I get the following message when using the reshape2 package line

> tDat.m<- melt(Dataset)
Using Item, Subject as id variables
> tDatCast<- acast(tDat.m,Subject~Item)
Aggregation function missing: defaulting to length


Note Problem Statement-

convert dataframe


Subject   Item Score
1 Subject 1 Item 1     1
2 Subject 1 Item 2     0
3 Subject 1 Item 3     1
4 Subject 2 Item 1     1
5 Subject 2 Item 2     1
6 Subject 2 Item 3     0

to


  Subject Item 1 Item 2 Item 3 Item 4
1 Subject 1      1      0      1      1
5 Subject 2      1      1      0      0

Note- when I tried using the "wide" method the resultant vector went out of
memory- its a dataset appox 100,000 lines



Websites-
http://decisionstats.com
http://dudeofdata.com


Linkedin- www.linkedin.com/in/ajayohri




On Sat, Oct 30, 2010 at 5:41 PM, Rainer Hurling <rhurlin@gwdg.de> wrote:

> On 30.10.2010 13:50 (UTC+1), Santosh Srinivas wrote:
>
>> A more usable problem input would definitely help ... use dput to send a
>> reproducible sample to the group
>>
>> Think the below should solve your problem
>>
>>  read.csv("Book1.csv")
>>>
>>     Subject   Item Score
>> 1 Subject 1 Item 1     1
>> 2 Subject 1 Item 2     0
>> 3 Subject 1 Item 3     1
>> 4 Subject 2 Item 1     1
>> 5 Subject 2 Item 2     1
>> 6 Subject 2 Item 3     0
>>
>>  library("reshape2")
>>> tDat.m<- melt(tDat)
>>>
>>
>>  tDatCast<- acast(tDat.m,Subject~Item)
>>> tDatCast
>>>
>>           Item 1 Item 2 Item 3
>> Subject 1      1      0      1
>> Subject 2      1      1      0
>>
>
>
> # Or without using package reshape2, only function reshape from stats:
>
> df <- data.frame(Subject=
>                   c("Subject 1","Subject 1","Subject 1","Subject 1",
>                     "Subject 2","Subject 2","Subject 2","Subject 2"),
>                 Item   =
>                   c("Item 1","Item 2","Item 3","Item 4",
>                     "Item 1","Item 2","Item 3","Item 4"),
>                 Score  = c(1,0,1,1,1,1,0,0))
>
> df.wide <- reshape(df, idvar="Subject", timevar="Item", direction="wide")
> names(df.wide) <- c("Subject",unique(as.character(df$Item)))
>
> df.wide
>    Subject Item 1 Item 2 Item 3 Item 4
> 1 Subject 1      1      0      1      1
> 5 Subject 2      1      1      0      0
>
>
>
>  -----Original Message-----
>> From: r-help-bounces@r-project.org [mailto:r-help-bounces@r-project.org]
>> On
>> Behalf Of Ajay Ohri
>> Sent: 30 October 2010 16:27
>> To: Rhelp
>> Subject: [R] transforming a dataset for association analysis
>>
>> Hi
>>
>> I would like to transform  a data frame like
>>
>> Subject    Item   Score
>> Subject 1 Item 1 1
>> Subject 1 Item 2 0
>> Subject 1 Item 3 1
>> Subject 2 Item 1 1
>> Subject 2 Item 2 1
>> Subject 2 Item 3 0
>> ....
>> *to *
>>
>> Subject      Item1   Item2   Item3 .....Item N
>> Subject1       1          0       1
>> Subject2       1          1        0
>> ........
>> SubjectP..
>>
>> Apologize for the simple nature of my query but I am stuck. How can I do
>> this transformation?
>>
>> Regards
>>
>> Ajay
>>
>>
>>
>> Websites-
>> http://decisionstats.com
>> http://dudeofdata.com
>>
>>
>> Linkedin- www.linkedin.com/in/ajayohri
>>
>>
>>
>>
>> On Sat, Oct 30, 2010 at 2:39 PM, Alaios<alaios@yahoo.com>  wrote:
>>
>>  Hello everyone.
>>> I have written quite a big function that at the end correctly returns the
>>> values
>>> I want. I found a rare exception that I want to cover also. The easier
>>> for
>>> me
>>> would be to write something like that
>>>
>>>
>>> function(){
>>>
>>>  if (rare exception happened)
>>>      return that value
>>>
>>>  # The comes the code for normal execution
>>>  # ...
>>>  # ...
>>>  return value # Normal values to return
>>>
>>> }
>>>
>>>
>>> Would that be feasible with R or two returns statements are not accepted?
>>>
>>> Regards
>>> Alex
>>>
>>

	[[alternative HTML version deleted]]

