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如果有人能给我一些指导如何解决矩阵的复杂排序和选择每个子类别中的前 2 个元素，我将不胜感激。

代码：

index<-1:14
metric<-c(0.037777,0.041143,0.041043,0.042056,0.043701,0.042169,0.042134,
          0.046565,0.044638,0.036653,0.046221,0.04033,0.045385,0.043873)
cat_1<-c("California Munis","California Munis","California Munis","California Munis",
         "California Munis","California Munis","California Munis","Corporate Bonds",
         "Corporate Bonds","Corporate Bonds","Government Bonds","Government Bonds",
         "High Yield Bonds","High Yield Bonds")
cat_2<-c("California Munis","Corporate Bonds","Corporate Bonds","Government Bonds",
         "High Yield Bonds","High Yield Bonds","High Yield Bonds","High Yield Bonds",
         "High Yield Bonds","High Yield Bonds","California Munis","California Munis",
         "Corporate Bonds","Corporate Bonds")

data<-data.frame(cbind(index,metric,cat_1,cat_2))

产生以下矩阵

Ind Metric     Cat_1                Cat_2
1   0.037777    California Munis    California Munis
2   0.041143    California Munis    Corporate Bonds
3   0.041043    California Munis    Corporate Bonds
4   0.042056    California Munis    Government Bonds
5   0.043701    California Munis    High Yield Bonds
6   0.042169    California Munis    High Yield Bonds
7   0.042134    California Munis    High Yield Bonds
8   0.046565    Corporate Bonds     High Yield Bonds
9   0.044638    Corporate Bonds     High Yield Bonds
10  0.036653    Corporate Bonds     High Yield Bonds
11  0.046221    Government Bonds    California Munis
12  0.04033     Government Bonds    California Munis
13  0.045385    High Yield Bonds    Corporate Bonds
14  0.043873    High Yield Bonds    Corporate Bonds

鉴于上面的矩阵，我想根据 Cat_1、Cat_2 和 Metric 进行排序。我试过这个：

data[order(data[,3],data[,4],data[,2]),]

但是，如果 Cat_1 和 Cat_2 的条目相同，则它们应该是无关紧要的。例如，“California Munis”&“Corporate Bonds”=“Corporate Bonds”&“California Munis”。我希望得到的结果应该类似于以下矩阵中的结果

Ind Metric      Cat_1               Cat_2               Selection
1   0.037777    California Munis    California Munis    1
2   0.041143    California Munis    Corporate Bonds     1
3   0.041043    California Munis    Corporate Bonds     2
11  0.046221    Government Bonds    California Munis    1
4   0.042056    California Munis    Government Bonds    2
12  0.04033     Government Bonds    California Munis    
5   0.043701    California Munis    High Yield Bonds    1
6   0.042169    California Munis    High Yield Bonds    2
7   0.042134    California Munis    High Yield Bonds    
8   0.046565    Corporate Bonds     High Yield Bonds    1
13  0.045385    High Yield Bonds    Corporate Bonds     2
9   0.044638    Corporate Bonds     High Yield Bonds    
14  0.043873    High Yield Bonds    Corporate Bonds 
10  0.036653    Corporate Bonds     High Yield Bonds

最后一列显示了我需要提取的每个子类别的前 2 行的选择。

任何想法或代码将不胜感激。

谢谢

4

3 回答 3

2

请放弃使用data.frame(cbind(...))。只会让你伤心。

 newdat <- data[ with( data, 
                order( pmax( as.numeric(cat_1), as.numeric(cat_2) ), 
                       pmin( as.numeric(cat_1), as.numeric(cat_2) ) ,
                     - metric) ) , ]
 newdat$selection <- ave(index, 
                         first=pmax( as.numeric(newdat$cat_1), 
                                     as.numeric(newdat$cat_2) ), 
                        second= pmin( as.numeric(newdat$cat_1), 
                                      as.numeric(newdat$cat_2) ) ,
                         FUN=seq)
#-----------------------------------------
> newdat
   index   metric            cat_1            cat_2 selection
1      1 0.037777 California Munis California Munis         1
2      2 0.041143 California Munis  Corporate Bonds         1
3      3 0.041043 California Munis  Corporate Bonds         2
11    11 0.046221 Government Bonds California Munis         1
4      4 0.042056 California Munis Government Bonds         2
12    12 0.040330 Government Bonds California Munis         3
5      5 0.043701 California Munis High Yield Bonds         1
6      6 0.042169 California Munis High Yield Bonds         2
7      7 0.042134 California Munis High Yield Bonds         3
8      8 0.046565  Corporate Bonds High Yield Bonds         1
13    13 0.045385 High Yield Bonds  Corporate Bonds         2
9      9 0.044638  Corporate Bonds High Yield Bonds         3
14    14 0.043873 High Yield Bonds  Corporate Bonds         4
10    10 0.036653  Corporate Bonds High Yield Bonds         5

这里成功的要求是两个 cat 变量中的级别相同。如果不是，那么使它们与levels(.) <- union(levels(cat1, levels(cat_2))

于 2013-11-04T07:26:12.630 回答
1

我扩展我的评论

# introduce combined category
cat3 <- sapply(paste(data$cat_1,data$cat_2,sep=" "),function(x){paste(sort(strsplit(x," ")[[1]]), collapse=" ")})
data$cat_3 <- cat3
# order as desired
data1 <- data[order( cat_3 , -metric), ]
# label and select top 2 in each cat
data1$rankByCat <- unlist(sapply(unique(data1$cat_3), function(mycat, mydf)  {return(1:sum(mydf$cat_3==mycat))}, mydf=data1))
data1[data1$rankByCat < 3, !names(data1)%in%c("cat_3")]
于 2013-11-04T14:29:40.127 回答
0

@andrei

我有以下代码的排序部分：

#concacenate the 2 strings
cat_3<-paste(data[,3],data[,4],sep="  ")

#break the string to 2 (creates a list)
temp_split<-strsplit(cat_3,"  ")

#sort by row
sort_split<-sapply(temp_split,sort)

#bind split
out<-cbind(data,t(sort_split))

这是最好的写法吗？

我将如何从这里开始选择每个类别的前 2 个？

谢谢您的帮助！

于 2013-11-04T04:17:20.223 回答