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我有一个要读入 R 的 DAT 文件，但是当我导入数据时，它一直显示我有 10 个列/变量（来自第一行），而实际上，它实际上应该是 29 个列/变量。我该如何解决这个问题？

记事本上的 DAT 文件示例：

smsa66 smsa76 nearc2 nearc4 nearc4a nearc4b ed76 ed66 age76 daded
nodaded momed nomomed momdad14 sinmom14 step14 south66 south76
lwage76 famed black wage76 enroll76 kww iqscore mar76 libcrd14
exp76 exp762

        1          1          0          0          0          0          7
        5         29       9.94          1      10.25          1          1
        0          0          0          0   6.306275          9          1
      548          0         15          .          1          0         16
      256
        1          1          0          0          0          0         12
       11         27          8          0          8          0          1
        0          0          0          0   6.175867          8          0
      481          0         35         93          1          1          9
       81
        1          1          0          0          0          0         12
       12         34         14          0         12          0          1
        0          0          0          0   6.580639          2          0
      721          0         42        103          1          1         16
      256
        1          1          1          1          1          0         11
       11         27         11          0         12          0          1
        0          0          0          0   5.521461          6          0
      250          0         25         88          1          1         10
      100
        1          1          1          1          1          0         12
       12         34          8          0          7          0          1
        0          0          0          0   6.591674          8          0
      729          0         34        108          1          0         16
      256
        1          1          1          1          1          0         12
       11         26          9          0         12          0          1
        0          0          0          0   6.214608          6          0
      500          0         38         85          1          1          8
       64
        1          1          1          1          1          0         18
       16         33         14          0         14          0          1
        0          0          0          0   6.336826          1          0
      565          0         41        119          1          1          9
       81
        1          1          1          1          1          0         14
       13         29         14          0         14          0          1
        0          0          0          0   6.410175          1          0
      608          0         46        108          1          1          9
       81
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1 回答 1

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txt1<-"    smsa66 smsa76 nearc2 nearc4 nearc4a nearc4b ed76 ed66 age76 daded
    nodaded momed nomomed momdad14 sinmom14 step14 south66 south76
    lwage76 famed black wage76 enroll76 kww iqscore mar76 libcrd14
    exp76 exp762"

txt2 <-    
"            1          1          0          0          0          0          7
            5         29       9.94          1      10.25          1          1
            0          0          0          0   6.306275          9          1
          548          0         15          NA          1          0         16
          256
            1          1          0          0          0          0         12
           11         27          8          0          8          0          1
            0          0          0          0   6.175867          8          0
          481          0         35         93          1          1          9
           81
            1          1          0          0          0          0         12
           12         34         14          0         12          0          1
            0          0          0          0   6.580639          2          0
          721          0         42        103          1          1         16
          256
            1          1          1          1          1          0         11
           11         27         11          0         12          0          1
            0          0          0          0   5.521461          6          0
          250          0         25         88          1          1         10
          100
            1          1          1          1          1          0         12
           12         34          8          0          7          0          1
            0          0          0          0   6.591674          8          0
          729          0         34        108          1          0         16
          256
            1          1          1          1          1          0         12
           11         26          9          0         12          0          1
            0          0          0          0   6.214608          6          0
          500          0         38         85          1          1          8
           64
            1          1          1          1          1          0         18
           16         33         14          0         14          0          1
            0          0          0          0   6.336826          1          0
          565          0         41        119          1          1          9
           81
            1          1          1          1          1          0         14
           13         29         14          0         14          0          1
            0          0          0          0   6.410175          1          0
          608          0         46        108          1          1          9
           81"

现在代码：

inp <- scan(text=txt2, what="numeric")
inmat <- matrix( as.numeric(inp), ncol=29, byrow=TRUE)
dfrm <- as.data.frame(inmat)
scan(text=txt1, what="")
Read 29 items
 [1] "smsa66"   "smsa76"   "nearc2"   "nearc4"   "nearc4a"  "nearc4b"  "ed76"    
 [8] "ed66"     "age76"    "daded"    "nodaded"  "momed"    "nomomed"  "momdad14"
[15] "sinmom14" "step14"   "south66"  "south76"  "lwage76"  "famed"    "black"   
[22] "wage76"   "enroll76" "kww"      "iqscore"  "mar76"    "libcrd14" "exp76"   
[29] "exp762"  
names(dfrm) <- scan(text=txt1, what="")
#Read 29 items
 dfrm
#-----------------------
  smsa66 smsa76 nearc2 nearc4 nearc4a nearc4b ed76 ed66 age76 daded nodaded momed nomomed
1      1      1      0      0       0       0    7    5    29  9.94       1 10.25       1
2      1      1      0      0       0       0   12   11    27     8       0     8       0
3      1      1      0      0       0       0   12   12  
snipped remainder of output

最后结果：

str(dfrm)
'data.frame':   8 obs. of  29 variables:
 $ smsa66  : num  1 1 1 1 1 1 1 1
 $ smsa76  : num  1 1 1 1 1 1 1 1
 $ nearc2  : num  0 0 0 1 1 1 1 1
 $ nearc4  : num  0 0 0 1 1 1 1 1
 $ nearc4a : num  0 0 0 1 1 1 1 1
 $ nearc4b : num  0 0 0 0 0 0 0 0
 $ ed76    : num  7 12 12 11 12 12 18 14
 $ ed66    : num  5 11 12 11 12 11 16 13
 $ age76   : num  29 27 34 27 34 26 33 29
 $ daded   : num  9.94 8 14 11 8 9 14 14
 $ nodaded : num  1 0 0 0 0 0 0 0
 $ momed   : num  10.2 8 12 12 7 ...
 $ nomomed : num  1 0 0 0 0 0 0 0
 $ momdad14: num  1 1 1 1 1 1 1 1
 $ sinmom14: num  0 0 0 0 0 0 0 0
 $ step14  : num  0 0 0 0 0 0 0 0
 $ south66 : num  0 0 0 0 0 0 0 0
 $ south76 : num  0 0 0 0 0 0 0 0
 $ lwage76 : num  6.31 6.18 6.58 5.52 6.59 ...
 $ famed   : num  9 8 2 6 8 6 1 1
 $ black   : num  1 0 0 0 0 0 0 0
 $ wage76  : num  548 481 721 250 729 500 565 608
 $ enroll76: num  0 0 0 0 0 0 0 0
 $ kww     : num  15 35 42 25 34 38 41 46
 $ iqscore : num  NA 93 103 88 108 85 119 108
 $ mar76   : num  1 1 1 1 1 1 1 1
 $ libcrd14: num  0 1 1 1 0 1 1 1
 $ exp76   : num  16 9 16 10 16 8 9 9
 $ exp762  : num  256 81 256 100 256 64 81 81
于 2013-10-17T22:39:13.957 回答