[R] Joining two datasets - recursive procedure?

Bert Gunter gunter.berton at gene.com
Sun Mar 22 16:05:42 CET 2015 

Oh, wait a minute ...

You still want the marginals for the other columns to be as originally?

If so, then this is impossible in general as the sum of all the values
must be what they were originally and you cannot therefore choose your
values for V3 arbitrarily.

Or at least, that seems to be what you are trying to do.

-- 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 Sun, Mar 22, 2015 at 7:55 AM, Bert Gunter <bgunter at gene.com> wrote:
> I would have thought that this is straightforward given my previous email...
>
> Just set z to what you want -- e,g, all B values to 29/number of B's,
> and all C values to 2.567/number of C's (etc. for more categories).
>
> A slick but sort of cheat way to do this programmatically -- in the
> sense that it relies on the implementation of factor() rather than its
> API -- is:
>
> y <- f1$v3  ## to simplify the notation; could be done using with()
> z <- (c(29,2.567)/table(y))[c(y)]
>
> Then proceed to z1 as I previously described
>
> -- 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 Sun, Mar 22, 2015 at 2:00 AM, Luca Meyer <lucam1968 at gmail.com> wrote:
>> Hi Bert, hello R-experts,
>>
>> I am close to a solution but I still need one hint w.r.t. the following
>> procedure (available also from
>> https://www.dropbox.com/s/qhmpkkrejjkpbkx/sample_code.txt?dl=0)
>>
>> rm(list=ls())
>>
>> # 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 the procedure that Bert suggested (slightly adjusted):
>> z <- rnorm(nrow(f1)) ## or anything you want
>> z1 <- round(with(f1,v4 + z -ave(z,v1,v2,FUN=mean)), digits=5)
>> aggregate(v4~v1*v2,f1,sum)
>> aggregate(z1~v1*v2,f1,sum)
>> aggregate(v4~v3,f1,sum)
>> aggregate(z1~v3,f1,sum)
>>
>> My question to you is: how can I set z so that I can obtain specific values
>> for z1-v4 in the v3 aggregation?
>> In other words, how can I configure the procedure so that e.g. B=29 and
>> C=2.56723 after running the procedure:
>> aggregate(z1~v3,f1,sum)
>>
>> Thank you,
>>
>> Luca
>>
>> PS: to avoid any doubts you might have about who I am the following is my
>> web page: http://lucameyer.wordpress.com/
>>
>>
>> 2015-03-21 18:13 GMT+01:00 Bert Gunter <gunter.berton at gene.com>:
>>>
>>> ... or cleaner:
>>>
>>> z1 <- with(f1,v4 + z -ave(z,v1,v2,FUN=mean))
>>>
>>>
>>> Just for curiosity, was this homework? (in which case I should
>>> probably have not provided you an answer -- that is, assuming that I
>>> HAVE provided an answer).
>>>
>>> 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 7:53 AM, Bert Gunter <bgunter at gene.com> wrote:
>>> > 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.
>>> >>
>>> >>
>>
>>

More information about the R-help mailing list