[TUTORIAL] Advanced CTable: Schemas, Mutations, & Nullable Data #718

doc/tutorials/13.ctable-basics.ipynb covers introductory CTable creation and basic queries. Since that tutorial was written, CTable has gained significant tabular capabilities:

• Python dataclass schema definitions with blosc2.field() (src/blosc2/schema.py)
• Dynamic column mutations (append_column, del table[col], column renaming)
• Computed columns using UDF expressions
• Nullable column semantics via NullPolicy (src/blosc2/ctable_nulls.py)

Suggested Work

Create a new Jupyter Notebook at doc/tutorials/13b.ctable-advanced.ipynb (or complement tutorial 13) covering:

1. Dataclass Schema API: Defining structured schemas using dataclasses with typed fields (int32, float64, string, struct).
2. Nullable Columns: Enabling nulls on columns, understanding null masks, using NullPolicy.ZERO vs. NullPolicy.IGNORE, and filtering for null/non-null entries.
3. Computed Columns: Defining columns whose values are computed on the fly from other columns via UDFs.
4. Column Operations: Appending new columns to existing on-disk tables, removing columns, and column renaming without rewriting whole tables.

Bonus points: try to use a real dataset (< 1 MB compressed) that you can make public.