On Tue, May 10, 2011 at 3:09 PM, David Winsemius <dwinsem...@comcast.net>
wrote:
>
> On May 10, 2011, at 3:18 AM, noxyp...@gmail.com wrote:
>
>> On Fri, May 6, 2011 at 7:41 PM, David Winsemius <dwinsem...@comcast.net>
>> wrote:
>>>
>>> On May 6, 2011, at 11:35 AM, Pete Pete wrote:
>>>
>>>>
>>>> Gabor Grothendieck wrote:
>>>>>
>>>>> On Tue, Dec 7, 2010 at 11:30 AM, Pete Pete <noxyp...@gmail.com>
>>>>> wrote:
>>>>>>
>>>>>> Hi,
>>>>>> consider the following two dataframes:
>>>>>> x1=c("232","3454","3455","342","13")
>>>>>> x2=c("1","1","1","0","0")
>>>>>> data1=data.frame(x1,x2)
>>>>>>
>>>>>> y1=c("232","232","3454","3454","3455","342","13","13","13","13")
>>>>>> y2=c("E1","F3","F5","E1","E2","H4","F8","G3","E1","H2")
>>>>>> data2=data.frame(y1,y2)
>>>>>>
>>>>>> I need a new column in dataframe data1 (x3), which is either 0 or 1
>>>>>> depending if the value "E1" in y2 of data2 is true while x1=y1. The
>>>>>> result
>>>>>> of data1 should look like this:
>>>>>> x1 x2 x3
>>>>>> 1 232 1 1
>>>>>> 2 3454 1 1
>>>>>> 3 3455 1 0
>>>>>> 4 342 0 0
>>>>>> 5 13 0 1
>>>>>>
>>>>>> I think a SQL command could help me but I am too inexperienced with
it
>>>>>> to
>>>>>> get there.
>>>>>>
>>>>>
>>>>> Try this:
>>>>>
>>>>>> library(sqldf)
>>>>>> sqldf("select x1, x2, max(y2 = 'E1') x3 from data1 d1 left join data2
>>>>>> d2
>>>>>> on (x1 = y1) group by x1, x2 order by d1.rowid")
>>>>>
>>>>> x1 x2 x3
>>>>> 1 232 1 1
>>>>> 2 3454 1 1
>>>>> 3 3455 1 0
>>>>> 4 342 0 0
>>>>> 5 13 0 1
>>>>>
>>>>>
>>> snipped Gabor's sig
>>>>
>>>> That works pretty cool but I need to automate this a bit more. Consider
>>>> the
>>>> following example:
>>>>
>>>> list1=c("A01","B04","A64","G84","F19")
>>>>
>>>> x1=c("232","3454","3455","342","13")
>>>> x2=c("1","1","1","0","0")
>>>> data1=data.frame(x1,x2)
>>>>
>>>> y1=c("232","232","3454","3454","3455","342","13","13","13","13")
>>>> y2=c("E13","B04","F19","A64","E22","H44","F68","G84","F19","A01")
>>>> data2=data.frame(y1,y2)
>>>>
>>>> I want now to creat a loop, which creates for every value in list1 a
new
>>>> binary variable in data1. Result should look like:
>>>> x1 x2 A01 B04 A64 G84 F19
>>>> 232 1 0 1 0 0 0
>>>> 3454 1 0 0 1 0 1
>>>> 3455 1 0 0 0 0 0
>>>> 342 0 0 0 0 0 0
>>>> 13 0 1 0 0 1 1
>>>
>>> Loops!?! We don't nee no steenking loops!
>>>
>>>> xtb <- with(data2, table(y1,y2))
>>>> cbind(data1, xtb[match(data1$x1, rownames(xtb)), ] )
>>>
>>> x1 x2 A01 A64 B04 E13 E22 F19 F68 G84 H44
>>> 232 232 1 0 0 1 1 0 0 0 0 0
>>> 3454 3454 1 0 1 0 0 0 1 0 0 0
>>> 3455 3455 1 0 0 0 0 1 0 0 0 0
>>> 342 342 0 0 0 0 0 0 0 0 0 1
>>> 13 13 0 1 0 0 0 0 1 1 1 0
>>>
>>> I am guessing that you were to ... er, busy? ... to complete the table?
>>>
>>> --
>>>
>>> David Winsemius, MD
>>> West Hartford, CT
>>>
>>>
>>
>> Thanks a lot! Pretty simple. I am so much used to SQLDF right now.
>>
>> So how would you handle more complicated strings like that:
>> y1=c("232","232", "232", "3454","3454","3455","342","13","13","13","13")
>> y2=c("E13","B04 A01 F19","B04","F19","A64 G84 A05","E22","H44
>> C35","F68","G84","F19","A01")
>> data2=data.frame(y1,y2)
>>
>> Where you want to extract for instance all "A01" from the strings?
>
> I think you need either to explain what you want in more words of the
> English language or to offer an example of the desired output. I suspect
you
> did not want something as simple as this:
>
>> A01.instances <- grep("A01" , data2$y2)
>> A01.instances
> [1] 2 11
>> data2[A01.instances, ]
> y1 y2
> 2 232 B04 A01 F19
> 11 13 A01
>
> Or maybe you did?
>
> --
> David Winsemius, MD
> West Hartford, CT
>
>
No, that was not my intention. Consider the following example:
list1=c("A01","B04","A64","G84","F19") # My "substrings" to screen for in
> data2
>
>
> x1=c("232","3454","3455","342","13")
> x2=c("1","1","1","0","0")
> data1=data.frame(x1,x2) # Target dataframe where the 5 new binary variables
> (namely from list1) are added
>
>
> y1=c("232","232", "232", "3454","3454","3455","342","13","13","13","13")
> y2=c("E133","B04 A01A F194","B04","F19","A642 G84 A05","E223","H44
> C35","F68","G84","F19","A01")
> data2=data.frame(y1,y2) # Dataframe to be screen by list1
>
Result should look like this:
x1 x2 A01 B04 A64 G84 F19
> 232 1 1 1 0 0 0
> 3454 1 0 0 1 0 1
> 3455 1 0 0 0 0 0
> 342 0 0 0 0 0 0
> 13 0 1 0 0 1 1
>
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