CLN: Update Cython data pointers for rolling apply
- [x] xref #34014
- [x] tests passed
- [x] passes `black pandas`
- [x] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`

Performance looks pretty comparable between master and this PR

```
N = 10 ** 3
arr = 100 * np.random.random(N)
roll = pd.DataFrame(arr).rolling(10)
%timeit roll.apply(lambda x: np.sum(x) + 5, raw=True)

4.48 ms ± 14.8 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) <--PR
4.34 ms ± 29.6 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) <--master
```