Tabeline

The main feature of this release is the addition of null support. It also adds Python 3.12 support, which necessitated changing the bounds of dependencies.

* Add Python 3.12 support
* Upgrade to pyarrow 14 (first version with Python 3.12 support) for export to Arrow
* Upgrade to Pandas 2 (2.1 is the first version with Python 3.12 support) for Pandas export
* Upgrade to Polars 0.19
* Put `<3.13` ceiling on Python support. This was needed because NumPy 1.26 (the first version with Python 3.12 support) put a ceiling on its Python support, and in Poetry, this ceiling is viral.
* Add support for nulls
* Add `DataType` enum and apply to `Array`s
* Added `is_null` function
* Made all functions propagate nulls effectively
* Fixed a bug in the NumPy export of `Array`s

One big feature and one small feature:

- `DataFrame` indexing thourgh `df[rows, columns]`
- If `int`, `str`, returns a Python scalar
- If `columns` is a `str`, return a `tabeline.Array` which is basically an array
- If `rows` is an `int`, return a `tabeline.Record` which is basically a dictionary
- If both request multiple items, return a new `tabeline.DataFrame`
- `DataFrame.to_dict(self)` returns a `dict[str, Array]`

This adds a handful of functions that can be used in expressions:

* Casting functions
* `to_boolean(x)`: Convert `x` from a boolean, a float, or an integer, to a boolean
* `to_integer(x)`: Convert `x` from a boolean, a float, or an integer to an integer or parse a string as an integer
* `to_float(x)`: Convert `x` from a boolean, a float, or an integer to a float or parse a string as a float
* `to_string(x)`: Deparse `x` to a string
* `is_finite(x)`: True if `x` value is a floating point finite number
* `same(x)`: One value of `x` if all values of `x` are the same, otherwise error

Duplicate columns in various operations are now properly detected and given a nice error message.

This adds a handful of functions to expressions:

* `arcsin`, `arccos`, `arctan`
* `interp`
* `if_else`

This also adds `concatenate_rows` and `concatenate_columns` as Python functions that take multiple `DataFrame`s and do what you expect.

This release makes two major changes to Tabeline:

- `group` was renamed to `group_by` to be more consistent with the surrounding ecosystem.
- `group` was kept as an alias for backwards compatibility
- `DataTable` was renamed to `DataFrame` to be more consistent with the surrounding ecosystem
- `DataTable` was kept as an alias for backwards compatibility

In addition, there were some minor changes:

- The required version of Polars was advanced from 0.13 to 0.17.
- Support for Python 3.11 was added.
- A [Contributing](https://tabeline.drhagen.com/contributing/) page was added to the [documentation website](https://tabeline.drhagen.com/)

This provides minor fixes to broken package metadata. There is no change in the behavior of the installed package.