[R] How to extract same columns from identical dataframes in a list?

[Wolfgang Waser]

Hi,

sapply(l,"[",T,2)

and

sapply(l, function(e) e[, 2])


work fine!


Thanks a lot!

Why is the second version "brute force and ignorance"? Is one of the
versions to be preferred? If so, which and why (very briefly, please)?


Results of the other options mentioned:

> sapply(l,"[[",2)

results in a single vector of length 7


> sapply(l,"[",,2)
Error in lapply(X = X, FUN = FUN, ...) :
argument is missing, with no default

These versions probably don't work due the "data frames" in the list
actually being matrices.


I'm not enough of a programer to always make complete sense of the R
help pages. Should I have found this information in the sapply - R help
page?
Where else could I check before pestering the R mailing list, which, of
course, provides quick and valuable answers.


Cheers,

Wolfgang




On 09/02/16 16:19, peter dalgaard wrote:
> Like this?
> 
>> l <- replicate(3,data.frame(w1=sample(1:4),w2=sample(1:4)), simplify=FALSE)
>> l
> [[1]]
>   w1 w2
> 1  2  2
> 2  3  3
> 3  1  1
> 4  4  4
> 
> [[2]]
>   w1 w2
> 1  3  4
> 2  2  2
> 3  1  3
> 4  4  1
> 
> [[3]]
>   w1 w2
> 1  1  4
> 2  4  3
> 3  2  1
> 4  3  2
> 
>> sapply(l,"[[",2)
>      [,1] [,2] [,3]
> [1,]    2    4    4
> [2,]    3    2    3
> [3,]    1    3    1
> [4,]    4    1    2
> 
> Or even
> 
>> sapply(l,"[",,2)
>      [,1] [,2] [,3]
> [1,]    2    4    4
> [2,]    3    2    3
> [3,]    1    3    1
> [4,]    4    1    2
> 
> 
> Notice that if dd[1:24] gives you the 1st column, then dd is not a data frame but rather a matrix, and indexing semantics are different. In that case, for some unspeakable reason, the empty index does not work and you'll need something like
> 
>> l <- replicate(3,cbind(w1=sample(1:4),w2=sample(1:4)), simplify=FALSE)
>> sapply(l,"[",T,2)
>      [,1] [,2] [,3]
> [1,]    4    3    2
> [2,]    1    1    4
> [3,]    3    2    3
> [4,]    2    4    1
> 
> Or, brute-force-and-ignorance:
> 
>> sapply(l, function(e) e[, 2])
>      [,1] [,2] [,3]
> [1,]    4    3    2
> [2,]    1    1    4
> [3,]    3    2    3
> [4,]    2    4    1
> 
> 
> 
> 
> 
> On 09 Feb 2016, at 10:03 , Wolfgang Waser <waser at frankenfoerder-fg.de> wrote:
> 
>> Hi,
>>
>> sorry if my description was too short / unclear.
>>
>>> I have a list of 7 data frames, each data frame having 24 rows (hour of
>>> the day) and 5 columns (weeks) with a total of 5 x 24 values
>>
>> [1]
>> 	week1	week2	week3	...
>> 1	x	a	m	...
>> 2	y	b	n
>> 3	z	c	o
>> .	.	.	.
>> .	.	.	.
>> .	.	.	.
>> 24	.	.	.
>>
>>
>> [2]
>> 	week1 week2 week3 ...
>> 1	x2	a2	m2	...
>> 2	y2	b2	n2
>> 3	z2	c2	o2
>> .	.	.	.
>> .	.	.	.
>> .	.	.	.
>> 24	.	.	.
>>
>>
>> [3]
>> ...
>>
>> .
>> .
>> .
>>
>>
>> [7]
>> ...
>>
>>
>>
>> I now would like to extract e.g. all week2 columns of all data frames in
>> the list and combine them in a new data frame using cbind.
>>
>> new data frame
>>
>> week2 ([1])	week2 ([2])	week2 ([3])	...
>> a		a2		.
>> b		b2		.
>> c		c2		.
>> .
>> .
>> .
>>
>> I will then do further row-wise calculations using e.g. apply(x,1,mean),
>> the result being a vector of 24 values.
>>
>>
>> I have not found a way to extract specific columns of the data frames in
>> a list.
>>
>>
>> As mentioned I can use
>>
>> sapply(list_of_dataframes,"[",1:24)
>>
>> which will pick the first 24 values (first column) of each data frame in
>> the list and arrange them as an array of 24 rows and 7 columns (7 data
>> frames are in the list).
>> To pick the second column (week2) using sapply I have to use the next 24
>> values from 25 to 48:
>>
>> sapply(list_of_dataframes,"[",25:48)
>>
>>
>> It seems that sapply treats the data frames in the list as vectors. I
>> can of course extract all consecutive weeks using consecutive blocks of
>> 24 values, but this seems cumbersome.
>>
>>
>> The question remains, how to select specific columns from data frames in
>> a list, e.g. all columns 3 of all data frames in the list.
>>
>>
>> Reformatting (unlist(), dim()) in one data frame with one column for
>> each week does not help, since I'm not calculating colMeans etc, but
>> row-wise calculations using apply(x,1,FUN) ("applying a function to
>> margins of an array or matrix").
>>
>>
>>
>> Thanks for you help and suggestions!
>>
>>
>> Wolfgang
>>
>>
>>
>> On 08/02/16 18:00, Dénes Tóth wrote:
>>> Hi,
>>>
>>> Although you did not provide any reproducible example, it seems you
>>> store the same type of values in your data.frames. If this is true, it
>>> is much more efficient to store your data in an array:
>>>
>>> mylist <- list(a = data.frame(week1 = rnorm(24), week2 = rnorm(24)),
>>>               b = data.frame(week1 = rnorm(24), week2 = rnorm(24)))
>>>
>>> myarray <- unlist(mylist, use.names = FALSE)
>>> dim(myarray) <- c(nrow(mylist$a), ncol(mylist$a), length(mylist))
>>> dimnames(myarray) <- list(hour = rownames(mylist$a),
>>>                          week = colnames(mylist$a),
>>>                          other = names(mylist))
>>> # now you can do:
>>> mean(myarray[, "week1", "a"])
>>>
>>> # or:
>>> colMeans(myarray)
>>>
>>>
>>> Cheers,
>>>  Denes
>>>
>>>
>>> On 02/08/2016 02:33 PM, Wolfgang Waser wrote:
>>>> Hello,
>>>>
>>>> I have a list of 7 data frames, each data frame having 24 rows (hour of
>>>> the day) and 5 columns (weeks) with a total of 5 x 24 values
>>>>
>>>> I would like to combine all 7 columns of week 1 (and 2 ...) in a
>>>> separate data frame for hourly calculations, e.g.
>>>>> apply(new.data.frame,1,mean)
>>>>
>>>> In some way sapply (lapply) works, but I cannot directly select columns
>>>> of the original data frames in the list. As a workaround I have to
>>>> select a range of values:
>>>>
>>>>> sapply(list_of_dataframes,"[",1:24)
>>>>
>>>> Values 1:24 give the first column, 25:48 the second and so on.
>>>>
>>>> Is there an easier / more direct way to select for specific columns
>>>> instead of selecting a range of values, avoiding loops?
>>>>
>>>>
>>>> Cheers,
>>>>
>>>> Wolfgang
>>>>
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