[R] merge: right set overwrite left set

[aldi]

Hi,
I have two sets of data x.HHu and y.HHo, rows are IDs and columns are 
individuals. I do not know in advance indv or HHid, both of them will be 
captured from the data. As the y.HHo set updates, y.HHo set has better 
information then x.HHu set. Thus I want a merge where right set 
overwrites left set info based on HHid, i.e. to overwrite x.HHu set with 
y.HHo set but keep any extra info from the x.HHu set that is not present 
in y.HHo set.
HHids will be complete based on z.map, with the corresponding positions.
I am having trouble with the part after this line: ### 
============================================+++++++++++++++++++++++++++
I am thinking that I am creating new columns "position" "indv1" and 
"indv2", but R is interpreting them as row information.
See the expected final table at the end. HHid is common, indv3 is from 
x.HHu, and the rest position and indv1 and indv2 are from y.HHo
Any suggestions are appreciated.
Thank you in advance,
Aldi

x.HHu<- data.frame(
            HHid = c( 'HH1', 'HH2', 'HH3', 'HH4', 'HH5', 'HH10')
          , indv1 = c( 2, 0, 2 , 0, 2, 0)
          , indv2 = c( 0, NA, 2, 2, 2, 2)
          , ind3 = c( 0, 0, 0, 0, 0, 0)
          )
### the HHo data will be the top set to overwrite any HHu data, when 
they exist, thinking that HHo are better than HHu results
### when they are available

y.HHo<-data.frame(HHid=c('HH1', 'HH2','HH5', 'HH3', 'HH10')
          , indv1 = c(2, 0, 2, 0, NA)
          , indv2 = c(0, 2, 2, 1, 2)
          )

z.map<-data.frame(HHid = c('HH1', 'HH2', 'HH3', 'HH4', 'HH5', 
'HH6','HH8', 'HH7', 'HH9', 'HH10', 'HH11')
                 , position= c(10,20,30,42,55,66,81,75,92,101,111)
                 )
### see objects
x.HHu
y.HHo
z.map
### now sort the map by position, this sorted map will be used to sort 
finally all data
z.map<-z.map[with(z.map, order(position)), ]
z.map

### First I introduce position to both sets so I can sort them in 
advance by position.
x.HHu.map <-merge( z.map, x.HHu, by='HHid', all=T)
x.HHu.map<-x.HHu.map[with(x.HHu.map, order(position)), ]
x.HHu.map

y.HHo.map <-merge( z.map, y.HHo, by='HHid', all= T)
y.HHo.map<-y.HHo.map[with(y.HHo.map, order(position)), ]
y.HHo.map

### now merge HHu  and HHo  with the hope to overwrite the HHu set with 
HHo wherever they overlap by column names.
zzz <- merge(x.HHu.map, y.HHo.map, by='HHid', all=T)
zzz
### find common variable names in two sets

commonNames <- names(x.impu.map)[which(colnames(x.impu.map) %in% 
colnames(y.geno.map))]

## remove HHid wich is common for x and y, but work with the rest of columns
commonNames<-commonNames[-c(1)]

### ============================================+++++++++++++++++++++++++++
for(i in 1:length(commonNames)){

print(commonNames[i])
zzz$commonNames[i] <- NA

print(paste("zzz","$",commonNames[i],".y",sep=""))

zzz$commonNames[i] <- zzz[,paste(commonNames[i],".y",sep="")]

### paste(zzz$commonNames[i],".x",sep='') <- NULL;
### paste(zzz$commonNames[i],".y",sep='') <- NULL;

}
zzz

The final expected set has to be: HHid is common, indv3 is from x.HHu, 
and the rest position and indv1 and indv2 are from y.HHo
    HHid     position     ind3  indv1 indv2
1   HH1         10          0     2       0
2  HH10        101          0    NA       2
3  HH11        111         NA    NA      NA
4   HH2         20          0     0       2
5   HH3         30          0     0       1
6   HH4         42          0    NA      NA
7   HH5         55          0     2       2
8   HH6         66         NA    NA      NA
9   HH7         75         NA    NA      NA
10  HH8         81         NA    NA      NA
11  HH9         92         NA    NA      NA

-- 


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