Awkward

Make Awkward-in-Pandas an opt-in feature with likely deprecation, as described in 350. (That's where users can explain their use-cases if they want to keep it.)

Change `metadata` with a `"cache"` into just `cache`, since "metadata" is a legitimate word for scientific data and we don't want a conflict. (It broke Coffea's daily tests.)

This version includes trickarcher's first full example of moving an array to the GPU and computing something on it (ak.num). The necessary code does not exist in PyPI yet, though.

From nsmith-, docstrings are now passed through array manipulations as a `__doc__` parameter (which becomes a `__doc__` attribute on `ak.Array`).

ianna implemented negative `axis` parameters, which includes cases like::

array = ak.Array([
{"x": [1], "y": [[], [1]]},
{"x": [1, 2], "y": [[], [1], [1, 2]]},
{"x": [1, 2, 3], "y": [[], [1], [1, 2], [1, 2, 3]]}])

ak.num(array, axis=-1).tolist() == [{'x': 1, 'y': [0, 1]},
{'x': 2, 'y': [0, 1, 2]},
{'x': 3, 'y': [0, 1, 2, 3]}]

which would be inexpressible with a nonnegative `axis`.

Sorting finally has a high-level function, `ak.sort` (and `ak.argsort`).

Awkward ↔ Apache Arrow conversion now prefers 32-bit Arrow types, if possible, and Awkward arrays can be written to and read from Parquet files.

Awkward Arrays can now be deconstructed into a Mapping of str → NumPy arrays (or binary blobs) and back again using `ak.to_arrayset` and `ak.from_arrayset`. This permits general serialization, though standard formats like Arrow and Parquet are to be preferred for any long-term storage.

Added sort/argsort; kernels are being refactored and documented to prepare for GPU support; performance tuning: RecordArray carry → IndexedArray; `__getitem__` for masked, jagged slices is now correct.

This is the first version of Awkward Array to strictly require Numba 0.50 if Numba is used at all. By incorporating numba/numba5717 in version 0.50, importing Awkward Array does not cause Numba to be imported, yet even the first function JIT'ed by Numba can accept an Awkward Array as an argument because the Numba entry-point registers all Awkward types.

For details, see the [release history](https://awkward-array.readthedocs.io/en/latest/_auto/changelog.html).

Built on pybind 2.4.3.

For details, see the [release history](https://awkward-array.readthedocs.io/en/latest/_auto/changelog.html).

Built on pybind 2.4.3.

For details, see the [release history](https://awkward-array.readthedocs.io/en/latest/_auto/changelog.html).

Built on pybind 2.4.3.