两列的结果出现在R中的同一列中

我有一个包含Sol.grp非数字和年龄数字列的数据框。我试图将年龄平均值和观察值计数存储在两个单独的列中

我使用了以下代码：

示例数据：前20行

sol.grp     age
Account A   29.6
Account B   29.6
WMID        26.9
Qty         1.7
PM          3.0
CS          2043.8
ED          24.3
TM          24.3
Account A   24.3
Account B   133.3
WMID        27.0
Qty         2.1
PM          29.2
CS          29.4
ED          97.8
TM          192.9
Account A   651.6
Account B   148.6
WMID        125.2
Qty         31.1

您可以使用data.table尝试此操作

数据

---

以下来自您自己的代码的代码运行良好：

aggregate(age~sol.grp, data=na.omit(all.tkts), FUN=function(x) c(mean= mean(x), count=length(x)))
    sol.grp   age.mean  age.count
1 Account A  235.16667    3.00000
2 Account B  103.83333    3.00000
3        CS 1036.60000    2.00000
4        ED   61.05000    2.00000
5        PM   16.10000    2.00000
6       Qty   11.63333    3.00000
7        TM  108.60000    2.00000
8      WMID   59.70000    3.00000

避免将data.frame放在aggregate周围，因为aggregate返回data.frame

编辑：

输出的详细信息如下：

> dd = aggregate(age~sol.grp, data=na.omit(all.tkts), FUN=function(x) c(mean= mean(x), count=length(x)))
> str(dd)
'data.frame':   8 obs. of  2 variables:
 $ sol.grp: Factor w/ 8 levels "Account A","Account B",..: 1 2 3 4 5 6 7 8
 $ age    : num [1:8, 1:2] 235.2 103.8 1036.6 61 16.1 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : NULL
  .. ..$ : chr  "mean" "count"
> 
> dd$sol.grp
[1] Account A Account B CS        ED        PM        Qty       TM        WMID     
Levels: Account A Account B CS ED PM Qty TM WMID

> dd$age
           mean count
[1,]  235.16667     3
[2,]  103.83333     3
[3,] 1036.60000     2
[4,]   61.05000     2
[5,]   16.10000     2
[6,]   11.63333     3
[7,]  108.60000     2
[8,]   59.70000     3
> 
> dd$age[,2]
[1] 3 3 2 2 2 3 2 3
> 
> dd$age[,1]
[1]  235.16667  103.83333 1036.60000   61.05000   16.10000   11.63333  108.60000   59.70000

---

最好使用dput显示一个示例数据集，即.dputheaddata，20-do.calldata.frame，aggregate。。。在没有示例数据的情况下未测试。@Mathan无法使用示例数据集重现问题。seed25；all.tkts我现在在末尾添加了示例数据集。谢谢@Mathan我使用您的示例更新版本进行了测试，没有发现任何问题。@Mathan没有问题。我很想知道你是如何得到你在帖子中提到的输出的。：-你是否在你那端尝试了我的代码并得到了相同的结果？@Mathan是的，我做了，唯一的区别是它不会改变“将矩阵强制为数据帧”。第二栏。

 library(data.table)
 res1 <- setDT(all.tkts)[, list(Mean=mean(age, na.rm=TRUE), Count=.N),
                                            keyby=sol.grp]

 res2 <- do.call(data.frame,aggregate(age~sol.grp, 
          data=na.omit(all.tkts), FUN=function(x) c(mean= mean(x), count=length(x))))

 res2 
 #    sol.grp   age.mean age.count
 #1 Account A  235.16667         3
 #2 Account B  103.83333         3
 #3        CS 1036.60000         2
 #4        ED   61.05000         2
 #5        PM   16.10000         2
 #6       Qty   11.63333         3
 #7        TM  108.60000         2
 #8      WMID   59.70000         3

 all.tkts <- structure(list(sol.grp = structure(c(1L, 2L, 8L, 6L, 5L, 3L, 
 4L, 7L, 1L, 2L, 8L, 6L, 5L, 3L, 4L, 7L, 1L, 2L, 8L, 6L), .Label = c("Account A", 
 "Account B", "CS", "ED", "PM", "Qty", "TM", "WMID"), class = "factor"), 
age = c(29.6, 29.6, 26.9, 1.7, 3, 2043.8, 24.3, 24.3, 24.3, 
133.3, 27, 2.1, 29.2, 29.4, 97.8, 192.9, 651.6, 148.6, 125.2, 
31.1)), .Names = c("sol.grp", "age"), class = "data.frame", row.names = c(NA, 
-20L))

aggregate(age~sol.grp, data=na.omit(all.tkts), FUN=function(x) c(mean= mean(x), count=length(x)))
    sol.grp   age.mean  age.count
1 Account A  235.16667    3.00000
2 Account B  103.83333    3.00000
3        CS 1036.60000    2.00000
4        ED   61.05000    2.00000
5        PM   16.10000    2.00000
6       Qty   11.63333    3.00000
7        TM  108.60000    2.00000
8      WMID   59.70000    3.00000

> dd = aggregate(age~sol.grp, data=na.omit(all.tkts), FUN=function(x) c(mean= mean(x), count=length(x)))
> str(dd)
'data.frame':   8 obs. of  2 variables:
 $ sol.grp: Factor w/ 8 levels "Account A","Account B",..: 1 2 3 4 5 6 7 8
 $ age    : num [1:8, 1:2] 235.2 103.8 1036.6 61 16.1 ...
  ..- attr(*, "dimnames")=List of 2
  .. ..$ : NULL
  .. ..$ : chr  "mean" "count"
> 
> dd$sol.grp
[1] Account A Account B CS        ED        PM        Qty       TM        WMID     
Levels: Account A Account B CS ED PM Qty TM WMID

> dd$age
           mean count
[1,]  235.16667     3
[2,]  103.83333     3
[3,] 1036.60000     2
[4,]   61.05000     2
[5,]   16.10000     2
[6,]   11.63333     3
[7,]  108.60000     2
[8,]   59.70000     3
> 
> dd$age[,2]
[1] 3 3 2 2 2 3 2 3
> 
> dd$age[,1]
[1]  235.16667  103.83333 1036.60000   61.05000   16.10000   11.63333  108.60000   59.70000