PERF: improved clip performance
closes #15400
In [1]: np.random.seed(1234)

In [2]: s = pd.Series(np.random.randn(50))

master
```
In [3]: %timeit s.clip(0, 1)
1.65 ms ± 48.2 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
```

PR
```
In [3]: %timeit s.clip(0, 1)
124 µs ± 2.79 µs per loop (mean ± std. dev. of 7 runs, 10000 loops each)
```

prob as good as can do for now as we still have 2 where ops (numpy does this in a single loop), and we have a mask check and fill (and final construction).

but about 15x better