For anyone stumbling across a similar problem, this answered my question: conditional sums for pandas aggregate
I've had success doing a normal groupby on data like this...
score | type |
--------------------
1 | type1 |
3 | type6 |
5 | type4 |
3 | type21 |
2 | type3 |
4 | type1 |
...etc...
ideal output
That resulted in something like this...
score | type |
--------------------
5 | 882 |
4 | 183 |
3 | 458 |
2 | 1156 |
1 | 10934 |
But I want to be able to take the unique values of the "type" column into account and end up with something more like this...
score | type1 | type 2 | type 3 ... etc.
------------------------------
5 | 20 | 4 | .. |
4 | 3 | 17 | .. |
3 | 1 | 12 | .. |
2 | 14 | 9 | .. |
1 | 70 | 13 | .. |
I'm not sure if a groupby is the right approach but I've been banging my head against this and need help.
