Q:

Combine rows based on multiple columns and keep all unique values

I have a dataset with User Information. For a specific user I have often multiple rows with more or less complete information.  I want to summarize all rows that belong to a customer on the basis of First_Name, Last_Name, Street while keeping all information of the other columns and if there are two unique observation for a specific column I want to collapse them with ",". 
This is what the df looks like
First_Name Last_Name Street Column1 Colum2 Colum_n

Mike       Smith      X     abc     ab     a
Mike       Smith      X     abc     ad     b
John       Smith      Y     xyz     xy     n
John       Smith      Y     xyz     xm     NA

My desired output would be 
 First_Name Last_Name Street Column1 Colum2 Colum_n

 Mike       Smith      X     abc     ab,ad     a,b
 John       Smith      Y     xyz     xy,xm       n

I would like using dplyr and tried something with 
df %>% 
group_by(First_Name,Last_Name, Street) %>%
summarise_all(funs())

The problem with that function is that I only had the option of using something like the mean or the first occuring value for a column and this would mean the loss of values. What I would like are columns with all unique values without NA's

A:

You can write your own summarization function like
concat_unique <- function(x){paste(unique(x),  collapse=',')}
and then apply it using
summarize_all(concat_unique)

