width = 0.25) +
geom_errorbar(data = media_3, aes(ymax = value + se.obs, ymin = value - se.obs),
position = dodge, width = 0.25) +
labs(x = "Sponge Species", y = "Averaged OTU Richness") +
scale_y_continuous(expand = c(0,0))
ggsave(g, file = "Obs_Est_OTUs.svg")
关键是将se.obs作为S.obs和se.chao1的标准错误作为S.chao1的标准错误,并将它们绘制为分组的条形图...
我在这做错了什么？
这是你想要的吗？
加载您的数据代码段:
txt <- '"Group.1" "S.obs" "se.obs" "S.chao1" "se.chao1"
"Cliona celata complex" 499.7143 59.32867 850.6860 65.16366
"Cliona viridis" 285.5000 51.68736 462.5465 45.57289
"Dysidea fragilis" 358.6667 61.03096 701.7499 73.82693
"Phorbas fictitius" 525.9167 24.66763 853.3261 57.73494'
dat <- read.table(text = txt, header = TRUE)
并加载一些包.特别是,我将使用tidyr进行数据操作,这种操作并不适合熔铸或重塑概念
library("ggplot2")
library("tidyr")
这三个步骤以合适的格式获取数据.首先我们收集变量,就像melt()我们需要告诉它哪个变量不收集,即哪个变量是id变量
mdat <- gather(dat, S, value, -Group.1)
S是我想要创建的包含变量名称value的列,是我要创建的列的名称,其中包含所选列中的数据,并且- Group.1表示可以处理除所有列之外的所有列group.1.这给出了:
Group.1 S value
1 Cliona celata complex S.obs 499.71430
2 Cliona viridis S.obs 285.50000
3 Dysidea fragilis S.obs 358.66670
4 Phorbas fictitius S.obs 525.91670
5 Cliona celata complex se.obs 59.32867
6 Cliona viridis se.obs 51.68736
7 Dysidea fragilis se.obs 61.03096
8 Phorbas fictitius se.obs 24.66763
9 Cliona celata complex S.chao1 850.68600
10 Cliona viridis S.chao1 462.54650
11 Dysidea fragilis S.chao1 701.74990
12 Phorbas fictitius S.chao1 853.32610
13 Cliona celata complex se.chao1 65.16366
14 Cliona viridis se.chao1 45.57289
15 Dysidea fragilis se.chao1 73.82693
16 Phorbas fictitius se.chao1 57.73494
接下来,我想在S上期(可变数据分割.)成两个变量,我会打电话type和var.type包含的值S或者se和var含有obs或chao1
mdat <- separate(mdat, S, c("type","var"))
这使:
Group.1 type var value
1 Cliona celata complex S obs 499.71430
2 Cliona viridis S obs 285.50000
3 Dysidea fragilis S obs 358.66670
4 Phorbas fictitius S obs 525.91670
5 Cliona celata complex se obs 59.32867
6 Cliona viridis se obs 51.68736
7 Dysidea fragilis se obs 61.03096
8 Phorbas fictitius se obs 24.66763
9 Cliona celata complex S chao1 850.68600
10 Cliona viridis S chao1 462.54650
11 Dysidea fragilis S chao1 701.74990
12 Phorbas fictitius S chao1 853.32610
13 Cliona celata complex se chao1 65.16366
14 Cliona viridis se chao1 45.57289
15 Dysidea fragilis se chao1 73.82693
16 Phorbas fictitius se chao1 57.73494
数据处理的最后一步是展开当前的紧凑数据,以便我们有列S和se我们做的spread()(这有点像重塑中的铸造)
mdat <- spread(mdat, type, value)
这给了我们
mdat
> mdat
Group.1 var S se
1 Cliona celata complex chao1 850.6860 65.16366
2 Cliona celata complex obs 499.7143 59.32867
3 Cliona viridis chao1 462.5465 45.57289
4 Cliona viridis obs 285.5000 51.68736
5 Dysidea fragilis chao1 701.7499 73.82693
6 Dysidea fragilis obs 358.6667 61.03096
7 Phorbas fictitius chao1 853.3261 57.73494
8 Phorbas fictitius obs 525.9167 24.66763
现在,完成后,我们可以绘制
ggplot(mdat, aes(x = Group.1, y = S, fill = var)) +
geom_bar(position = "dodge", stat = "identity") +
geom_errorbar(mapping = aes(ymax = S + se, ymin = S - se),
position = position_dodge(width=0.9), width = 0.25)
你只需要一个调用geom_errorbar(),因为它具有美学ymax和ymin可以在同一时间进行设置.
这给了产品
