[R] replace NA's with row means for specific columns

[Marco]

Excerpts from Zahra via R-help's message of 2015-11-02 17:49:01 -0200:
> Hi there,
> 
> I am looking for some help replacing missing values in R with the row mean. This is survey data and I am trying to impute values for missing variables in each set of questions separately using the mean of the scores for the other questions within that set. 
> 
> I have a dataset that looks like this
> 
> ID      A1    A2    A3          B1     B2     B3         C1   C2   C3    C4
> b        4       5      NA          2       NA      4          5      1        3      NA
> c        4       5      1            NA      3        4          5      1        3      2
> d       NA     5      1            1        NA      4          5      1        3      2
> e        4       5      4            5       NA      4           5      1        3      2
> 
> 
> I want to replace any NA's in columns A1:A3 with the row mean for those columns only. So for ID=b, I want the NA in A3[ID=b] to be (4+5)/2 which is the average of the values in A1 and A2 for that row. 
> Same thing for columns B1:B3 - I want the NA in B2[ID=b] to be the mean of the values of B1 and B3 in row ID=b so that B2[ID=b] becomes 3 which is (2+4)/2. And same in C1:C4, I want C4[ID=b] to become (5+1+3)/3 which is the mean of C1:C3. 
> 
> Then I want to go to row ID=c and do the same thing and so on.
> 
> Can anybody help me do this? I have tried using rowMeans and subsetting but can't figure out the right code to do it. 
> 
> Thanks so much.
> Zahra
> 
use 

is.na(df[ which(df$ID) == 'b']) <- fmean(...), where fmean:

Depends on column selection (Axx, Byy, etc..) and the row id itself (so consider pass
the left hand of assignment entirely). I would use:

fmean <- function(row, col_selection) { # homework for you here }

Best Regards,

-- 
Marco Arthur @ (M)arco Creatives