Thank you arun !
I don't know the library reshape2
Michel

Le 20/06/2013 19:55, arun a écrit :
Hi,

Not sure if you wanted the entries with "0".

library(reshape2)
  dfMelt<-melt(df,id.var=c("Country","Iso"))

#subset those with "1"

dfNew<- subset(dfMelt,value==1,select=-4) row.names(dfNew)<- 1:nrow(dfNew)
  dfNew
#        Country Iso   variable
#1      Zimbabwe  ZW      Abaco
#2  South Africa  ZA      Abaco
#3    Madagascar  MG      Abaco
#4          Mali  ML      Abaco
#5         Kenya  KE      Abaco
#6  Burkina Faso  BF      Abaco
#7      Tanzania  TZ Adaptclone
#8          Mali  ML Adaptclone
#9    Mozambique  MZ Adaptclone
#10   Madagascar  MG Adaptclone
#11        Ghana  GH Adaptclone
#12      Nigeria  NG Adaptclone


A.K.


Hello

I have the following dataframe :
df <- data.frame(
Country=c("Zimbabwe","Burkina Faso","South Africa","Madagascar","Tanzania",
"Mali","Mozambique","Madagascar","Ghana","Nigeria","Kenya","Burkina Faso",
   "South Africa","Tanzania","Kenya","Ethiopia" ) ,

Iso=c("ZW","BF","ZA","MG","TZ","ML","MZ","MG","GH","NG","KE","BF",
   "ZA","TZ","KE","ET") ,

Abaco=c(1,0,1,1,0,1,0,0,0,0,1,1,0,0,0,0) ,
Adaptclone= c(0,0,0,0,1,1,1,1,1,1,0,0,0,0,0,0)
)
There is a lot of column like Abaco, Adaptclone,...
I would like to built a dataframe
wich transforms the initial dataframe of 4 columns into a dataframe of 3
columns as the following dataframe

Country          Iso    Project
Zimbabwe         ZW     Abaco
South Africa     ZA     Abaco
Madagascar       MG     Abaco
Tanzania         TZ     Adaptclone
Mali             ML     Abaco
Mali             ML     Adaptclone
......

Any idea ?
Michel


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Michel ARNAUD
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