Skip NA values using "FUN=first"

Question

there's probably really an simple explaination as to what I'm doing wrong, but I've been working on this for quite some time today and I still can not get this to work. I thought this would be a walk in the park, however, my code isn't quite working as expected.

So for this example, let's say I have a data frame as followed.

df
Row#   user      columnB    
1        1          NA        
2        1          NA        
3        1          NA        
4        1          31        
5        2          NA        
6        2          NA        
7        2          15        
8        3          18        
9        3          16       
10       3          NA

Basically, I would like to create a new column that uses the first (as well as last) function (within the TTR library package) to obtain the first non-NA value for each user. So my desired data frame would be this.

df
Row#   user      columnB    firstValue
1        1          NA        31
2        1          NA        31 
3        1          NA        31
4        1          31        31
5        2          NA        15
6        2          NA        15 
7        2          15        15
8        3          18        18
9        3          16        18
10       3          NA        18

I've looked around mainly using google, but I couldn't really find my exact answer.

Here's some of my code that I've tried, but I didn't get the results that I wanted (note, I'm bringing this from memory, so there are quite a few more variations of these, but these are the general forms that I've been trying).

    df$firstValue<-ave(df$columnB,df$user,FUN=first,na.rm=True)
    df$firstValue<-ave(df$columnB,df$user,FUN=function(x){x,first,na.rm=True})
    df$firstValue<-ave(df$columnB,df$user,FUN=function(x){first(x,na.rm=True)})
    df$firstValue<-by(df,df$user,FUN=function(x){x,first,na.rm=True})

Failed, these just give the first value of each group, which would be NA.

Again, these are just a few examples from the top of my head, I played around with na.rm, using na.exclude, na.omit, na.action(na.omit), etc...

Any help would be greatly appreciated. Thanks.

Answer 1

A data.table solution

require(data.table)
DT <- data.table(df, key="user")
DT[, firstValue := na.omit(columnB)[1], by=user]