ENH Add 'axis' argument to sparsefuncs.mean_variance_axis

This PR adds an 'axis' argument to sparsefuncs.mean_variance_axis, making it easier to calculate the columnwise mean/variance of sparse matrices. 

While switching the codebase over to the new functionality, I noticed that  `VarianceThreshold` needlessly converted CSC matrices to CSR. This PR also includes a commit to fix this, as the change fits naturally with the other changes.

(If the immediate need for the new functionality is not obvious: This PR is the first in a series that tries to split up #2514 into a few smaller, easy-to-digest PRs. I plan to commit other PRs that will make use of this one)
True, out of consistency with other methods in sklearn (and scipy in general) that handle the axis argument this way as well (e.g. `count_nonzero` in the same file), but those function don't document that usage, either. I assumed this is an sklearn convention.