将 data.frame 写入文本文件时的奇怪输出答案

【问题标题】：Weird output when writing a data.frame to a text file将 data.frame 写入文本文件时的奇怪输出
【发布时间】：2014-06-30 15:53:23
【问题描述】：

在使用 R 将数据框写入文本文件时，我不断收到奇怪的输出。我在使用 write.csv()、write.csv2() 和 write.table() 时遇到了同样的问题。

我有一个data.frame，它是通过使用rbind() 将多个data.frames 绑定在一起创建的，这些rbind() 以前是较大data.frame 的子集。它被称为“提取”，我正在尝试将除第一列（大文本字符串）之外的每一列写入 txt 文件。

> dim(extract)
[1] 1001   16

> extract[1:5,2:16]
          latitude    longitude WordCount English Common Tagalog Bikol Cebuano Hiligaynon Ilocano Kapampangan Pangasinense Waray Zam Spanish
20     20.45164941  121.9671742         7       1      0       0     3       0          0       0           0            0     0   0       0
77     20.45164941  121.9671742         7       1      0       0     3       0          0       0           0            0     0   0       0
106    20.45164941  121.9671742         7       1      0       0     3       0          0       0           0            0     0   0       0
48670  20.45164941  121.9671742         7       1      0       0     3       0          0       0           0            0     0   0       0
94831   8.19183664 124.17909375        13       8      2       0     3       0          0       0           0            0     0   0       0

当我这样做时

> write.csv(extract[,2:16], 'extract 6-30.txt', row.names=FALSE)

我的表将前两项纬度和经度视为列，然后为表中的每个单独项目在列中的每个项目的串联列表。所以，例如：

> write.csv(extract[1:5,2:16], 'extract 6-29.txt', row.names=FALSE)

产生以下文本文件：

"latitude","longitude","WordCount","English","Common","Tagalog","Bikol","Cebuano","Hiligaynon","Ilocano","Kapampangan","Pangasinense","Waray","Zam","Spanish"
    "20.45164941","121.9671742",c(7, 7, 7, 7, 13),c(1, 1, 1, 1, 8),c(0, 0, 0, 0, 2),c(0, 0, 0, 0, 0),c(3, 3, 3, 3, 3),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0)
    "20.45164941","121.9671742",c(7, 7, 7, 7, 13),c(1, 1, 1, 1, 8),c(0, 0, 0, 0, 2),c(0, 0, 0, 0, 0),c(3, 3, 3, 3, 3),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0)
    "20.45164941","121.9671742",c(7, 7, 7, 7, 13),c(1, 1, 1, 1, 8),c(0, 0, 0, 0, 2),c(0, 0, 0, 0, 0),c(3, 3, 3, 3, 3),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0)
    "20.45164941","121.9671742",c(7, 7, 7, 7, 13),c(1, 1, 1, 1, 8),c(0, 0, 0, 0, 2),c(0, 0, 0, 0, 0),c(3, 3, 3, 3, 3),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0)
    "8.19183664","124.17909375",c(7, 7, 7, 7, 13),c(1, 1, 1, 1, 8),c(0, 0, 0, 0, 2),c(0, 0, 0, 0, 0),c(3, 3, 3, 3, 3),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0),c(0, 0, 0, 0, 0)

我缺少一些论点吗？我尝试过使用和不使用 row.names，以及使用带有各种不同分隔符的 write.table。感谢您的帮助，如果您有更多问题，请告诉我。我相信这可能与数据框的创建方式有关。抱歉，如果已经问过这个问题，但我遇到的这个具体问题很难搜索。

编辑：所以使用 dput 产量：

> dput(extract[1:5,2:16])
structure(list(latitude = c("20.45164941", "20.45164941", "20.45164941", 
"20.45164941", "8.19183664"), longitude = c("121.9671742", "121.9671742", 
"121.9671742", "121.9671742", "124.17909375"), WordCount = structure(list(
    WordCount = c(7L, 7L, 7L, 7L, 13L)), .Names = "WordCount", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), English = structure(list(
    English = c(1L, 1L, 1L, 1L, 8L)), .Names = "English", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Common = structure(list(
    Common = c(0L, 0L, 0L, 0L, 2L)), .Names = "Common", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Tagalog = structure(list(
    Tagalog = c(0L, 0L, 0L, 0L, 0L)), .Names = "Tagalog", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Bikol = structure(list(
    Bikol = c(3L, 3L, 3L, 3L, 3L)), .Names = "Bikol", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Cebuano = structure(list(
    Cebuano = c(0L, 0L, 0L, 0L, 0L)), .Names = "Cebuano", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Hiligaynon = structure(list(
    Hiligaynon = c(0L, 0L, 0L, 0L, 0L)), .Names = "Hiligaynon", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Ilocano = structure(list(
    Ilocano = c(0L, 0L, 0L, 0L, 0L)), .Names = "Ilocano", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Kapampangan = structure(list(
    Kapampangan = c(0L, 0L, 0L, 0L, 0L)), .Names = "Kapampangan", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Pangasinense = structure(list(
   Pangasinense = c(0L, 0L, 0L, 0L, 0L)), .Names = "Pangasinense", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Waray = structure(list(
    Waray = c(0L, 0L, 0L, 0L, 0L)), .Names = "Waray", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Zam = structure(list(
    Zam = c(0L, 0L, 0L, 0L, 0L)), .Names = "Zam", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame"), Spanish = structure(list(
    Spanish = c(0L, 0L, 0L, 0L, 0L)), .Names = "Spanish", row.names = c("20", 
"77", "106", "48670", "94831"), class = "data.frame")), .Names = c("latitude", 
"longitude", "WordCount", "English", "Common", "Tagalog", "Bikol", 
"Cebuano", "Hiligaynon", "Ilocano", "Kapampangan", "Pangasinense", 
"Waray", "Zam", "Spanish"), row.names = c(20L, 77L, 106L, 48670L, 
94831L), class = "data.frame")

还有一个总结：

> summary(extract)
    alltweets.text                                                                                                                                                              latitude        
 Grabe. Kasanok masungbatan nu ana nakaturog nak idin. 1AM kano ngamin idin. Haha. \xed\xa0\xbd\xed\xb1\x8a\xed\xa0\xbd\xed\xb1\x8a                                 :  9   Length:1001       
 @MitchyyWong mejo mejo lang pud hahaha ikaw ang hinfi talaga ba haha labyu                                                                           :  8                 Class :character  
 #EvictLoisa nakaka inis panoorin sa tv screen di na maganda tingnan palayasin nayan ngaung saturday! #PBBStopAndStare                                :  8                 Mode  :character  
 Lionel Messi for breakfast! \xed\xa0\xbd\xed\xb8\x9c Happy Monday.. #ARG vs #BIH #WorldCup2014                                                              :  8                            
 ngano lami man kaayo ang kan.on oy? ilabi nag parisan ug bulad ug ginamos. ginoo ko tabang!                                                          :  8                                   
 "@IndayBanat: Ang taong pinakamahirap tanggalin sa isipan mo, ay yong taong kahit hindi kayo pero pinapasaya ka at binubuo ang araw mo." \xed\xa0\xbd\xed\xb8\xad:  7                       
 (Other)                                                                                                                                              :953                                   
  longitude         WordCount.WordCount   English.English      Common.Common     Tagalog.Tagalog      Bikol.Bikol     Cebuano.Cebuano   Hiligaynon.Hiligaynon  Ilocano.Ilocano  
 Length:1001        Min.   : 3.000000   Min.   : 0.000000   Min.   : 0.000000   Min.   :0.000000   Min.   :0.00000   Min.   :0.000000   Min.   :0.000000      Min.   :0.000000  
 Class :character   1st Qu.: 9.000000   1st Qu.: 1.000000   1st Qu.: 2.000000   1st Qu.:0.000000   1st Qu.:0.00000   1st Qu.:0.000000   1st Qu.:0.000000      1st Qu.:0.000000  
 Mode  :character   Median :12.000000   Median : 2.000000   Median : 4.000000   Median :1.000000   Median :0.00000   Median :0.000000   Median :0.000000      Median :0.000000  
                    Mean   :12.384615   Mean   : 2.298701   Mean   : 4.074925   Mean   :1.599401   Mean   :0.07992   Mean   :0.418581   Mean   :0.140859      Mean   :0.305694  
                    3rd Qu.:15.000000   3rd Qu.: 3.000000   3rd Qu.: 6.000000   3rd Qu.:3.000000   3rd Qu.:0.00000   3rd Qu.:0.000000   3rd Qu.:0.000000      3rd Qu.:0.000000  
                    Max.   :22.000000   Max.   :15.000000   Max.   :13.000000   Max.   :7.000000   Max.   :4.00000   Max.   :5.000000   Max.   :4.000000      Max.   :4.000000  

 Kapampangan.Kapampangan Pangasinense.Pangasinense     Waray.Waray       Zam.Zam    Spanish.Spanish  
 Min.   :0.00000         Min.   :0.000000          Min.   : 0.000000   Min.   :0   Min.   :0.000000  
 1st Qu.:0.00000         1st Qu.:0.000000          1st Qu.: 0.000000   1st Qu.:0   1st Qu.:0.000000  
 Median :0.00000         Median :0.000000          Median : 0.000000   Median :0   Median :0.000000  
 Mean   :0.26973         Mean   :0.076923          Mean   : 0.818182   Mean   :0   Mean   :0.367632  
 3rd Qu.:0.00000         3rd Qu.:0.000000          3rd Qu.: 1.000000   3rd Qu.:0   3rd Qu.:1.000000  
 Max.   :8.00000         Max.   :5.000000          Max.   :10.000000   Max.   :0   Max.   :5.000000

还有一个字符串列的示例：

> extract$alltweets.text[1:10]
 [1] Helo #Payi!! #lobster!! #happyfiesta diptan!! \xed\xa0\xbc\xed\xbe\x89\xed\xa0\xbc\xed\xbe\x8a\xed\xa0\xbd\xed\xb8\x8d\xed\xa0\xbd\xed\xb1\x8c @ Diptan, Basco,Batanes http://t.co/rZy4QlIwxW
 [2] Helo #Payi!! #lobster!! #happyfiesta diptan!! \xed\xa0\xbc\xed\xbe\x89\xed\xa0\xbc\xed\xbe\x8a\xed\xa0\xbd\xed\xb8\x8d\xed\xa0\xbd\xed\xb1\x8c @ Diptan, Basco,Batanes http://t.co/rZy4QlIwxW
 [3] Helo #Payi!! #lobster!! #happyfiesta diptan!! \xed\xa0\xbc\xed\xbe\x89\xed\xa0\xbc\xed\xbe\x8a\xed\xa0\xbd\xed\xb8\x8d\xed\xa0\xbd\xed\xb1\x8c @ Diptan, Basco,Batanes http://t.co/rZy4QlIwxW
 [4] Helo #Payi!! #lobster!! #happyfiesta diptan!! \xed\xa0\xbc\xed\xbe\x89\xed\xa0\xbc\xed\xbe\x8a\xed\xa0\xbd\xed\xb8\x8d\xed\xa0\xbd\xed\xb1\x8c @ Diptan, Basco,Batanes http://t.co/rZy4QlIwxW
 [5] Here is what's cooking at Gloria's Lechon in Iligan City! Who wants lechon manok? @ Gloria's Lechon http://t.co/9gxv4GxgIW                                       
 [6] Here is what's cooking at Gloria's Lechon in Iligan City! Who wants lechon manok? @ Gloria's Lechon http://t.co/9gxv4GxgIW                                       
 [7] "@PBBabscbn: Pindot, pindot lang! Pindot, pindot lang! #PBBStopAndStare"                                                                                       
 [8] "@PBBabscbn: Pindot, pindot lang! Pindot, pindot lang! #PBBStopAndStare"                                                                                      
 [9] @eyyyorange dae pwede duman. Crowded na duman ta dakulon na boarders. Dae ngani ko duman makaadal tultol ta maribok. Inda matxt na lang ako                      
[10] Pindot pindot lang..pindot pindot pindot lang xD hahahahahaha                                                                                                    
92162 Levels: ⃣ phones are the best \xed��\xed�\u008a _beown eyes tells his soul\nxo xo http://t.co/vzbMmzgdk7 ... 

【问题讨论】：

dput(extract[1:5,2:16]) 看起来像什么（或同样表现出这种行为的较小示例）？还有summary(extract)?
请查看编辑@Spacedman
正如我所怀疑的，您可以从str(extract) 看到，您的数据框中有数据框。返回合并步骤并正确执行它们

标签： r dataframe output text-files

【解决方案1】：

如 cmets 所示，您的问题是由于您的 data.frame 的结构造成的。如果您无法从问题的根源解决它，您应该能够通过以下方式解决它：

do.call(data.frame, extract) ## extract is the name of your original data frame

例子：

str(do.call(data.frame, extract))
# 'data.frame':  5 obs. of  15 variables:
# $ latitude    : Factor w/ 2 levels "20.45164941",..: 1 1 1 1 2
# $ longitude   : Factor w/ 2 levels "121.9671742",..: 1 1 1 1 2
# $ WordCount   : int  7 7 7 7 13
# $ English     : int  1 1 1 1 8
# $ Common      : int  0 0 0 0 2
# $ Tagalog     : int  0 0 0 0 0
# $ Bikol       : int  3 3 3 3 3
# $ Cebuano     : int  0 0 0 0 0
# $ Hiligaynon  : int  0 0 0 0 0
# $ Ilocano     : int  0 0 0 0 0
# $ Kapampangan : int  0 0 0 0 0
# $ Pangasinense: int  0 0 0 0 0
# $ Waray       : int  0 0 0 0 0
# $ Zam         : int  0 0 0 0 0
# $ Spanish     : int  0 0 0 0 0

它应该是这样的：

A <- tempfile()
write.csv(do.call(data.frame, extract), A)
readLines(A)
# [1] "\"\",\"latitude\",\"longitude\",\"WordCount\",\"English\",\"Common\",\"Tagalog\",\"Bikol\",\"Cebuano\",\"Hiligaynon\",\"Ilocano\",\"Kapampangan\",\"Pangasinense\",\"Waray\",\"Zam\",\"Spanish\""
# [2] "\"20\",\"20.45164941\",\"121.9671742\",7,1,0,0,3,0,0,0,0,0,0,0,0"                                                                                                                                
# [3] "\"77\",\"20.45164941\",\"121.9671742\",7,1,0,0,3,0,0,0,0,0,0,0,0"                                                                                                                                
# [4] "\"106\",\"20.45164941\",\"121.9671742\",7,1,0,0,3,0,0,0,0,0,0,0,0"                                                                                                                               
# [5] "\"48670\",\"20.45164941\",\"121.9671742\",7,1,0,0,3,0,0,0,0,0,0,0,0"                                                                                                                             
# [6] "\"94831\",\"8.19183664\",\"124.17909375\",13,8,2,0,3,0,0,0,0,0,0,0,0"

【讨论】：