r - Reshaping longitudinal value to wide, for data with multiple rows per subject

Question

R: Reshape data from long to wide, including a date

(I was trying to include data, but the formatting was so horrible that I gave up).

I have a question on reshaping longitudinal data. The trick is that I have multiple rows per subject ('row_num' ranges from 1 to 8).

I've looked at over 20 Stack Overflow pages, some other pages, and Hadley's posts (and articles) on reshaping, and there seems to be a gap I can't find:

I have got multiple rows per subject, and can't find out how to turn that into one row. The trick is that I need to take (say) Q1,...,Q5, and turn it into two or more blocks of questions (Q1.1,...,Q5.1,Q1.2,...Q5.2, ...)

Using one terminology, 'row_num' is a within-subject variable, and everything seems to be based on between-subject variables.

It puzzles and frustrates me, since IMHO the classic longitudinal to wide situation = multiple rows per subject (with one block of variables) to one row per subject (with multiple blocks of variables).

Could somebody direct me to some answers or tutorials which would cover this?

Thank you very much!

Upon edit, here is what a dput of the original data frame would look like:

# A tibble: 6 x 9
  Subject_ID row_num Date          Q1 Q2_text       Q3    Q4    Q5 Q6_text      
       <dbl>   <dbl> <date>     <dbl> <chr>      <dbl> <dbl> <dbl> <chr>        
1          1       1 2019-01-01     4 Because        5     5     1 and so on    
2          1       2 2019-01-02     1 O, bother      5     4     1 NA           
3          1       3 2019-01-03     2 NA             3     4    NA NA           
4          2       1 2018-12-04    NA NA             1     4     1 NA           
5          3       1 2018-12-15     3 In addtion     5    NA     3 NA           
6          3       2 2018-12-26     1 NA             4     3     2 in conclusion

Answer 1

We could help if you provided some sample data. The web is full of tutorials for using the following functions that do what you are interested in:

gather() and spread() from the tidyr package

melt() and dcast() from the reshape2 package