CLN: fix asv setup_cache() for groupby.AggFunctions benchmarks
This PR fixes a typo in an `asv` benchmark and additionally clarifies a misleading result.

Simply fixing the typo leads to this rather surprising result where the single column benchmark is ~6x slower than the multi-column benchmark:
```
$ asv dev -b groupby.AggFunctions
· Discovering benchmarks
· Running 4 total benchmarks (1 commits * 1 environments * 4 benchmarks)
[  0.00%] ·· Benchmarking existing-py_home_chris_anaconda3_bin_python
[ 12.50%] ··· Setting up groupby.py:213                                                                                                                                   ok
[ 12.50%] ··· groupby.AggFunctions.time_different_numpy_functions                                                                                                   53.7±0ms
[ 25.00%] ··· groupby.AggFunctions.time_different_python_functions_multicol                                                                                         84.7±0ms
[ 37.50%] ··· groupby.AggFunctions.time_different_python_functions_singlecol                                                                                         483±0ms
[ 50.00%] ··· groupby.AggFunctions.time_different_str_functions                                                                                                     46.0±0ms
```
Fortunately, the difference is solely due to the inclusion of a `str` column in the single column case. Therefore, we drop that column to keep the comparison comparable:
```
$ asv run HEAD -b groupby.AggFunctions
· Creating environments
· Discovering benchmarks..
·· Uninstalling from conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt...
·· Building d3fa9d67 <groupby_agg_functions> for conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt.............................
·· Installing d3fa9d67 <groupby_agg_functions> into conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt....
· Running 53900 total benchmarks (13475 commits * 1 environments * 4 benchmarks)
[  0.00%] · For pandas commit d3fa9d67 <groupby_agg_functions>:
[  0.00%] ·· Benchmarking conda-py3.6-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[  0.00%] ··· Setting up groupby.py:213                                                                                                                                   ok
[  0.00%] ··· Running (groupby.AggFunctions.time_different_numpy_functions--)....
[  0.00%] ··· groupby.AggFunctions.time_different_numpy_functions                                                                                                   23.2±3ms
[  0.01%] ··· groupby.AggFunctions.time_different_python_functions_multicol                                                                                        70.2±10ms
[  0.01%] ··· groupby.AggFunctions.time_different_python_functions_singlecol                                                                                       38.5±10ms
[  0.01%] ··· groupby.AggFunctions.time_different_str_functions                                                                                                   22.4±0.3ms
```
- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry
