Dear R helpers
I have following table
Name no_of_instances
AAA 12
AA 17
A 0
BBB 11
BB 6
B 0
C 8
D 3
Now I need to generate the uniform random numbers (against the no. of instances)
and assign these numbers generated against the respective names. E.g. I need to
generate 12 random numbers and assign these numbers against AAA.
Individually I can generate them as
AAA_no = c(runif(12))
AA_no = c(runif(17))
......
and so on.
And in the end I can club them as
ran_nos = c(AAA_no, AA_no, ..........D_no)
My problem is if there are say 1000 names, then it will be a cumbersome job to
generate 1000 individual random number sets and then to combine them to form a
single dataset.
Is there any alternative to this?
Thanking in advance
With regards
Maithili
The INTERNET now has a personality. YOURS! See your Yahoo! Homepage.
[[alternative HTML version deleted]]
Dear Maithili,
Here are two suggestions:
# data set
x <- read.table(textConnection("Name no_of_instances
AAA 12
AA 17
A 0
BBB 11
BB 6
B 0
C 8
D 3"), header = TRUE)
closeAllConnections()
x
# option 1
do.call(c,with(x, tapply(no_of_instances, Name, runif)))
# option 2
with(x, runif( sum(no_of_instances) ))
HTH,
Jorge
On Tue, Dec 15, 2009 at 8:26 AM, Maithili Shiva <> wrote:
> Dear R helpers
>
> I have following table
>
> Name no_of_instances
> AAA 12
> AA 17
> A 0
> BBB 11
> BB 6
> B 0
> C 8
> D 3
>
> Now I need to generate the uniform random numbers (against the no. of
> instances) and assign these numbers generated against the respective names.
> E.g. I need to generate 12 random numbers and assign these numbers against
> AAA.
>
> Individually I can generate them as
>
> AAA_no = c(runif(12))
> AA_no = c(runif(17))
> ......
>
> and so on.
>
> And in the end I can club them as
>
> ran_nos = c(AAA_no, AA_no, ..........D_no)
>
> My problem is if there are say 1000 names, then it will be a cumbersome
> job to generate 1000 individual random number sets and then to combine them
> to form a single dataset.
>
> Is there any alternative to this?
>
> Thanking in advance
>
> With regards
>
> Maithili
>
>
>
>
> The INTERNET now has a personality. YOURS! See your Yahoo! Homepage.
> [[alternative HTML version deleted]]
>
>
> ______________________________________________
> R-help@r-project.org mailing list
> 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]]
On 15-Dec-09 13:35:36, Jorge Ivan Velez wrote:> Dear Maithili, > Here are two suggestions: > ># data set > x <- read.table(textConnection("Name no_of_instances > AAA 12 > AA 17 > A 0 > BBB 11 > BB 6 > B 0 > C 8 > D 3"), header = TRUE) > closeAllConnections() > x > ># option 1 > do.call(c,with(x, tapply(no_of_instances, Name, runif))) > ># option 2 > with(x, runif( sum(no_of_instances) )) > > HTH, > JorgeAnd, to round off the above: names(x) <- rep(Name,times=no_of_instances) (or similar). Then you can extract the random numbers for any Name. Ted.> On Tue, Dec 15, 2009 at 8:26 AM, Maithili Shiva <> wrote: > >> Dear R helpers >> >> I have following table >> >> Name no_of_instances >> AAA 12 >> AA 17 >> A 0 >> BBB 11 >> BB 6 >> B 0 >> C 8 >> D 3 >> >> Now I need to generate the uniform random numbers (against the no. of >> instances) and assign these numbers generated against the respective >> names. >> E.g. I need to generate 12 random numbers and assign these numbers >> against >> AAA. >> >> Individually I can generate them as >> >> AAA_no = c(runif(12)) >> AA_no = c(runif(17)) >> ...... >> >> and so on. >> >> And in the end I can club them as >> >> ran_nos = c(AAA_no, AA_no, ..........D_no) >> >> My problem is if there are say 1000 names, then it will be a >> cumbersome >> job to generate 1000 individual random number sets and then to combine >> them >> to form a single dataset. >> >> Is there any alternative to this? >> >> Thanking in advance >> >> With regards >> >> Maithili >> >> >> >> >> The INTERNET now has a personality. YOURS! See your Yahoo! >> Homepage. >> [[alternative HTML version deleted]] >> >> >> ______________________________________________ >> R-help at r-project.org mailing list >> 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 > 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.-------------------------------------------------------------------- E-Mail: (Ted Harding) <Ted.Harding at manchester.ac.uk> Fax-to-email: +44 (0)870 094 0861 Date: 15-Dec-09 Time: 13:57:50 ------------------------------ XFMail ------------------------------