表格中的分组条形图

Question

在对我的主题进行了一些搜索后，没有一个令人满意的答案或者我可以适应我的数据，这里还有一个关于使用 ggplot2 或 barplot 绘制分组（或堆叠）条形图的问题。

我有下表：

Table_lakes
    Lake Size Lake Mean Lake Med  Lake Max  Lake Min
 1:   2419723  6.557441 6.562879  9.107328 4.7520108
 2:    737345  1.569643 1.562833  2.643082 0.9065250
 3:   1904419  3.006871 2.989362  4.100533 2.3644874
 4:    633220  3.170494 3.154871  4.580919 1.6915103
 5:   3417157  4.587906 4.589763  5.865326 3.5397623
 6:   3046643  1.784759 1.783092  2.921241 0.6835220
 7:   3868608  2.152185 2.188566  5.382725 0.1158626
 8:  11952064  9.391443 9.342757 12.524334 8.5829620
 9:   2431961  7.796330 7.833883  9.186878 5.9242287
10:   5624563  8.444996 8.482042 12.207799 7.3909297
11:   2430490  3.474408 3.438787  5.186004 2.3032870

我想为每个 ID (1-11) 创建一个分组条形图，其中包含平均值、中值、最大值和最小值。湖的大小在这里有点无关紧要。

到目前为止，我试图帮助自己解决这个问题：https://www.theanalysisfactor.com/r-11-bar-charts/ 和 Grouped barplot in ggplot2 in R

我的一个尝试是这样的：

 ggplot(Table_lakes[Table_lakes$`Lake Mean` & Table_lakes$`Lake Max`],
       aes(x = factor(Name), y = Table_lakes)) + 
  geom_bar(stat = "identity", position="dodge") +
  labs(x = "Name", y = "Height")

y 轴应显示 vales（大约 0 到 15），x 轴应显示分组的最小值、最大值、中值、平均值，分别用于 1 到 11 个湖。

如果有人可以提供一些帮助，那就太好了。谢谢！

Answer 1

这是使用 R 基本绘图功能的可能解决方案：

1/ 来自您的示例数据：

    RAWDATA = "ID    Lake_Size Lake_Mean Lake_Med  Lake_Max  Lake_Min
 1:   2419723  6.557441 6.562879  9.107328 4.7520108
 2:    737345  1.569643 1.562833  2.643082 0.9065250
 3:   1904419  3.006871 2.989362  4.100533 2.3644874
 4:    633220  3.170494 3.154871  4.580919 1.6915103
 5:   3417157  4.587906 4.589763  5.865326 3.5397623
 6:   3046643  1.784759 1.783092  2.921241 0.6835220
 7:   3868608  2.152185 2.188566  5.382725 0.1158626
 8:  11952064  9.391443 9.342757 12.524334 8.5829620
 9:   2431961  7.796330 7.833883  9.186878 5.9242287
10:   5624563  8.444996 8.482042 12.207799 7.3909297
11:   2430490  3.474408 3.438787  5.186004 2.3032870"

DATA = read.table(textConnection(RAWDATA), header=TRUE)

2/ 选择您想要的列并（重新）设置列名和行名

A  = DATA[, 3:6]
rownames(A) = paste0("#", 1:nrow(A))
colnames(A) = c("Mean", "Median", "Max", "Min")

3/ 然后，绘制数据：

cols = c("blue", "darkblue",  "red", "green") # bar colors
mainsep = 0.1 # space between grouped bars
secsep = 0 # space between bars

# defining an empty plot with the right dimensions
xlim = c(0, nrow(A)-mainsep)
ylim = c(0, max(A))
plot(NA, xlim=xlim, ylim=ylim, xaxt="n", ylab="Lake level [m]", xlab="Lakes ID")
# create the x-axis with the table row names as labels
axis(1, at=1:nrow(A)-0.5-mainsep/2, labels=rownames(A), tick=FALSE, mgp=c(3, 0.1, 0))
axis(1, at=0:nrow(A)-mainsep/2, labels=NA, tick=TRUE)
# create the grouped bar according to the column of the table
boxsize = (1-mainsep)/ncol(A)
for (i in 1:nrow(A)) {
    for (j in 1:ncol(A)) {
        rect((i-1)+boxsize*(j-1), 0, (i-1)+boxsize*j-secsep, A[i, j], col=cols[j])
    }
}
# add a legend to identify the content of each column
legend("top",  horiz=TRUE, legend=colnames(A), col="black", pt.bg=cols, pch=22, pt.cex=2)

这可以根据您的需要轻松定制。希望对您有所帮助。

Answer 2

将数据放入名为“test.csv”的 csv 文件中，如下所示：

    id  size    mean    med max min
1   2419723 6.557441    6.562879    9.107328    4.7520108
2   737345  1.569643    1.562833    2.643082    0.906525
3   1904419 3.006871    2.989362    4.100533    2.3644874
4   633220  3.170494    3.154871    4.580919    1.6915103
5   3417157 4.587906    4.589763    5.865326    3.5397623
6   3046643 1.784759    1.783092    2.921241    0.683522
7   3868608 2.152185    2.188566    5.382725    0.1158626
8   11952064    9.391443    9.342757    12.524334   8.582962
9   2431961 7.79633 7.833883    9.186878    5.9242287
10  5624563 8.444996    8.482042    12.207799   7.3909297
11  2430490 3.474408    3.438787    5.186004    2.303287

然后写下面的代码：

require(reshape2)
#the reshape2 package is required here
testData <- read.csv('~/Desktop/test.csv')
testData$id <- as.factor(testData$id) 
#convert the id field to factors instead of numerical values
testDataMelt <- reshape2::melt(testData, id.vars = "id", value.name = "value")
testDataMelt <- testDataMelt[testDataMelt$variable != "size",]
#convert the data to the format that is convenient for plotting by ggplot2 and remove the size field
ggplot(testDataMelt, aes(x = id, y = value, group = variable, fill = variable)) + geom_bar(stat = "identity", position = "dodge")
#finally, ggplot the data

剧情：

希望这会有所帮助！