Migrate DatetimeSubtraction to narwhals+numpy, add polars support

[solegalli]

Ports DatetimeSubtraction (extends the already-migrated BaseCreation) to narwhals, adding native polars support and removing the pandas-only computation path, following the RelativeFeatures precedent.

Benchmarked pandas-native vs narwhals+numpy on pandas vs narwhals+numpy on polars at 10k/50k/100k rows x 1/2/10 datetime-pair combinations. Extracting each unique variable to a numpy datetime64 array once, then subtracting and dividing with plain numpy ops, is a clear MERGE win - no is_pandas branch needed for the arithmetic itself:

rows=100000 pairs=10 | pandas_native=5.934ms | narwhals+numpy(pandas)=
3.011ms (0.51x) | narwhals+numpy(polars)=1.282ms (0.22x)

End-to-end (including datetime parsing), the new pandas path is also consistently faster than the old pandas-only implementation (0.55x-0.96x across the grid), and polars is 4-20x faster than pandas at scale once parsing cost is amortized over more rows. "Y"/"M" output units are non-linear numpy timedelta units, so both the diff and the unit divisor are cast to timedelta64[ns] before dividing (numpy can't otherwise find a common divisor) - this mirrors what pandas does internally for Timedelta / Timedelta and was verified against all 14 supported output_unit values.

Datetime parsing (dayfirst/yearfirst/utc/format) is inherently backend-specific, so it keeps a real is_pandas branch: the pandas path calls pandas.to_datetime via nw.get_native_namespace() (no "import pandas") to preserve exact prior behaviour; the non-pandas path uses narwhals' str.to_datetime first, then falls back to per-value dateutil parsing (honouring dayfirst/yearfirst/utc) for ambiguous formats narwhals can't infer - the same flexible, cross-backend date guessing check_datetime_variables/find_datetime_variables already promise, so a column that passes fit() can always be parsed in transform() on any backend.

No bugs found in DatetimeSubtraction itself. Two pre-existing failures in test_datetime_features.py (DatetimeFeatures index/NaN handling) and 68 repo-wide pre-existing failures elsewhere are unchanged before/after this change (confirmed via git stash) and belong to other, not-yet-migrated modules.

Rewrote tests/test_datetime/test_datetime_subtraction.py to parametrize every dataframe-dependent test over pandas and polars via make_df (122 tests, up from 83), and added a "With polars" section to DatetimeSubtraction.rst, verifying every doc example (old and new) against actual output.