[R] Having some Trouble Data Structures
arun
smartpink111 at yahoo.com
Sun Oct 28 17:55:50 CET 2012
Hi,
In addition to using paste(), you can also try this:
dat1<-data.frame(ID=formatC(0001:0010,width=4,flag="0"),No_of_Effectors=rep(3,10))
dat1<-within(dat1,{ID<-as.character(ID)})
list1<-lapply(1:nrow(dat1),function(x) sample(1:10000,3,replace=TRUE))
dat2<-data.frame(dat1,Effectors=I(list1))
str(dat2)
#'data.frame': 10 obs. of 3 variables:
# $ ID : chr "0001" "0002" "0003" "0004" ...
# $ No_of_Effectors: num 3 3 3 3 3 3 3 3 3 3
# $ Effectors :List of 10
# ..$ : int 6155 979 3079
#..$ : int 690 5515 9469
# ..$ : int 903 7439 7582
#..$ : int 9788 5930 7456
#..$ : int 8106 8319 2396
#..$ : int 8050 5299 264
#..$ : int 5558 7401 8865
#..$ : int 7178 7273 4065
#..$ : int 2135 75 7571
#..$ : int 6652 9900 2313
#..- attr(*, "class")= chr "AsIs"
head(dat2)
# ID No_of_Effectors Effectors
#1 0001 3 6155, 97....
#2 0002 3 690, 551....
#3 0003 3 903, 743....
#4 0004 3 9788, 59....
#5 0005 3 8106, 83....
#6 0006 3 8050, 52....
BTW, I had a line of code in my previous reply which was not required and it will not work.
#list1<-lapply(1:nrow(dat1),function(x) paste(sample(1:10000,3,replace=TRUE)),sep=",")
A.K.
----- Original Message -----
From: Benjamin Ward (ENV) <B.Ward at uea.ac.uk>
To: "r-help at r-project.org" <r-help at r-project.org>
Cc:
Sent: Sunday, October 28, 2012 5:32 AM
Subject: [R] Having some Trouble Data Structures
Hi All,
I'm trying to run a simulation of host-pathogen evolution based around individuals.
What I need to have is a dataframe or table of some description - describing all the individuals of a pathogen population (so far I've implemented this as a matrix):
ID No_of_Effectors Effectors (Sequences)
[1,] 0001 3 ## 3 Random Numbers ##
There will be many such rows for many individuals. They have something called effectors, the number of which is randomly generated, so say you get 3 in the No_of_Effectors column. Then I make R generate 3 numbers from between 1 and 10,000, this gives me three numerical representations of genes. These numbers will be compared to a similar data structure of the host individuals who have their immune genes with similar numbers.
My problem is that obviously I can't stick 3 numbers in one "cell" of the matrix (I've tried) :
Pathogen_Individuals[1,3] <- c(2,3,4)
Error in Pathogen_Individuals[1, 3] <- c(345, 567, 678) :
number of items to replace is not a multiple of replacement length
In future I'm also going to have more variables such as whether a gene is expressed. Such information may require a matrix in itself - something like:
Effector ID Sequence Expressed?
[1,] 0001 345,567,678 1 (or 0).
Is there a way then I can put more than one value in the cell like a list of values, or a way to put objects in a cell of a data frame, matrix or table etc. Almost an inception deal - data structures nested in a data structure? If I search for things like "insert list into matrix" I get results like how to turn one into another, which is not what I think I need to be doing.
I have been considering having several data structures not nested in each other, something like for every individual create a new matrix object with the name Effectors_[Individual_ID] and some how get my simulation loops operating on those objects but I find it hard to see how to tell R all of those matrices are to be included in an operation, as you can all lines of a data frame for example with for loops.
This is strange for me because this model was written in a macro-code for another program which handles data in a different format and layout to R.
My problem is I think, each individual in the model has many variables - in this case representations of genes. So I'm having trouble getting my head about this.
Hopefully someone more experienced will be able to offer advice or a solution, it will be very appreciated.
Many Thanks,
Ben Ward (ENV, UEA & The Sainsbury Lab, JIC).
P.S. I have searched previous queries to the list, and I'm not sure but this may be useful for relevant:
Have you thought of using a list?
> a <- matrix(1:10, nrow=2)
> b <- 1:5
> x <- list(a=a, b=b)
> x
$a
[,1] [,2] [,3] [,4] [,5]
[1,] 1 3 5 7 9
[2,] 2 4 6 8 10
$b
[1] 1 2 3 4 5
> x$a
[,1] [,2] [,3] [,4] [,5]
[1,] 1 3 5 7 9
[2,] 2 4 6 8 10
> x$b
[1] 1 2 3 4 5
oliveoil and yarn datasets have been mentioned.
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