两个不同测量 session 的两个数据文件: ECG 和 B ECG 。
每个数据文件包含男性和女性。
我想在 R 中最低限度地做 2 列 x 4 行 Lattice Barchart，其中以下是界面的草图。
我可以做 2x2 条形图，请参阅下面的代码。
必须有一些更简单的方法，而不是手动在代码末尾添加越来越多的行，这很难控制。
ECG B.ECG
female female
Sinus
Arr/AHB
Digoxin arr
Furosemide arr
ECG B.ECG
male male
Sinus
Arr/AHB
Digoxin arr
Furosemide arr
数据心电图.csv
female Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.0,0.0,0.0,0.0,0.0,12.0,0.0
Arr/AHB,1.0,0.0,0.0,0.1,0.0,0.0,20.9,0.0
Digoxin arr,1.0,0.0,0.0,0.2,0.0,0.0,10.8,0.0
Furosemide arr,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
,,,,,,,,
male Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0
Arr/AHB,1.0,0.0,0.0,0.0,0.0,0.0,24.0,0.0
Digoxin arr,1.0,0.0,0.0,0.0,0.0,0.0,11.0,0.0
Furosemide arr,1.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0
数据 b.ecg.csv
female Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.2,0.2,0.0,0.0,0.0,11.7,0.0
Arr/AHB,1.2,0.0,1.8,3.8,0.0,0.0,15.1,0.1
Digoxin arr,0.5,0.2,0.0,1.0,0.0,0.0,4.3,0.0
Furosemide arr,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
,,,,,,,,
male Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0
Arr/AHB,1.0,3.2,0.0,4.3,0.0,0.0,16.5,0.0
Digoxin arr,1.0,0.0,0.7,0.8,0.0,0.0,9.5,0.0
Furosemide arr,1.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0
可以做 2x2 条形图但很难扩展到 2 列 x 4 行条形图的代码大约 1) 读取数据，以及 2) 应用格子条形图
library("gridExtra")
library("lattice")
library("reshape2")
data.n <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1:7]
rownames(data.n) <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1]
data.n.female <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1:7]
rownames(data.n.female) <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1]
data.n.male <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1:7]
rownames(data.n.male) <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1]
data.b <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1:7]
rownames(data.b) <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1]
data.b.female <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1:7]
rownames(data.b.female) <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1]
data.b.male <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1:7]
rownames(data.b.male) <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1]
# https://stackoverflow.com/a/40693458/54964
#1
data.n[] <- lapply(data.n, function(x) as.numeric(as.character(x)))
data.n$type <- "ecg"
data.n$ID <- rownames(data.n)
data.b[] <- lapply(data.b, function(x) as.numeric(as.character(x)))
data.b$type <- "b ecg"
data.b$ID <- rownames(data.b)
dat <- rbind(data.n[names(data.b)], data.b)
# Arrange data for plotting
dat.m <- melt(dat)
barchart(variable ~ value|ID, groups=type, data=dat.m,
auto.key=list(space='right'),
origin=0
)
#2
data.n.female[] <- lapply(data.n.female, function(x) as.numeric(as.character(x)))
data.n.female$gender <- "female"
data.n.female$ID <- rownames(data.n.female)
data.n.male[] <- lapply(data.n.male, function(x) as.numeric(as.character(x)))
data.n.male$gender <- "male"
data.n.male$ID <- rownames(data.n.male)
data.b.female[] <- lapply(data.b.female, function(x) as.numeric(as.character(x)))
data.b.female$gender <- "female"
data.b.female$ID <- rownames(data.b.female)
data.b.male[] <- lapply(data.b.male, function(x) as.numeric(as.character(x)))
data.b.male$gender <- "male"
data.b.male$ID <- rownames(data.b.male)
dat.2 <- rbind(data.n.female[names(data.n.male)],
data.b.female[names(data.b.male)],
data.n.male,
data.b.male)
dat.2$type <- rep(c("ECG", "B ECG"), each=2)
dat.2.m <- melt(dat.2, id=c("ID", "gender", "type"))
barchart(variable ~ value|ID+type, groups=gender, data=dat.2.m, auto.key=list(space='right'),
origin=0)
图 1 2x2 Lattice 条形图代码的输出
对我的系统的答案 here 进行故障排除
在答案中输出代码 1
带有代码的输出 2
Error in +geom_bar(stat = "identity", position = position_dodge()) :
invalid argument to unary operator
Execution halted
# Code
datm$male.Nij <- factor(datm$male.Nij, levels=lvs)
ggplot(datm, aes(variable, value, fill=gender))
+ geom_bar(stat="identity", position = position_dodge())
+ facet_grid(male.Nij ~ group)
# + facet_grid(factor(male.Nij, levels=lvs) ~ group)
+ coord_flip()
系统信息
> library(ggplot2)
> sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 8 (jessie)
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ggplot2_2.1.0
loaded via a namespace (and not attached):
[1] colorspace_1.3-0 scales_0.4.1 plyr_1.8.4 gtable_0.2.0
[5] Rcpp_0.12.7 grid_3.3.2 munsell_0.4.3
我们注意到
+ 版本在处理 ggplot2 方面存在一些差异。使代码在所描述的系统中工作的最后一行
ggplot(datm, aes(variable, value, fill=gender)) + geom_bar(stat="identity", position = position_dodge()) + facet_grid(male.Nij ~ group)
R:3.3.2 向后移植
操作系统:Debian 8.5
最佳答案
我认为最好的方法是结合数据，并重塑绘图
# Your data
# ECG
fem <- read.csv( text=
"female Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.0,0.0,0.0,0.0,0.0,12.0,0.0
Arr/AHB,1.0,0.0,0.0,0.1,0.0,0.0,20.9,0.0
Digoxin arr,1.0,0.0,0.0,0.2,0.0,0.0,10.8,0.0
Furosemide arr,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0")
male <- read.csv( text=
"male Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0
Arr/AHB,1.0,0.0,0.0,0.0,0.0,0.0,24.0,0.0
Digoxin arr,1.0,0.0,0.0,0.0,0.0,0.0,11.0,0.0
Furosemide arr,1.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0")
# Add gender grouping variable
fem$gender <- "female"
male$gender <- "male"
fem$group <- male$group <- "ECG"
# ECG b
fem2 <- read.csv( text=
"female Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.2,0.2,0.0,0.0,0.0,11.7,0.0
Arr/AHB,1.2,0.0,1.8,3.8,0.0,0.0,15.1,0.1
Digoxin arr,0.5,0.2,0.0,1.0,0.0,0.0,4.3,0.0
Furosemide arr,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0")
male2 <- read.csv( text=
"male Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0
Arr/AHB,1.0,3.2,0.0,4.3,0.0,0.0,16.5,0.0
Digoxin arr,1.0,0.0,0.7,0.8,0.0,0.0,9.5,0.0
Furosemide arr,1.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0")
fem2$gender <- "female"
male2$gender <- "male"
fem2$group <- male2$group <- "ECG b"
合并数据并重塑
# you will need to check they are in the right order
dat <- rbind(setNames(fem, names(male)), male,
setNames(fem2, names(male)), male2)
# reshape data for plotting
library(reshape2)
datm <- melt(dat)
格图
library(lattice)
lvs = unique(dat$male.Nij) # for ordering facets
barchart(variable ~ value|group + factor(male.Nij, levels=lvs), groups=gender,
data=datm, auto.key=list(space='right'), origin=0)
ggplot2 情节
library(ggplot2) # v2.1.0.9001
ggplot(datm, aes(variable, value, fill=gender)) +
geom_bar(stat="identity", position = position_dodge()) +
facet_grid(factor(male.Nij, levels=lvs) ~ group) +
coord_flip()
对于早期的 ggplot2 (v2.1.0) 版本，您可能需要在
factor 之外设置 facet_grid 级别datm$male.Nij <- factor(datm$male.Nij, levels=lvs)
ggplot(datm, aes(variable, value, fill=gender)) +
geom_bar(stat="identity", position = position_dodge()) +
facet_grid(male.Nij ~ group) +
coord_flip()
以及用于轻松复制粘贴 here 的完整代码。
关于r - 2x4 Lattice Barchart 在 R 中最低限度？，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/40694522/