如何在R ggplot中对此行列表进行直方图？
Léo*_* 준영 8 csv statistics r ggplot2
我试图通过以下过程在第一行中绘制描述性变量.我也尝试引用列/行名称失败
- 旋转CSV数据中的行和列,以获得线程中所需的重叠数据结构(高表)一个非常简单的直方图与R？同
ggplot 绘制事件的直方图
Absolute可变XOR( ,Average,)MinMax- 如果只是绝对值,只需在直方图中绘制绝对值.
- 如果(平均值,最小值和最大值),只需在直方图中用胡须(= 胡须图)绘制它们,其中胡须的极限由最小值和最大值组成.
数据
原来,
data.csv
Run Code Online (Sandbox Code Playgroud)"Vars" , "Sleep", "Awake", "REM", "Deep" "Absolute", , , 5 , 7 "Average" , 7 , 12 , , "Min" , 4 , 5 , , "Max" , 10 , 15 , ,视觉重塑后的数据
Run Code Online (Sandbox Code Playgroud)V1 V2 V3 V4 Vars Absolute Average Min Max Sleep <NA> 7 4 10 Awake <NA> 12 5 15 REM 5 <NA> <NA> <NA> Deep 7 <NA> <NA> <NA>重塑R后的数据
Run Code Online (Sandbox Code Playgroud)data <- structure(list(V1 = structure(c(3L, NA, NA, 1L, 2L), .Names = c("Vars", "Sleep", "Awake", "REM", "Deep"), .Label = c(" 5", " 7", "Absolute" ), class = "factor"), V2 = structure(c(3L, 2L, 1L, NA, NA), .Names = c("Vars", "Sleep", "Awake", "REM", "Deep"), .Label = c("12", " 7", "Average " ), class = "factor"), V3 = structure(c(3L, 1L, 2L, NA, NA), .Names = c("Vars", "Sleep", "Awake", "REM", "Deep"), .Label = c(" 4", " 5", "Min " ), class = "factor"), V4 = structure(c(3L, 1L, 2L, NA, NA), .Names = c("Vars", "Sleep", "Awake", "REM", "Deep"), .Label = c("10", "15", "Max " ), class = "factor")), .Names = c("V1", "V2", "V3", "V4"), row.names = c("Vars", "Sleep", "Awake", "REM", "Deep"), class = "data.frame")
R代码带有调试代码
dat.m <- read.csv("data.csv")
# rotate rows and columns
dat.m <- as.data.frame(t(dat.m)) # https://stackoverflow.com/a/7342329/54964 Comment 42-
library("reshape2")
dat.m <- melt(dat.m, id.vars="Vars")
## Just plot values existing there correspondingly
library("ggplot2")
# https://stackoverflow.com/a/25584792/54964
# TODO following
#ggplot(dat.m, aes(x = "Vars", y = value,fill=variable))
错误
Error: id variables not found in data: Vars
Execution halted
R:
3.3.3,3.4.0 (backports)
操作系统:Debian 8.7
R reshape2,ggplot2,... sessionInfo()加载两个软件包后
Platform: x86_64-pc-linux-gnu (64-bit)
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 reshape2_1.4.2
loaded via a namespace (and not attached):
[1] colorspace_1.3-2 scales_0.4.1 magrittr_1.5 plyr_1.8.4
[5] tools_3.3.3 gtable_0.2.0 Rcpp_0.12.10 stringi_1.1.5
[9] grid_3.3.3 stringr_1.2.0 munsell_0.4.3
测试HaberdashPI的提议
输出在图1中,其中在错误地绝对值Sleep和Awake.如果NA,只需将值设置为零.
图1 HaberdashPI的提案输出与预期不符
dat.m转置前的数据结构
'data.frame': 4 obs. of 5 variables:
$ Absolute: Factor w/ 2 levels " 5"," 7": NA NA 1 2
..- attr(*, "names")= chr "Sleep" "Awake" "REM" "Deep"
$ Average : Factor w/ 2 levels "12"," 7": 2 1 NA NA
..- attr(*, "names")= chr "Sleep" "Awake" "REM" "Deep"
$ Min : Factor w/ 2 levels " 4"," 5": 1 2 NA NA
..- attr(*, "names")= chr "Sleep" "Awake" "REM" "Deep"
$ Max : Factor w/ 2 levels "10","15": 1 2 NA NA
..- attr(*, "names")= chr "Sleep" "Awake" "REM" "Deep"
$ Vars : chr "Sleep" "Awake" "REM" "Deep"
Absolute Average Min Max Vars
Sleep <NA> 7 4 10 Sleep
Awake <NA> 12 5 15 Awake
REM 5 <NA> <NA> <NA> REM
Deep 7 <NA> <NA> <NA> Deep
dat.m转置后的数据结构
'data.frame': 16 obs. of 3 variables:
$ Vars : chr "Sleep" "Awake" "REM" "Deep" ...
$ variable: Factor w/ 4 levels "Absolute","Average ",..: 1 1 1 1 2 2 2 2 3 3 ...
$ value : chr NA NA " 5" " 7" ...
Vars variable value
1 Sleep Absolute <NA>
2 Awake Absolute <NA>
3 REM Absolute 5
4 Deep Absolute 7
5 Sleep Average 7
6 Awake Average 12
7 REM Average <NA>
8 Deep Average <NA>
9 Sleep Min 4
10 Awake Min 5
11 REM Min <NA>
12 Deep Min <NA>
13 Sleep Max 10
14 Awake Max 15
15 REM Max <NA>
16 Deep Max <NA>
测试akash87的提议
码
ds <- dat.m
str(ds)
ds
ds$variable
ds$variable %in% c("Min","Max")
输出错误,因为False最终
$ Vars : chr "Sleep" "Awake" "REM" "Deep" ...
$ variable: Factor w/ 4 levels "Absolute","Average ",..: 1 1 1 1 2 2 2 2 3 3 ...
$ value : chr NA NA " 5" " 7" ...
Vars variable value
1 Sleep Absolute <NA>
2 Awake Absolute <NA>
3 REM Absolute 5
4 Deep Absolute 7
5 Sleep Average 7
6 Awake Average 12
7 REM Average <NA>
8 Deep Average <NA>
9 Sleep Min 4
10 Awake Min 5
11 REM Min <NA>
12 Deep Min <NA>
13 Sleep Max 10
14 Awake Max 15
15 REM Max <NA>
16 Deep Max <NA>
[1] "hello 3"
[1] Absolute Absolute Absolute Absolute Average Average Average Average
[9] Min Min Min Min Max Max Max Max
Levels: Absolute Average Min Max
[1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[13] FALSE FALSE FALSE FALSE
这样做ds[ds$variable %in% c("Min","Max"), ]会给出False输出因为错误结转.
测试Uwe的提议
代码用显式data.table::dcast和两次data.table::melt.sessionInfo()刚刚打印出来molten <- ....注意library(ggplot2)尚未加载,因为错误来自该行molten <- ....
$ Rscript test111.r
Vars "Average" "Max" "Min" Absolute
1: Sleep 7 10 4 NA
2: Awake 12 15 5 NA
3: REM NA NA NA 5
4: Deep NA NA NA 7
R version 3.4.0 (2017-04-21)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 8 (jessie)
Matrix products: default
BLAS: /usr/lib/openblas-base/libblas.so.3
LAPACK: /usr/lib/libopenblasp-r0.2.12.so
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 base
other attached packages:
[1] data.table_1.10.4
loaded via a namespace (and not attached):
[1] compiler_3.4.0 methods_3.4.0
Error in melt.data.table(transposed, measure.vars = c("Absolute", "Average")) :
One or more values in 'measure.vars' is invalid.
Calls: <Anonymous> -> melt.data.table
Execution halted
用测试代码2测试Uwe的提议
码
molten <- structure(list(Vars = structure(c(1L, 2L, 1L, 2L, 1L, 2L), class = "factor", .Label = c("V1", "V2")), variable = structure(c(1L, 1L, 2L, 2L, 3L, 3L), class = "factor", .Label = c("ave", "ave_max", "lepo")), value = c(7L, 8L, 10L, 10L, 4L, 4L)), .Names = c("Vars", "variable", "value"), row.names = c(NA, -6L), class = c("data.table", "data.frame"))
print(molten)
library(ggplot2)
ggplot(molten, aes(x = Vars, y = value, fill = variable, ymin = lepo, ymax = ave_max)) +
geom_col() + geom_errorbar(width = 0.2)
产量
Vars variable value
1 V1 ave 7
2 V2 ave 8
3 V1 ave_max 10
4 V2 ave_max 10
5 V1 lepo 4
6 V2 lepo 4
Error in FUN(X[[i]], ...) : object 'lepo' not found
Calls: <Anonymous> ... by_layer -> f -> <Anonymous> -> f -> lapply -> FUN -> FUN
Execution halted
您的代码的问题在于您在 ggplot aes 函数中使用带引号的“Vars”而不是简单的 Vars。此外，您的数据集的标题也很混乱。Absolute、Average...应该是数据集的列名称，而不是值本身。这就是熔化函数出现错误的原因。
鉴于您的数据集，这是我的尝试：
#Data
data = cbind.data.frame(c("Sleep", "Awake", "REM", "Deep"),
c(NA, NA, 5, 7),
c(7, 12, NA, NA),
c(4, 5, NA, NA),
c(10, 15, NA, NA))
colnames(data) = c("Vars", "Absolute", "Average", "Min", "Max")
#reshape
dat.m <- melt(data, id.vars="Vars")
#Stacked plot
ggplot(dat.m, aes(x = Vars, y = value)) + geom_bar(aes(fill=variable), stat = "identity")
这将产生：
#Or multiple bars
ggplot(dat.m, aes(x = Vars, y = value)) +
geom_bar(aes(fill=variable), stat = "identity", position="dodge")
#Or separated by Vars
ggplot(dat.m, aes(x = Vars, y = value)) + geom_bar(aes(fill=variable), stat = "identity", position="dodge") + facet_wrap( ~ Vars, scales="free")
我正在为答案添加另一个图表。这与@Uwe 合作回答。
#data
data <- structure(list(Vars = structure(1:2, class = "factor", .Label = c("V1", "V2")), ave = c(7L, 8L), ave_max = c(10L, 10L), lepo = c(4L, 4L)), .Names = c("Vars", "ave", "ave_max", "lepo"), row.names = c(NA, -2L), class = c("data.table", "data.frame"), sorted = "Vars")
#Melt
library(data.table)
mo = data.table::melt(data, measure.vars = c("ave"))
ggplot(mo, aes(x = Vars, y = value, fill = variable, ymin = lepo, ymax = ave_max)) + geom_col() + geom_errorbar(width = 0.2)
这将产生：
