[R] Vector recycling and zoo
Gabor Grothendieck
ggrothendieck at gmail.com
Mon May 17 02:05:49 CEST 2010
Or even:
with(x, a / coredata(a[1]) )
On Sun, May 16, 2010 at 7:48 PM, Gabor Grothendieck
<ggrothendieck at gmail.com> wrote:
> Normally that would be written like this using the coredata extraction
> function which extracts the data portion of a zoo object:
>
> x$a / coredata( x$a[1] )
>
> On Sun, May 16, 2010 at 7:32 PM, Sean Carmody <seancarmody at gmail.com> wrote:
>> Thanks David,
>>
>> You comment made me realise that whereas when x is a data frame, x$a is a
>> numeric vector,
>> when x is of class zoo, x$a is also of class zoo, so the following does what
>> I was expecting:
>>
>> x$a/as.numeric(x$a[1])
>>
>> Sean.
>>
>> On Sun, May 16, 2010 at 9:25 PM, David Winsemius <dwinsemius at comcast.net>wrote:
>>
>>>
>>> On May 16, 2010, at 2:00 AM, Sean Carmody wrote:
>>>
>>> I am a bit confused about the different approaches taken to recycling in
>>>> plain data frames and zoo objects. When carrying out simple arithmetic,
>>>> dataframe seem to recycle single arguments, zoo objects do not. Here is an
>>>> example
>>>>
>>>> x <- data.frame(a=1:5*2, b=1:5*3)
>>>>> x
>>>>>
>>>> a b
>>>> 1 2 3
>>>> 2 4 6
>>>> 3 6 9
>>>> 4 8 12
>>>> 5 10 15
>>>>
>>>>> x$a/x$a[1]
>>>>>
>>>> [1] 1 2 3 4 5
>>>>
>>>>> x <- zoo(x)
>>>>> x$a/x$a[1]
>>>>>
>>>> 1
>>>> 1
>>>>
>>>>>
>>>>>
>>>> I feel understanding this difference would lead me to a greater
>>>> understanding of the zoo module!
>>>>
>>>
>>> I think you do have misunderstandings about the zoo package but I do not
>>> think it is in the area of vector recycling. Notice the effect of your
>>> application of the zoo function to x:
>>>
>>> > x$a
>>>
>>> 1 2 3 4 5
>>> 2 4 6 8 10
>>> > x$a[1]
>>> 1
>>> 2
>>>
>>> You have in effect transposed the elements in x and are now getting a two
>>> element column vector when requesting x$a[1]. The term vector recycling is
>>> applied to situations where short vectors are reused starting with their
>>> first elements until the necessary length is achieved. For instance if you
>>> request:
>>>
>>> > data.frame(x=1:2, y=letters[1:10])
>>> x y
>>> 1 1 a
>>> 2 2 b
>>> 3 1 c
>>> 4 2 d
>>> 5 1 e
>>> 6 2 f
>>> 7 1 g
>>> 8 2 h
>>> 9 1 i
>>> 10 2 j
>>>
>>> Or plot(1:10, col=c("red","green"))
>>>
>>>
>>>> Sean.
>>>>
>>>> --
>>>> Sean Carmody
>>>>
>>>
>>>
>>>
>>
>>
>> --
>> Sean Carmody
>> Twitter: http://twitter.com/seancarmody
>> Stable: http://mulestable.net/sean
>>
>> The Stubborn Mule
>> Blog: http://www.stubbornmule.net
>> Forum: http://mulestable.net/
>>
>> [[alternative HTML version deleted]]
>>
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