如何使用reshape2包中的melt（）来堆叠数据的分类标签以产生多个并排的boxpot

Question

我正在尝试使用R中“reshape2”包中的melt() function来堆叠数据“reshape2” ，同时保留用于各个观察的分类标签。 我的问题是，我如何适应Eric Cai's code Code，以在行为级别$ family（2级因子列）的行为级别上生成多个并排的带槽的箱线图，该行为由称为行为的数据集的每个行为变量分组（链接虚拟数据在下面提供）？

我的目标是用图例为每个系列(V4=red and W3 = blue)为这些多个凹口箱形图着色。 但是，在尝试使用melt()函数排列数据框时遇到尺寸问题，我无法从中解译。 如果有人可以提供帮助，则在此先多谢。

可重复的虚拟数据是在一个堆栈溢出页面底部发现重复性数据

 Here is an example:

 I am trying to follow Eric Cai's instructions
 (1) Stack the data:
     (a) Retain the categorical (2 level factor column) for family [,1]
     (b) Retain all behavioural variables [,2:13]

  #Set vectors for labelling the data

                      behaviours.label=c("Swimming", 
                                         "Not.Swimming",
                                         "Running", 
                                         "Not.Running",
                                         "Fighting",
                                         "Not.Fighting",
                                         "Resting",
                                         "Not.Resting",
                                         "Hunting",
                                         "Not.Hunting",
                                         "Grooming",
                                         "Not.Grooming")

                         family.labels=c("V4", "G8",
                                         "V4", "G8",
                                         "V4", "G8",
                                         "V4", "G8",
                                         "V4", "G8",
                                         "V4", "G8",
                                         "V4", "G8",
                                         "V4", "G8",
                                         "V4", "G8",
                                         "V4", "G8",
                                         "V4", "G8",
                                         "V4", "G8")

    library(tidyr)                        
    data_long <- gather(behaviours, x, Mean.Value, Swimming:Not.Grooming)
    head(data_long)  

    # stack the data while retaining the Family and behavioural variables 

    stacked.data = melt(behaviours, id = c('Family', 'behaviours'))

    # remove the column that gives the column name variable
    stacked.data = stacked.data[, -3]

    #head(stacked.data)
    colnames(stacked.data)<-c("Family", "Behaviours", "Values")

生成箱线图

生成一个名为boxplots.double的对象，该对象将使用公式文本{Mean.value〜Family + Behaviours}将地块分成12组doublet组（即，每个行为将在单个地块的行为$ family级别进行分组）。 在Eric Cai的代码中，“ at =”是一个选项，用于指定沿水平轴的箱形图的位置，而xaxt ='n'禁止使用默认水平轴，该默认水平轴将自定义轴与axis（）和title（）一起添加

   boxplots.double = boxplot(values~Family + Behaviours, 
                             data = stacked.data, 
                             at = c(1:24), 
                             xaxt='n',
                             ylim = c(min(0, min(-3)), 
                             max(7, na.rm = T)),
                             notch=TRUE,
                             col = c("red", "blue"),
                             names = c("V4", "G8"),
                             cex.axis=1.0,
                             srt=45)

  axis(side=1, at=c(1.8, 6.8), labels=c("Swimming", 
                                       "Not.Swimming",
                                       "Running", 
                                       "Not.Running",
                                       "Fighting",
                                       "Not.Fighting",
                                       "Resting",
                                       "Not.Resting",
                                       "Hunting",
                                       "Not.Hunting",
                                       "Grooming",
                                       "Not.Grooming"), line=0.5, lwd=0)

错误信息

   Error in axis(side = 1, at = 1:24, labels = c("V4", "G8"), xaxt = "n",     : 
  'at' and 'labels' lengths differ, 24 != 2
  In addition: Warning message:
  In bxp(list(stats = c(-1.20186549488911, -0.970033304559564,   -0.465271399251147,  :
  some notches went outside hinges ('box'): maybe set notch=FALSE

Answer 1

理查德·特尔福德（Richard Telford）慷慨地提供帮助之后，此代码使用reshape2包中包含的melt() function生成了多个分类箱图，这些箱图被归类为称为Family的分类列（2个级别）。

   clear the working directory
   rm(list=ls())

   data(behaviours)

   #Set vectors for labelling the data

   behaviours.labels=c("Swimming",  
                       "Not.Swimming",
                       "Running", 
                       "Not.Running",
                       "Fighting",
                       "Not.Fighting",
                       "Resting",
                       "Not.Resting",
                       "Hunting",
                       "Not.Hunting",
                       "Grooming",
                       "Not.Grooming")

       family.labels=c("V4", "G8",
                       "V4", "G8",
                       "V4", "G8",
                       "V4", "G8",
                       "V4", "G8",
                       "V4", "G8",
                       "V4", "G8",
                       "V4", "G8",
                       "V4", "G8",
                       "V4", "G8",
                       "V4", "G8",
                       "V4", "G8")

      library(tidyr)

      #Structure the data from wide to long format 

      data_long <- gather(behaviours, x, Mean.Value, Swimming:Not.Grooming)
      head(data_long)    

   library(reshape2)

   # stack the data while retaining Family and Values calculated from behaviours[,2:13] using the melt() function

   stacked.data = melt(data_long, id = c('Family', 'x'))
   head(stacked.data)

   # remove the column that gives the column name of the `variable' from all.data

   stacked.data = stacked.data[, -3]
   head(stacked.data)

   #Rename the column headings

   colnames(stacked.data)<-c("Family", "Behaviours", "Values")    

   #Generate the side-by-side boxplots

   windows(height=10, width=14)
   par(mar = c(9, 7, 4, 4)+0.3, mgp=c(5, 1.5, 0))

   boxplots.double = boxplot(Values~Family + Behaviours, 
                             data = stacked.data, 
                             at = c(1:24), 
                             ylim = c(min(0, min(0)), 
                                      max(1.8, na.rm = T)),
                             xaxt = "n",
                             notch=TRUE,
                             col = c("red", "blue"),
                             cex.axis=0.7,
                             cex.labels=0.7,
                             ylab="Values", 
                             xlab="Behaviours",
                             space=1)

   axis(side = 1, at = seq(2, 24, by = 2), labels = FALSE)
   text(seq(2, 24, by=2), par("usr")[3] - 0.2, labels=unique(behaviours.labels), srt = 45, pos = 1, xpd = TRUE, cex=0.8)
   legend("topright", title = "Family", cex=1.0, legend=c("V4" , "G8"), fill=c("Blue", "Red"), lty = c(1,1))