I'd like to recruit your help in coming up with an Excel-based method to analyse a set of raw ordering data where each item is on its own row. 

So, in the data below, order 111 contains two part numbers, ABC and DEF, in quantities of 2 and 3, respectively.

```
Order Number | Part Number | Quantity |
111          | ABC         |     2    |
111          | DEF         |     3    |
222          | ABC         |     1    |
333          | ABC         |     4    |
333          | DEF         |     4    |

```

You can think of ABC as peanut butter and DEF as jelly. Usually they're ordered in a 1:1 ratio, but someone may be a heavy peanut butter user and only order peanut butter (as in order 222).

The part number array is large, let's say in the several hundreds (peanut butter, jelly, apple butter, fluffernutter, lemon curd, whatever).

I'd like to be able to answer:

* For a given part number (ABC, for example) what is the most commonly ordered
partner part number (peanut butter, ABC, is usually paired with jelly, DEF, 83% of the time, apple butter, 3%, by itself 14%) and
* What is the ratio of the queried part number against its partner? (peanut butter:jelly = 0.8 because jelly goes faster usually)