Awkward

veprbl fixed the warnings in Linux (gcc) and MacOS (clang): everything is clean!

jpivarski added a categorical type with functions like `ak.to_categorical`. This type is high-level only, like the string type, and is used to determine which fields to convert to Arrow/Parquet's dictionary encoding and which not to. See issue 400.

Fixed 408, a severe error in `ak.argmin` and `ak.argmax`: they returned wrong integer positions for arrays with missing values or variable-length lists with `axis != -1`.

nsmith- filled in missing data in VirtualArrays so they can be used in Numba in more situations.

reikdas cleaned up the kernel tests.

jpivarski fixed some bugs in the Numba implementation, enabled functions like `enumerate` and `zip`, added GitHub URLs to all exceptions for faster investigation of bugs, and abstracted the use of NumPy so that the Python-side calculations can be swapped for CuPy.

Updated the awkward1-cuda-kernels build and testing process. This is the first regular release of awkward1-cuda-kernels as a PyPI package, and henceforth all awkward1 PyPI releases will be accompanied by a awkward1-cuda-kernels PyPI release with the same version number.

Renamed and fixed ak.values_astype, added Pandas-style ak.Array constructor, and other touch-ups as part of writing documentation.

nsmith made ak.from_arrayset "even more lazy" by inserting a VirtualArray in every field of a RecordArray when `lazy=True`.

The website can't be updated unless the bug-fixes that the tutorials require are available as a released version. Thus, this is just a bug-fix release (there may be more, as more documentation gets written).

As per 350, Pandas integration will be deprecated. Starting in version 0.3.0, it won't be possible to use Awkward arrays as Pandas Series or DataFrame columns. We're also giving up on attempts to keep Matplotlib from iterating over non-numeric data. (These are part of a theme of removing sneaky tricks from the code, such as `awkward1._util.called_by_module`, for robustness.)

Updated to backward-incompatible changes in Arrow 1.0.0. Now Arrow 1.0.0 is the minimum version that works with Awkward.

Updated to changes in JupyterBooks to fix documentation.

ianna added a `numbers_to_type` function, which converts all numbers to a given type while maintaining an array's structure.

reikdas generated over three thousand unit tests for the kernels, which previously had only been tested as part of integration tests. Once the blacklist in the test generation framework is reduced to zero, line coverage of kernels will be 100%. Once the samples are carefully chosen in kernel-specification/samples.json, all the important cases will be tested as well. This testing framework will be extended to CUDA kernels as well.

nsmith- added class and class method decorators to simplify the process of adding high-level behaviors.

Internally, all of the "offset" parameters have been removed from kernel argument lists. Instead, correctly offset pointers are passed to these functions, so they can assume that they start from (relative) array index zero. Several previously fixed bugs have been traced to this and in the conversion, I found a few more suspicious spots—now we don't have to worry about it anymore.

Still built on pybind 2.4.3, though we might want to update that, especially if pybind supports the NumPy datetime dtypes.