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
