如何在每个方面都具有有序数据的情况下生成多方面的ggplot图? [英] How to generate facetted ggplot graph where each facet has ordered data?

问题描述

我想按MeanWeight对我的因子(条件，参数和SubjectID)进行排序，并针对SubjectID对MeanWeight进行绘制，以便当面对Condition和Parameter时，MeanWeight以降序显示. 这是我的解决方案，没有给我我想要的东西:

I want to sort my factors (Condition, Parameter and SubjectID) by MeanWeight and plot MeanWeight against SubjectID such that when faceted by Condition and Parameter, MeanWeight appears in descending order. Here is my solution, which isn't giving me what I want:

dataSummary <- structure(list(SubjectID = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L), .Label = c("s001", 
"s002", "s003", "s004"), class = "factor"), Condition = structure(c(1L, 
1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L), .Label = c("1", "2", "3"), class = "factor"), Parameter = structure(c(1L, 
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 
3L), .Label = c("(Intercept)", "PrevCorr1", "PrevFail1"), class = "factor"), 
    MeanWeight = c(-0.389685536725783, 0.200987679398502, -0.808114314421089, 
    -0.10196105040707, 0.0274188815763494, 0.359978984195839, 
    -0.554583879312783, 0.643791202050396, -0.145042221940287, 
    -0.0144598460145723, -0.225804028997856, -0.928152539784374, 
    0.134025102103562, -0.267448309989731, -1.19980109795115, 
    0.0587152632631923, 0.0050656268880826, -0.156537446664213
    )), .Names = c("SubjectID", "Condition", "Parameter", "MeanWeight"
), row.names = c(NA, 18L), class = "data.frame")
## Order by three variables
orderWeights <- order(dataSummary$Condition, dataSummary$Parameter, dataSummary$SubjectID, -dataSummary$MeanWeight)
## Set factors to the new order. I expect this to sort for each facet when plotting, but it doesn't seem to work. 
conditionOrder <- dataSummary$Condition[orderWeights]
dataSummary$Condition <- factor(dataSummary$Condition, levels=conditionOrder)
paramOrder <- dataSummary$Parameter[orderWeights]
dataSummary$Parameter <- factor(dataSummary$Parameter, levels=paramOrder)
sbjOrder <- dataSummary$SubjectID[orderWeights]
dataSummary$SubjectID <- factor(dataSummary$SubjectID, levels=sbjOrder)
## Plot
ggplot(dataSummary, aes(x=MeanWeight, y=SubjectID)) + 
scale_x_continuous(limits=c(-3, 3)) + 
geom_vline(yintercept = 0.0, size = 0.1, colour = "#a9a9a9", linetype = "solid") + 
geom_segment(aes(yend=SubjectID), xend=0, colour="grey50") + 
geom_point(size=2) + 
facet_grid(Parameter~Condition, scales="free_y")

我尝试了其他几种方法，但是它们也不起作用:

I tried a few other approaches, but they didn't work either:

dataSummary <- dataSummary[order(dataSummary$Condition, dataSummary$Parameter, dataSummary$SubjectID, -dataSummary$MeanWeight),]

或这个

dataSummary <- transform(dataSummary, SubjectID=reorder(Condition, Parameter, SubjectID, MeanWeight))

推荐答案

您可以对数据进行排序和绘制.但是，标签不再对应于主题ID，而是对应于重新排序的主题.如果这不是您想要的，则不能使用构面，而必须分别绘制零件并使用例如grid.arrange组合不同的图.

You can order your data and plot it. However, the labels no longer correspond to Subject ID's, but to the reordered subjects. If that is not what you want, you cannot use faceting but have to plot the parts separately and use e.g.grid.arrangeto combind the different plots.

require(plyr)
## Ordered data
datOrder <- ddply(dataSummary, c("Condition", "Parameter"), function(x){
  if (nrow(x)<=1) return(x)
  x$MeanWeight <- x$MeanWeight[order(x$MeanWeight)]
  x
})
## Plot
ggplot(datOrder, aes(x=MeanWeight, y=SubjectID)) + 
  scale_x_continuous(limits=c(-3, 3)) + 
  geom_vline(yintercept = 0.0, size = 0.1, colour = "#a9a9a9", linetype = "solid") + 
  geom_segment(aes(yend=SubjectID), xend=0, colour="grey50") + 
  geom_point(size=2) + 
  facet_grid(Parameter~Condition) +
  scale_y_discrete(name="Ordered subjects")

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