BUG: support fused types in roll_min/max #12373
- Closes #12373
- Added test_rolling_min_max_types to test_window.py
- passes `git diff upstream/master | flake8 --diff`

Ran the performance tests with no changes detected:

$ asv continuous -b 'stat_op.*rolling' upstream/master GH12373
· Creating environments
· Discovering benchmarks
·· Uninstalling from py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
·· Building for py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt..................................................
·· Installing into py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt..
· Running 18 total benchmarks (2 commits \* 1 environments \* 9 benchmarks)
[  0.00%] · For pandas commit hash 170fb27a:
[  0.00%] ·· Building for py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt.......................................................
[  0.00%] ·· Benchmarking py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[  5.56%] ··· Running stat_ops.stats_rolling_mean.time_rolling_kurt                                                                                                                                  11.39ms
[ 11.11%] ··· Running stat_ops.stats_rolling_mean.time_rolling_max                                                                                                                                    7.48ms
[ 16.67%] ··· Running stat_ops.stats_rolling_mean.time_rolling_mean                                                                                                                                   7.22ms
[ 22.22%] ··· Running stat_ops.stats_rolling_mean.time_rolling_median                                                                                                                               114.21ms
[ 27.78%] ··· Running stat_ops.stats_rolling_mean.time_rolling_min                                                                                                                                    7.55ms
[ 33.33%] ··· Running stat_ops.stats_rolling_mean.time_rolling_skew                                                                                                                                  11.35ms
[ 38.89%] ··· Running stat_ops.stats_rolling_mean.time_rolling_std                                                                                                                                    9.13ms
[ 44.44%] ··· Running stat_ops.stats_rolling_mean.time_rolling_sum                                                                                                                                    6.93ms
[ 50.00%] ··· Running stat_ops.stats_rolling_mean.time_rolling_var                                                                                                                                    7.98ms
[ 50.00%] · For pandas commit hash 56e285a6:
[ 50.00%] ·· Building for py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt.......................................................
[ 50.00%] ·· Benchmarking py2.7-Cython-matplotlib-numexpr-numpy-openpyxl-pytables-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 55.56%] ··· Running stat_ops.stats_rolling_mean.time_rolling_kurt                                                                                                                                  11.66ms
[ 61.11%] ··· Running stat_ops.stats_rolling_mean.time_rolling_max                                                                                                                                    8.68ms
[ 66.67%] ··· Running stat_ops.stats_rolling_mean.time_rolling_mean                                                                                                                                   7.48ms
[ 72.22%] ··· Running stat_ops.stats_rolling_mean.time_rolling_median                                                                                                                               107.71ms
[ 77.78%] ··· Running stat_ops.stats_rolling_mean.time_rolling_min                                                                                                                                    8.74ms
[ 83.33%] ··· Running stat_ops.stats_rolling_mean.time_rolling_skew                                                                                                                                  11.53ms
[ 88.89%] ··· Running stat_ops.stats_rolling_mean.time_rolling_std                                                                                                                                    9.25ms
[ 94.44%] ··· Running stat_ops.stats_rolling_mean.time_rolling_sum                                                                                                                                    6.97ms
[100.00%] ··· Running stat_ops.stats_rolling_mean.time_rolling_var                                                                                                                                    8.24msBENCHMARKS NOT SIGNIFICANTLY CHANGED.
