Mixed survey (multiple + single choice) data

Hi all,

I need to analyze mixed survey data. Some of the questions are single choice/user is requirested to provide just one answer, others are multiple choice. Multiple choice questions are of 2 types:

• 1)  assumes 1/0 as acceptable values, e.g.  What kind of music do you prefer?
  • a) Pop/Not Pop (1 or 0)
  • b) Rock/Not Rock,  (1 or 0)
  • c) Classic/Not Classic (1 or 0)

• 2) assumes predefined values, e.g. How long have you been palying guitar?
  • a) 1-2 years
  • b) Do not  remember
  • c) 3-5 years

In total I have 1000 users, each user is identified by record id. The dataset has 1000 rows (one for each user), about 30-35 questions and 1500 columns (in one 1/0 -type question I have 30 different options to choose => 30 columns to cover just one question).

user q1a1  q1a2  q1a3   q1a4     q2a1   q2a2    q2a3    q3

1       1          0        0         1            1        7         4       25

2       0          1        1         0            0        3         1       20
etc

The data as it arrives (1500 columns) becomes quite unmanageable and my first idea was to unpivot it. So from the format one user - one row and many columns I passed to one user - multiple rows and one column (to store all the responses). 

user  Attribute  Value                                 

1      q1a1              1           

1      q1a4              1

1       q2a1              1

1       q2a2              7

1       q2a3              4 

1       q3                  20

The format seems quite suitable to visualize single questions, but when I need to do conditional counts, i.e. users who prefer rock and play guitar and do smth else, this becomes tricky because when I select one question as a filter, others diappear (and this is quite normal).

What I want is to be able to show for those who  prefer Rock what are their answers on the other questions. 
I have already tried several models but struggle to create one flexible and simple enough at the same time. Keep 1500 columns is not an option, unpivot everything doesn't seem a suitable choice as well. I don't think that my dataset is unique and I'm quite sure that there should be an elegant solution, but I'm just missing something.

Any ideas/advice how to organize the data?

Thanks in advance,
Victoria