[R] Reshaping Data for bi-partite Network Analysis

[arun]

Hi,
Try this;
library(reshape2)
res<-dcast(Input,people~place,value.var="time")
res[is.na(res)]<-0
 res
#  people beach home school sport
#1    Joe     5    3      0     1
#2   Marc     0    4      2     0
#3   Mary     0    0      4     0

#or
 xtabs(time~.,Input)
#      place
#people beach home school sport
 # Joe      5    3      0     1
 # Marc     0    4      2     0
 # Mary     0    0      4     0

A.K.



________________________________
 From: sylvain willart <sylvain.willart at gmail.com>
To: r-help <r-help at r-project.org>; sylvain willart <sylvain.willart at gmail.com> 
Sent: Saturday, April 13, 2013 5:03 PM
Subject: [R] Reshaping Data for bi-partite Network Analysis
 

Hello

I have a dataset of people spending time in places. But most people don't
hang out in all the places.

it looks like:

> Input<-data.frame(people=c("Marc","Marc","Joe","Joe","Joe","Mary"),
+              place=c("school","home","home","sport","beach","school"),
+              time=c(2,4,3,1,5,4))
> Input
  people  place time
1   Marc school    2
2   Marc   home    4
3    Joe   home    3
4    Joe  sport    1
5    Joe  beach    5
6   Mary school    4

In order to import it within R's igraph, I must use graph.incidence(), but
the data needs to be formatted that way:

>
Output<-data.frame(school=c(2,0,4),home=c(4,3,0),sport=c(0,1,0),beach=c(0,5,0),
+                    row.names=c("Marc","Joe","Mary"))
> Output
     school home sport beach
Marc      2    4     0     0
Joe       0    3     1     5
Mary      4    0     0     0

The Dataset is fairly large (couple hundreds of people and places), and I
would very much appreciate if someone could point me to a routine or
function that could transform my Input dataset to the required Output,

Thank you very much in advance

Regards

Sylvain

PS: sorry for cross-posting this on statnet and then on R help list, but I
received a message from statnet pointing out the question was more related
to general data management than actual network analysis. Which is true
indeed...

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