CLN: ASV categoricals benchmark
- Split classes from `Categoricals/2/3` --> `Concat`, `ValueCounts`, `Rank`, `Repr`, `SetCategories`, and `Constructor`

- Utilized `params` and `param_names` for `ValueCounts`

- Added `np.random.seed(1234)` in setup classes where random data is created xref #8144

- Ran flake8 and replaced star imports

```
$ asv run -q -b ^categoricals
[  0.00%] ·· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[  5.88%] ··· Running categoricals.Concat.time_concat                                                                               14.2ms
[ 11.76%] ··· Running categoricals.Concat.time_union                                                                                12.2ms
[ 17.65%] ··· Running categoricals.Constructor.time_constructor_all_nan                                                             54.7ms
[ 23.53%] ··· Running categoricals.Constructor.time_constructor_datetimes                                                           2.22ms
[ 29.41%] ··· Running categoricals.Constructor.time_constructor_datetimes_with_nat                                                  2.32ms
[ 35.29%] ··· Running categoricals.Constructor.time_constructor_fastpath                                                            1.59ms
[ 41.18%] ··· Running categoricals.Constructor.time_constructor_regular                                                             48.8ms
[ 47.06%] ··· Running categoricals.Constructor.time_constructor_with_nan                                                             510ms
[ 52.94%] ··· Running categoricals.Rank.time_rank_int                                                                               11.7ms
[ 58.82%] ··· Running categoricals.Rank.time_rank_int_cat                                                                           12.9ms
[ 64.71%] ··· Running categoricals.Rank.time_rank_int_cat_ordered                                                                   12.2ms
[ 70.59%] ··· Running categoricals.Rank.time_rank_string                                                                             520ms
[ 76.47%] ··· Running categoricals.Rank.time_rank_string_cat                                                                        18.3ms
[ 82.35%] ··· Running categoricals.Rank.time_rank_string_cat_ordered                                                                10.2ms
[ 88.24%] ··· Running categoricals.Repr.time_rendering                                                                              1.58ms
[ 94.12%] ··· Running categoricals.SetCategories.time_set_categories                                                                70.7ms
[100.00%] ··· Running categoricals.ValueCounts.time_value_counts                                                                81.2ms;...
```