使用R合并新列中的行

我有一个如下所示的数据框：

ID  X1  X2  X3  X4  X5  X6  X7  X8
202 1   0   895 114 17  21  1   4
202 2   0   130 399 74  19  4   4
202 3   0   364 112 48  12  5   4
202 4   4   104 012 83  81  0   4
203 1   0   895 112 76  49  1   5
203 2   2   950 815 32  35  4   5
203 3   0   3.4 156 69  14  5   5
203 4   0   868 025 71  20  0   5
204 2   0   801 398 51  44  4   8
204 4   4   205 000 14  24  0   8

我想将与ID对应的数据放在一行中。对于一个ID，“X1”列提到的行数不同，“X8”列对于一个ID是相同的，“X2”只包含一个非零值，我只对这个值感兴趣。如果新列的值不可用，则可以将其设置为999。所以，我想最后看起来像：

ID  X8  X2  X3_1    X4_1    X5_1    X6_1    X7_1    X3_2    X4_2    X5_2    X6_2    X7_2    X3_3    X4_3    X5_3    X6_3    X7_3    X3_4    X4_4    X5_4    X6_4    X7_4                                                                            
202 4   4   895     114     17      21      1       130     399     74      19      4       364     112     48      12      5       104     12      83      81      0
203 5   2   895     112     76      49      1       950     815     32      35      4       3.4     156     69      14      5       868     25      71      20      0
204 8   4   999     999     999     999     999     801     398     51      44      4       999     999     999     999     999     205     0       14      24      0

我想用R来做这个。提前感谢您的帮助。

我们可以试试

 res <- Reduce(function(...) merge(..., by = c("ID", "X8"),
           all=TRUE), split(df1[-(2:3)], df1$X1))
 res[is.na(res)] <- 999
 res$X2 <- df1$X2[df1$X2!=0]
 colnames(res) <-make.unique(colnames(res))
 res[c(1:2, 23, 3:22)]
 #   ID X8 X2 X3.x X4.x X5.x X6.x X7.x X3.y X4.y X5.y X6.y X7.y X3.x.1 X4.x.1 X5.x.1 X6.x.1 X7.x.1 X3.y.1 X4.y.1 X5.y.1 X6.y.1 X7.y.1
 #1 202  4  4  895  114   17   21    1  130  399   74   19    4  364.0    112     48     12      5    104     12     83     81      0
 #2 203  5  2  895  112   76   49    1  950  815   32   35    4    3.4    156     69     14      5    868     25     71     20      0
 #3 204  8  4  999  999  999  999  999  801  398   51   44    4  999.0    999    999    999    999    205      0     14     24      0

或使用以下命令：

library(reshape2)
> df.melt = melt(df, id.vars =c("ID", "X1","X2", "X8"))
> df.cast = dcast(df.melt, ID + X8 ~variable + X1 , fill = 999)
> df.cast
   ID X8 X3_1 X3_2 X3_3 X3_4 X4_1 X4_2 X4_3 X4_4 X5_1 X5_2 X5_3 X5_4 X6_1 X6_2 X6_3 X6_4 X7_1 X7_2 X7_3 X7_4
1 202  4  895  130  364  104  114  399  112   12   17   74   48   83   21   19   12   81    1    4    5    0
2 203  5  895  950  430  868  112  815  156   25   76   32   69   71   49   35   14   20    1    4    5    0
3 204  8  999  801  999  205  999  398  999    0  999   51  999   14  999   44  999   24  999    4  999    0

如果需要，合并X2

> df.merge = merge(df.cast, df[df$X2!=0,c("ID", "X2")], by="ID", all.x =TRUE)
> df.new =df.merge[, c(1,ncol(df.merge), 2:(ncol(df.merge)-1))]
> df.new
   ID X2 X8 X3_1 X3_2 X3_3 X3_4 X4_1 X4_2 X4_3 X4_4 X5_1 X5_2 X5_3 X5_4 X6_1 X6_2 X6_3 X6_4 X7_1 X7_2 X7_3 X7_4
1 202  4  4  895  130  364  104  114  399  112   12   17   74   48   83   21   19   12   81    1    4    5    0
2 203  2  5  895  950  430  868  112  815  156   25   76   32   69   71   49   35   14   20    1    4    5    0
3 204  4  8  999  801  999  205  999  398  999    0  999   51  999   14  999   44  999   24  999    4  999    0

---

这可以通过使用基数R来实现：（1）将

ID

和

X8

列都视为

idvar

列，（2）将

X1

列视为

timevar

列，（3）在重塑后仅合并

ID

上非零的

X2

行，以及（4）重塑后用999替换NAs：

df <- data.frame(ID=c(202L,202L,202L,202L,203L,203L,203L,203L,204L,204L),X1=c(1L,2L,3L,4L,1L,2L,3L,4L,2L,4L),X2=c(0L,0L,0L,4L,0L,2L,0L,0L,0L,4L),X3=c(895,130,364,104,895,950,3.4,868,801,205),X4=c(114L,399L,112L,12L,112L,815L,156L,25L,398L,0L),X5=c(17L,74L,48L,83L,76L,32L,69L,71L,51L,14L),X6=c(21L,19L,12L,81L,49L,35L,14L,20L,44L,24L),X7=c(1L,4L,5L,0L,1L,4L,5L,0L,4L,0L),X8=c(4L,4L,4L,4L,5L,5L,5L,5L,8L,8L));
res <- merge(subset(df[c('ID','X2')],X2!=0L),reshape(df,dir='w',idvar=c('ID','X8'),timevar='X1',drop='X2',sep='_'));
res[is.na(res)] <- 999L;
res;
##    ID X2 X8 X3_1 X4_1 X5_1 X6_1 X7_1 X3_2 X4_2 X5_2 X6_2 X7_2  X3_3 X4_3 X5_3 X6_3 X7_3 X3_4 X4_4 X5_4 X6_4 X7_4
## 1 202  4  4  895  114   17   21    1  130  399   74   19    4 364.0  112   48   12    5  104   12   83   81    0
## 2 203  2  5  895  112   76   49    1  950  815   32   35    4   3.4  156   69   14    5  868   25   71   20    0
## 3 204  4  8  999  999  999  999  999  801  398   51   44    4 999.0  999  999  999  999  205    0   14   24    0

---

df是否已经查看了
reformae2
包？
df <- data.frame(ID=c(202L,202L,202L,202L,203L,203L,203L,203L,204L,204L),X1=c(1L,2L,3L,4L,1L,2L,3L,4L,2L,4L),X2=c(0L,0L,0L,4L,0L,2L,0L,0L,0L,4L),X3=c(895,130,364,104,895,950,3.4,868,801,205),X4=c(114L,399L,112L,12L,112L,815L,156L,25L,398L,0L),X5=c(17L,74L,48L,83L,76L,32L,69L,71L,51L,14L),X6=c(21L,19L,12L,81L,49L,35L,14L,20L,44L,24L),X7=c(1L,4L,5L,0L,1L,4L,5L,0L,4L,0L),X8=c(4L,4L,4L,4L,5L,5L,5L,5L,8L,8L));
res <- merge(subset(df[c('ID','X2')],X2!=0L),reshape(df,dir='w',idvar=c('ID','X8'),timevar='X1',drop='X2',sep='_'));
res[is.na(res)] <- 999L;
res;
##    ID X2 X8 X3_1 X4_1 X5_1 X6_1 X7_1 X3_2 X4_2 X5_2 X6_2 X7_2  X3_3 X4_3 X5_3 X6_3 X7_3 X3_4 X4_4 X5_4 X6_4 X7_4
## 1 202  4  4  895  114   17   21    1  130  399   74   19    4 364.0  112   48   12    5  104   12   83   81    0
## 2 203  2  5  895  112   76   49    1  950  815   32   35    4   3.4  156   69   14    5  868   25   71   20    0
## 3 204  4  8  999  999  999  999  999  801  398   51   44    4 999.0  999  999  999  999  205    0   14   24    0