Minor Description
In Spark 0.9, the PySpark version of StatCounter worked with an RDD of numpy arrays just as with an RDD of scalars, which was very useful (e.g. for computing stats on a set of vectors in ML analyses). In 1.0.0 this broke because the added functionality for computing the minimum and maximum, as implemented, doesn't work on arrays.
I have a PR ready that re-enables this functionality by having StatCounter use the numpy element-wise functions "maximum" and "minimum", which work on both numpy arrays and scalars (and I've added new tests for this capability).
However, I realize this adds a dependency on NumPy outside of MLLib. If that's not ok, maybe it'd be worth adding this functionality as a util within PySpark MLLib?
