Question

我有以下数据集：

structure(list(Geschaeft = c(0.0961028525512254, 0.0753516756309475, 
0, 0.0722803347280335, 0, 0.000877706260971328), Gaststaette = c(0.0981116914423463, 
0.0789718659495242, 0.0336538461538462, 0.0905857740585774, 0, 
0.00175541252194266), Bank = c(0.100843712334271, 0.0717832023169218, 
0.00480769230769231, 0.025, 0.00571428571428572, 0.00965476887068461
), Hausarzt = c(0.0633989554037766, 0.0589573851882499, 0.0288461538461538, 
0.0217573221757322, 0.00685714285714286, 0.0128730251609128), 
    Einr..F..Aeltere = c(0.0337484933708317, 0.0550268928423666, 
    0.00480769230769231, 0, 0.00114285714285714, 0.000292568753657109
    ), Park = c(0.0738449176376055, 0.0726623913942904, 0.0625, 
    0.0846234309623431, 0.00228571428571429, 0.112053832650673
    ), Sportstaette = c(0.0449979911611089, 0.0612846503930492, 
    0.00480769230769231, 0.0619246861924686, 0.00114285714285714, 
    0), OEPNV = c(0.10847730012053, 0.089056681836988, 0.264423076923077, 
    0.135669456066946, 0, 0.185488589818607), Mangel.an.Gruenflaechen = c(0.0867818400964243, 
    0.071369466280513, 0.144230769230769, 0.117259414225941, 
    0.260571428571429, 0.186951433586893), Kriminalitaet = c(0.108316593009241, 
    0.083678113363674, 0.389423076923077, 0.139330543933054, 
    0.334857142857143, 0.216500877706261), Auslaender = c(0.00715146645239052, 
    0.0212039718659495, 0.0480769230769231, 0.0550209205020921, 
    0.0114285714285714, 0), Umweltbelastung = c(0.108879067898755, 
    0.0846607364501448, 0, 0.143828451882845, 0.376, 0.228203627852545
    ), Einr..f..Kinder = c(0.0693451185214946, 0.0825403392635499, 
    0.0144230769230769, 0.0527196652719665, 0, 0.0444704505558806
    ), Einr..f..Jugendliche = c(0, 0.0934526272238312, 0, 0, 
    0, 0.000877706260971328), count = c(1466, 1821, 81, 1491, 
    330, 793), cluster = c(1, 2, 3, 4, 5, 6)), .Names = c("Geschaeft", 
"Gaststaette", "Bank", "Hausarzt", "Einr..F..Aeltere", "Park", 
"Sportstaette", "OEPNV", "Mangel.an.Gruenflaechen", "Kriminalitaet", 
"Auslaender", "Umweltbelastung", "Einr..f..Kinder", "Einr..f..Jugendliche", 
"count", "cluster"), row.names = c(NA, -6L), class = "data.frame")

我用

排序

mdf <- melt(nbhpp[,-15], id.vars = 'cluster')
mdf <- transform(mdf, variable = reorder(variable, value, mean), y = cluster)

并用

绘图

ggplot(mdf, aes(x=variable, y=value, group=cluster, colour=factor(cluster))) + 
  geom_line() + 
  scale_y_continuous('Anteile', formatter = "percent") +
  scale_colour_hue(name='Cluster') +
  xlab('Infrastrukturmerkmal') +
  theme_bw() +
  opts(axis.text.x = theme_text(angle=90, hjust=1), legend.position = "none") +
  facet_wrap(~cluster, ncol=3)

enter image description here

如果我理解正确，转换函数会按平均值对数据进行排序。但是，如何将这些平均值作为灰线包含在每个图中？

感谢您的帮助

更新：

只是为了澄清：

如果我查看重新排序语句的输出

with(mdf, reorder(variable, value, mean))

比我得到以下属性：

attr(,"scores")
   Einr..f..Jugendliche        Einr..F..Aeltere              Auslaender            Sportstaette 
             0.01572172              0.01583642              0.02381364              0.02902631 
               Hausarzt                    Bank               Geschaeft         Einr..f..Kinder 
             0.03211500              0.03630061              0.04076876              0.04391644 
            Gaststaette                    Park                   OEPNV Mangel.an.Gruenflaechen 
             0.05051310              0.06799505              0.13051918              0.14452739 
        Umweltbelastung           Kriminalitaet 
             0.15692865              0.21201772

从左（最低）到右（最高）的图中排序。问题是，如何使用这些属性绘制一条线......

Answer 1

编辑回答

要添加具有群集平均值的行，您需要构造包含数据的data.frame。您可以从mdf：

中提取值

meanscores <- attributes(mdf$variable)$scores
meandf <- data.frame(
  variable = rep(names(meanscores), 6),
  value    = rep(unname(meanscores), 6),
  cluster  = rep(1:6, each=14)
  )

然后使用geom_line绘图：

ggplot(mdf, aes(x=variable, y=value, group=cluster, colour=factor(cluster))) + 
  geom_line() + 
  scale_y_continuous('Anteile', formatter = "percent") +
  scale_colour_hue(name='Cluster') +
  xlab('Infrastrukturmerkmal') +
  theme_bw() +
  opts(axis.text.x = theme_text(angle=90, hjust=1), legend.position = "none") +
  facet_wrap(~cluster, ncol=3) +
  geom_line(data=meandf, aes(x=variable, y=value), colour="grey50")

enter image description here

原始答案

我原来的解释是你想要一条具有整体手段的水平线。

只需在地块中添加geom_hline图层，然后将yintercept映射到mean(value)：

ggplot(mdf, aes(x=variable, y=value, group=cluster, colour=factor(cluster))) + 
  geom_line() + 
  scale_y_continuous('Anteile', formatter = "percent") +
  scale_colour_hue(name='Cluster') +
  xlab('Infrastrukturmerkmal') +
  theme_bw() +
  opts(axis.text.x = theme_text(angle=90, hjust=1), legend.position = "none") +
  facet_wrap(~cluster, ncol=3) +
  geom_hline(aes(yintercept=mean(value)), colour="grey50")

enter image description here

Answer 2

创建一个包含每个组的平均值的数据框。在R中有很多种方法可以做到这一点，例如，

means <- ddply(mdf, .(y), summarise, mean = mean(value))

（在这种情况下，似乎每个方面的值都相同。）

现在绘制为你的情节添加一条水平线。假设它之前被称为p，

p + geom_hline(aes(yintercept = mean), data = means)

绘制facet_wrap中的平均线

2 个答案:

编辑回答

原始答案