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

[S Ellison]

Does
do.call('cbind', list_of_dataframes)

do what you want?

S Ellison


> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Wolfgang
> Waser
> Sent: 09 February 2016 09:03
> To: Dénes Tóth; r-help at r-project.org
> Subject: Re: [R] How to extract same columns from identical dataframes in a
> list?
> 
> 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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> >> and provide commented, minimal, self-contained, reproducible code.
> >>
> >
> 
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