Build `clean_column(values, drop_na=True)` — the single most-used data-cleaning helper: - `values` is a list that may contain `None` entries (the pandas convention for missing). - `drop_na=True` (default) → return new list with `None` removed, preserving original order. - `drop_na=False` → return new list unchanged (callers may want imputation downstream). - Empty input → empty list. - Don't mutate the input. This is what every data pipeline calls before fitting a model.