将字符串拆分为R中的新行 [英] Splitting a string into new rows in R

问题描述

我有一个数据集如下：

 国家地区分子项目代码
 IND NA PB102 FR206985511 
 THAI AP PB103 BA-107603 / F000113361 / 107603 
 LUXE NA PB105 1012701 / SGP-1012701 / F041701000 
 IND AP PB106 AU206985211 / CA-F206985211 
 THAI HP PB107 F034702000 / 1010701 / SGP -1010701 
 BANG NA PB108 F000007970 / 25781/20009021 
  

我要根据字符串进行拆分 ITEMCODE 列中的值 / ，并为每个条目创建一个新行。

例如，所需的输出将是：

 国家地区分子项目代码
 IND NA PB102 FR206985511 
 THAI AP PB103 BA-107603 
 THAI AP PB103 F000113361 
 THAI AP PB103 107603 
 LUXE NA PB105 10127 01 
 LUXE NA PB105 SGP-1012701 
 LUXE NA PB105 F041701000 
 IND AP PB106 AU206985211 
 IND AP PB106 CA-F206985211 
 THAI HP PB107 F034702000 
 THAI HP PB107 1010701 
 THAI HP PB107 SGP-1010701 
 BANG NA PB108 F000007970 
 BANG NA PB108 25781 
 BANG NA PB108 20009021 
  pre> 
 
 
我尝试了以下代码
  library（splitstackshape）
 df2 = concat.split.multiple（df1，Plant.Item.Code，/，direction =long）
  
但收到错误
 错误：内存耗尽（限制达到了）
  
当我尝试 strsplit（）以下错误消息。
  strsplit中的错误（df1 $ Plant.Item.Code，/）：非字符参数
  
您的任何帮助将不胜感激。
解决方案
尝试使用 cSplit 函数使用@Anandas包）。请注意，将返回 data.table 对象，因此请确保已安装此软件包。您可以通过执行 setDF（df2） 来恢复 data.frame （如果您想） p> 
 
 
 库（splitstackshape）
 df2<  -  cSplit（df1，Item.Code，sep =/，方向=长）
 df2 
＃国家地区分子项目编号
＃1：IND NA PB102 FR206985511 
＃2：THAI AP PB103 BA-107603 
 ＃3：THAI AP PB103 F000113361 
＃4：THAI AP PB103 107603 
＃5：LUXE NA PB105 1012701 
＃6：LUXE NA PB105 SGP-1012701 
＃7：LUXE NA PB105 F041701000 
＃8：IND AP PB106 AU206985211 
＃9：IND AP PB106 CA-F206985211 
＃10：THAI HP PB107 F034702000 
＃11：THAI HP PB107 1010701 
＃12：THAI HP PB107 SGP-1010701 
＃13：BANG NA PB108 F000007970 
＃14：BANG NA PB108 25781 
＃15：BANG NA PB108 20009021 
  
 
I have a data set like below:
Country Region    Molecule      Item Code   
    IND     NA       PB102      FR206985511 
   THAI     AP       PB103      BA-107603 / F000113361 / 107603
   LUXE     NA       PB105      1012701 / SGP-1012701 / F041701000
    IND     AP       PB106      AU206985211 / CA-F206985211
   THAI     HP       PB107      F034702000 / 1010701 / SGP-1010701
   BANG     NA       PB108      F000007970/25781/20009021
I want to split based the string values in ITEMCODE column on / and create a new row for each entry.

For instance, the desired output will be:
Country Region Molecule      Item.Code
    IND     NA    PB102    FR206985511
   THAI     AP    PB103      BA-107603
   THAI     AP    PB103     F000113361
   THAI     AP    PB103         107603
   LUXE     NA    PB105        1012701
   LUXE     NA    PB105    SGP-1012701
   LUXE     NA    PB105     F041701000
    IND     AP    PB106    AU206985211
    IND     AP    PB106  CA-F206985211
   THAI     HP    PB107     F034702000
   THAI     HP    PB107        1010701
   THAI     HP    PB107    SGP-1010701
   BANG     NA    PB108     F000007970
   BANG     NA    PB108          25781
   BANG     NA    PB108       20009021
I tried the below code 
library(splitstackshape)
df2=concat.split.multiple(df1,"Plant.Item.Code","/", direction="long")
but got the Error
"Error: memory exhausted (limit reached?)"
When i tried strsplit() i got the below error message.
Error in strsplit(df1$Plant.Item.Code, "/") : non-character argument
Any help from you will be appreciated.
解决方案
Try the cSplit function (as you already using @Anandas package). Note that is will return a data.table object, so make sure you have this package installed. You can revert back to data.frame (if you want to) by doing something like setDF(df2)
library(splitstackshape)
df2 <- cSplit(df1, "Item.Code", sep = "/", direction = "long")
df2
#     Country Region Molecule      Item.Code
#  1:     IND     NA    PB102    FR206985511
#  2:    THAI     AP    PB103      BA-107603 
#  3:    THAI     AP    PB103     F000113361 
#  4:    THAI     AP    PB103         107603
#  5:    LUXE     NA    PB105        1012701 
#  6:    LUXE     NA    PB105    SGP-1012701 
#  7:    LUXE     NA    PB105     F041701000
#  8:     IND     AP    PB106    AU206985211 
#  9:     IND     AP    PB106  CA-F206985211
# 10:    THAI     HP    PB107     F034702000 
# 11:    THAI     HP    PB107        1010701 
# 12:    THAI     HP    PB107    SGP-1010701
# 13:    BANG     NA    PB108     F000007970
# 14:    BANG     NA    PB108          25781
# 15:    BANG     NA    PB108       20009021


                        
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