ASV: add frame ops benchmarks for varying n_rows/n_columns ratios
Currently, we have a benchmark for frame/frame ops with a wide dataframe (originating from previous (long) PR / discussion about this, xref https://github.com/pandas-dev/pandas/pull/32779)

To get a better idea of the trade-offs for future changes to the ops code (eg ArrayManager related), I think it is useful to have this benchmark for a varying rows/columns ratio (it is mostly this ratio that determines how much overhead we have when performing ops column-wise). 

So I changed the benchmark to be parametrized over 4 different ratios, from a long to a wide dataframe, and with each case having the same number of total elements in the dataframe. 

The shape in the original benchmark was `(500, 2000)`, which is somewhere in between two new cases of  `(10_000, 1000)` and `(1000, 10_000)`, so that should preserve the original intent of the benchmark (the last case of `(1000, 10_000)` even has a lower row/column ratio, so should even be a "worse" case for the column-wise ops perspective).

cc @jbrockmendel 