[R] Joining two datasets - recursive procedure?

Bert Gunter
2015-03-21T14:53:14Z

z <- rnorm(nrow(f1)) ## or anything you want
z1 <- f1$v4 + z - with(f1,ave(z,v1,v2,FUN=mean))


aggregate(v4~v1,f1,sum)
aggregate(z1~v1,f1,sum)
aggregate(v4~v2,f1,sum)
aggregate(z1~v2,f1,sum)
aggregate(v4~v3,f1,sum)
aggregate(z1~v3,f1,sum)


Cheers,
Bert

Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374

"Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom."
Clifford Stoll




On Sat, Mar 21, 2015 at 6:49 AM, Luca Meyer <lucam1968 at gmail.com>
wrote:
> Hi Bert,
>
> Thank you for your message. I am looking into ave() and tapply() as you
> suggested but at the same time I have prepared a example of input and
output
> files, just in case you or someone else would like to make an attempt to
> generate a code that goes from input to output.
>
> Please see below or download it from
> https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0
>
> # this is (an extract of) the INPUT file I have:
> f1 <- structure(list(v1 = c("A", "A", "A",
"A", "A", "A", "B", "B",
> "B", "B", "B", "B"), v2 =
c("A", "B", "C", "A", "B",
"C", "A",
> "B", "C", "A", "B", "C"),
v3 = c("B", "B", "B", "C",
"C", "C",
> "B", "B", "B", "C", "C",
"C"), v4 = c(18.18530, 3.43806,0.00273, 1.42917,
> 1.05786, 0.00042, 2.37232, 3.01835, 0, 1.13430, 0.92872,
> 0)), .Names = c("v1", "v2", "v3",
"v4"), class = "data.frame", row.names > c(2L,
> 9L, 11L, 41L, 48L, 50L, 158L, 165L, 167L, 197L, 204L, 206L))
>
> # this is (an extract of) the OUTPUT file I would like to obtain:
> f2 <- structure(list(v1 = c("A", "A", "A",
"A", "A", "A", "B", "B",
> "B", "B", "B", "B"), v2 =
c("A", "B", "C", "A", "B",
"C", "A",
> "B", "C", "A", "B", "C"),
v3 = c("B", "B", "B", "C",
"C", "C",
> "B", "B", "B", "C", "C",
"C"), v4 = c(17.83529, 3.43806,0.00295, 1.77918,
> 1.05786, 0.0002, 2.37232, 3.01835, 0, 1.13430, 0.92872,
> 0)), .Names = c("v1", "v2", "v3",
"v4"), class = "data.frame", row.names > c(2L,
> 9L, 11L, 41L, 48L, 50L, 158L, 165L, 167L, 197L, 204L, 206L))
>
> # please notice that while the aggregated v4 on v3 has changed ?
> aggregate(f1[,c("v4")],list(f1$v3),sum)
> aggregate(f2[,c("v4")],list(f2$v3),sum)
>
> # ? the aggregated v4 over v1xv2 has remained unchanged:
> aggregate(f1[,c("v4")],list(f1$v1,f1$v2),sum)
> aggregate(f2[,c("v4")],list(f2$v1,f2$v2),sum)
>
> Thank you very much in advance for your assitance.
>
> Luca
>
> 2015-03-21 13:18 GMT+01:00 Bert Gunter <gunter.berton at gene.com>:
>>
>> 1. Still not sure what you mean, but maybe look at ?ave and ?tapply,
>> for which ave() is a wrapper.
>>
>> 2. You still need to heed the rest of Jeff's advice.
>>
>> Cheers,
>> Bert
>>
>> Bert Gunter
>> Genentech Nonclinical Biostatistics
>> (650) 467-7374
>>
>> "Data is not information. Information is not knowledge. And
knowledge
>> is certainly not wisdom."
>> Clifford Stoll
>>
>>
>>
>>
>> On Sat, Mar 21, 2015 at 4:53 AM, Luca Meyer <lucam1968 at
gmail.com> wrote:
>> > Hi Jeff & other R-experts,
>> >
>> > Thank you for your note. I have tried myself to solve the issue
without
>> > success.
>> >
>> > Following your suggestion, I am providing a sample of the dataset
I am
>> > using below (also downloadble in plain text from
>> > https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0):
>> >
>> > #this is an extract of the overall dataset (n=1200 cases)
>> > f1 <- structure(list(v1 = c("A", "A",
"A", "A", "A", "A", "B",
"B",
>> > "B", "B", "B", "B"), v2 =
c("A", "B", "C", "A", "B",
"C", "A",
>> > "B", "C", "A", "B",
"C"), v3 = c("B", "B", "B",
"C", "C", "C",
>> > "B", "B", "B", "C",
"C", "C"), v4 = c(18.1853007621835,
>> > 3.43806581506388,
>> > 0.002733567617055, 1.42917483425029, 1.05786640463504,
>> > 0.000420548864162308,
>> > 2.37232740842861, 3.01835841813241, 0, 1.13430282139936,
>> > 0.928725667117666,
>> > 0)), .Names = c("v1", "v2", "v3",
"v4"), class = "data.frame", row.names
>> > >> > c(2L,
>> > 9L, 11L, 41L, 48L, 50L, 158L, 165L, 167L, 197L, 204L, 206L))
>> >
>> > I need to find a automated procedure that allows me to adjust v3
>> > marginals
>> > while maintaining v1xv2 marginals unchanged.
>> >
>> > That is: modify the v4 values you can find by running:
>> >
>> > aggregate(f1[,c("v4")],list(f1$v3),sum)
>> >
>> > while maintaining costant the values you can find by running:
>> >
>> > aggregate(f1[,c("v4")],list(f1$v1,f1$v2),sum)
>> >
>> > Now does it make sense?
>> >
>> > Please notice I have tried to build some syntax that tries to
modify
>> > values
>> > within each v1xv2 combination by computing sum of v4, row
percentage in
>> > terms of v4, and there is where my effort is blocked. Not really
sure
>> > how I
>> > should proceed. Any suggestion?
>> >
>> > Thanks,
>> >
>> > Luca
>> >
>> >
>> > 2015-03-19 2:38 GMT+01:00 Jeff Newmiller <jdnewmil at
dcn.davis.ca.us>:
>> >
>> >> I don't understand your description. The standard practice
on this list
>> >> is
>> >> to provide a reproducible R example [1] of the kind of data
you are
>> >> working
>> >> with (and any code you have tried) to go along with your
description.
>> >> In
>> >> this case, that would be two dputs of your input data frames
and a dput
>> >> of
>> >> an output data frame (generated by hand from your input data
frame).
>> >> (Probably best to not use the full number of input values just
to keep
>> >> the
>> >> size down.) We could then make an attempt to generate code
that goes
>> >> from
>> >> input to output.
>> >>
>> >> Of course, if you post that hard work using HTML then it will
get
>> >> corrupted (much like the text below from your earlier emails)
and we
>> >> won't
>> >> be able to use it. Please learn to post from your email
software using
>> >> plain text when corresponding with this mailing list.
>> >>
>> >> [1]
>> >>
>> >>
http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
>> >>
>> >>
---------------------------------------------------------------------------
>> >> Jeff Newmiller                        The     .....
.....  Go
>> >> Live...
>> >> DCN:<jdnewmil at dcn.davis.ca.us>        Basics: ##.#.
##.#.  Live
>> >> Go...
>> >>                                       Live:   OO#.. Dead:
OO#..
>> >> Playing
>> >> Research Engineer (Solar/Batteries            O.O#.
#.O#.  with
>> >> /Software/Embedded Controllers)               .OO#.
.OO#.
>> >> rocks...1k
>> >>
>> >>
---------------------------------------------------------------------------
>> >> Sent from my phone. Please excuse my brevity.
>> >>
>> >> On March 18, 2015 9:05:37 AM PDT, Luca Meyer <lucam1968 at
gmail.com>
>> >> wrote:
>> >> >Thanks for you input Michael,
>> >> >
>> >> >The continuous variable I have measures quantities (down
to the 3rd
>> >> >decimal level) so unfortunately are not frequencies.
>> >> >
>> >> >Any more specific suggestions on how that could be
tackled?
>> >> >
>> >> >Thanks & kind regards,
>> >> >
>> >> >Luca
>> >> >
>> >> >
>> >> >==>> >> >
>> >> >Michael Friendly wrote:
>> >> >I'm not sure I understand completely what you want to
do, but
>> >> >if the data were frequencies, it sounds like task for
fitting a
>> >> >loglinear model with the model formula
>> >> >
>> >> >~ V1*V2 + V3
>> >> >
>> >> >On 3/18/2015 2:17 AM, Luca Meyer wrote:
>> >> >>* Hello,
>> >> >*>>* I am facing a quite challenging task (at least
to me) and I was
>> >> >wondering
>> >> >*>* if someone could advise how R could assist me to
speed the task
>> >> > up.
>> >> >*>>* I am dealing with a dataset with 3 discrete
variables and one
>> >> >continuous
>> >> >*>* variable. The discrete variables are:
>> >> >*>>* V1: 8 modalities
>> >> >*>* V2: 13 modalities
>> >> >*>* V3: 13 modalities
>> >> >*>>* The continuous variable V4 is a decimal number
always greater
>> >> > than
>> >> >zero in
>> >> >*>* the marginals of each of the 3 variables but it is
sometimes equal
>> >> >to zero
>> >> >*>* (and sometimes negative) in the joint tables.
>> >> >*>>* I have got 2 files:
>> >> >*>>* => one with distribution of all possible
combinations of V1xV2
>> >> >(some of
>> >> >*>* which are zero or neagtive) and
>> >> >*>* => one with the marginal distribution of V3.
>> >> >*>>* I am trying to build the long and narrow
dataset V1xV2xV3 in such
>> >> >a way
>> >> >*>* that each V1xV2 cell does not get modified and V3
fits as closely
>> >> >as
>> >> >*>* possible to its marginal distribution. Does it make
sense?
>> >> >*>>* To be even more specific, my 2 input files look
like the
>> >> >following.
>> >> >*>>* FILE 1
>> >> >*>* V1,V2,V4
>> >> >*>* A, A, 24.251
>> >> >*>* A, B, 1.065
>> >> >*>* (...)
>> >> >*>* B, C, 0.294
>> >> >*>* B, D, 2.731
>> >> >*>* (...)
>> >> >*>* H, L, 0.345
>> >> >*>* H, M, 0.000
>> >> >*>>* FILE 2
>> >> >*>* V3, V4
>> >> >*>* A, 1.575
>> >> >*>* B, 4.294
>> >> >*>* C, 10.044
>> >> >*>* (...)
>> >> >*>* L, 5.123
>> >> >*>* M, 3.334
>> >> >*>>* What I need to achieve is a file such as the
following
>> >> >*>>* FILE 3
>> >> >*>* V1, V2, V3, V4
>> >> >*>* A, A, A, ???
>> >> >*>* A, A, B, ???
>> >> >*>* (...)
>> >> >*>* D, D, E, ???
>> >> >*>* D, D, F, ???
>> >> >*>* (...)
>> >> >*>* H, M, L, ???
>> >> >*>* H, M, M, ???
>> >> >*>>* Please notice that FILE 3 need to be such that
if I aggregate on
>> >> >V1+V2 I
>> >> >*>* recover exactly FILE 1 and that if I aggregate on
V3 I can recover
>> >> >a file
>> >> >*>* as close as possible to FILE 3 (ideally the same
file).
>> >> >*>>* Can anyone suggest how I could do that with R?
>> >> >*>>* Thank you very much indeed for any assistance
you are able to
>> >> >provide.
>> >> >*>>* Kind regards,
>> >> >*>>* Luca*
>> >> >
>> >> >       [[alternative HTML version deleted]]
>> >> >
>> >> >______________________________________________
>> >> >R-help at r-project.org mailing list -- To UNSUBSCRIBE and
more, see
>> >> >https://stat.ethz.ch/mailman/listinfo/r-help
>> >> >PLEASE do read the posting guide
>> >> >http://www.R-project.org/posting-guide.html
>> >> >and provide commented, minimal, self-contained,
reproducible code.
>> >>
>> >>
>> >
>> >         [[alternative HTML version deleted]]
>> >
>> > ______________________________________________
>> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more,
see
>> > https://stat.ethz.ch/mailman/listinfo/r-help
>> > PLEASE do read the posting guide
>> > http://www.R-project.org/posting-guide.html
>> > and provide commented, minimal, self-contained, reproducible code.
>
>