[R] Problems using unique function and !duplicated

[(Ted Harding)]

On 28-Feb-11 15:51:17, JonC wrote:
> Hi, I am trying to simultaneously remove duplicate variables from two
> or more
> variables in a small R data.frame. I am trying to reproduce the SAS
> statements from a Proc Sort with Nodupkey for those familiar with SAS. 
> 
> Here's my example data : 
> 
> test <- read.csv("test.csv", sep=",", as.is=TRUE)
>> test
>       date var1 var2 num1 num2
> 1 28/01/11    a    1  213   71
> 2 28/01/11    b    1  141   47
> 3 28/01/11    c    2  867  289
> 4 29/01/11    a    2  234   78
> 5 29/01/11    b    2  666  222
> 6 29/01/11    c    2  912  304
> 7 30/01/11    a    3  417  139
> 8 30/01/11    b    3  108   36
> 9 30/01/11    c    2  288   96
> 
> I am trying to obtain the following, where duplicates of date AND var2
> are removed from the above data.frame.
> 
> date                  var1    var2    num1    num2
> 28/01/2011    a       1       213            71
> 28/01/2011    c       2       867            289
> 29/01/2011    a       2       234            78
> 30/01/2011    c       2       288            96
> 30/01/2011    a       3       417            139
> 
> 
> 
> If I use the !duplicated function with one variable everything works
> fine.
> However I wish to remove duplicates of both Date and var2.
> 
>  test[!duplicated(test$date),]
>         date var1 var2 num1 num2
> 1 0011-01-28    a    1  213   71
> 4 0011-01-29    a    2  234   78
> 7 0011-01-30    a    3  417  139
> 
> test2 <- test[!duplicated(test$date),!duplicated(test$var2),]
> Error in `[.data.frame`(test, !duplicated(test$date),
> !duplicated(test$var2),  :   undefined columns selected
> I got different errors when using the unique() function. 
> 
> Can anybody solve this ? 
> 
> Thanks in advance.
> Jon

The following gives what you state you wish to obtain (though
not quite in the same order of rows. Call the original dataframe 'df':

  df
  #       date var1 var2 num1 num2
  # 1 28/01/11    a    1  213   71
  # 2 28/01/11    b    1  141   47
  # 3 28/01/11    c    2  867  289
  # 4 29/01/11    a    2  234   78
  # 5 29/01/11    b    2  666  222
  # 6 29/01/11    c    2  912  304
  # 7 30/01/11    a    3  417  139
  # 8 30/01/11    b    3  108   36
  # 9 30/01/11    c    2  288   96

  ix <-which(duplicated(data.frame(df$date,df$var2)))
  ix
  # [1] 2 5 6 8

  df[-ix,]
  #       date var1 var2 num1 num2
  # 1 28/01/11    a    1  213   71
  # 3 28/01/11    c    2  867  289
  # 4 29/01/11    a    2  234   78
  # 7 30/01/11    a    3  417  139
  # 9 30/01/11    c    2  288   96

Does this help?
Ted.
PS I'm posting this from a temporarily subscribed alternative
address (for testing purposes) instead of my usual
ted.harding at wlandres.net

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Date: 28-Feb-11                                       Time: 16:19:59
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