PERF: clipping with scalar
Removes conversion of boolean series to array-like in `_clip_with_scalar`.

- [x] closes #41434
- [x] tests added / passed
- [x] Ensure all linting tests pass, see [here](https://pandas.pydata.org/pandas-docs/dev/development/contributing.html#code-standards) for how to run them
- [ ] whatsnew entry

I may also add type annotations to `_clip_with_scalar`, let me know if that's welcome.

> I may also add type annotations to `_clip_with_scalar`, let me know if that's welcome.

always welcome. separate PR OK can you show the asv's on this. Here it is:
```
[ 50.00%] · For pandas commit ef773a6d <time-clip-perf> (round 2/2):
[ 50.00%] ·· Benchmarking conda-py3.8-Cython0.29.21-jinja2-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 75.00%] ··· series_methods.Clip.time_clip                                   ok
[ 75.00%] ··· ======== =============
                 n                  
              -------- -------------
                 50       492±40μs  
                1000      502±30μs  
               100000   1.46±0.05ms 
              ======== =============

[ 75.00%] · For pandas commit 3f67dc33 <master> (round 2/2):
[ 75.00%] ·· Building for conda-py3.8-Cython0.29.21-jinja2-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 75.00%] ·· Benchmarking conda-py3.8-Cython0.29.21-jinja2-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[100.00%] ··· series_methods.Clip.time_clip                                   ok
[100.00%] ··· ======== =============
                 n                  
              -------- -------------
                 50       540±30μs  
                1000      611±40μs  
               100000   1.79±0.09ms 
              ======== =============
```
that we can also compare with before the regression:
```
[ 50.00%] · For pandas commit 4f3acf10 <stash~155> (round 2/2):
[ 50.00%] ·· Benchmarking conda-py3.8-Cython0.29.21-jinja2-matplotlib-numba-numexpr-numpy-odfpy-openpyxl-pytables-pytest-scipy-sqlalchemy-xlrd-xlsxwriter-xlwt
[ 75.00%] ··· series_methods.Clip.time_clip                                   ok
[ 75.00%] ··· ======== =============
                 n                  
              -------- -------------
                 50       411±40μs  
                1000      449±20μs  
               100000   1.56±0.06ms 
              ======== =============
``` thanks @TLouf 