Supported data types by the private `_to_numpy` function

[seisman]

Here is a central issue tracking the data types the private _to_numpy function supports. We will add tests for these data types in a series of PRs. Please note that it doesn't mean that PyGMT support these data types.

Numeric Dtypes

• Python built-in types clib.converison._to_numpy: Add tests for numpy arrays of numpy numeric dtypes #3583
  • int
  • float
  • complex
• NumPy array: clib.converison._to_numpy: Add tests for numpy arrays of numpy numeric dtypes #3583
  • int8, int16, int32, int64, longlong
  • uint8, uint16, uint32, uint64, ulonglong
  • float16, float32, float64, longdouble
  • complex64, complex128, clongdouble
• pandas.Series with NumPy dtypes clib.converison._to_numpy: Add tests for numpy arrays of numpy numeric dtypes #3583
  • int8, int16, int32, int64, longlong
  • uint8, uint16, uint32, uint64, ulonglong
  • float16, float32, float64, longdouble
  • complex64, complex128, clongdouble
• pandas.Series with pandas/PyArrow dtypes clib.converison._to_numpy: Add tests for pandas.Series with pandas numeric dtypes #3584
  • Int8, Int16, Int32, Int64
  • UInt8, UInt16, UInt32, UInt64
  • Float32, Float64
  • int8[pyarrow], int16[pyarrow], int32[pyarrow], int64[pyarrow]
  • uint8[pyarrow], uint16[pyarrow], uint32[pyarrow], uint64[pyarrow]
  • float16[pyarrow], float32[pyarrow], float64[pyarrow]
• pyarrow.array with PyArrow dtypes clib.conversion._to_numpy: Add tests for pyarrow.array with pyarrow numeric types #3599
  • int8, int16, int32, int64
  • uint8, uint16, uint32, uint64
  • float16, float32, float64

String Dtypes

• Python's built-in list of strings clib.conversion._to_numpy: Add tests for Python list of strings and NumPy array with string type #3601
• NumPy array with string dtype clib.conversion._to_numpy: Add tests for Python list of strings and NumPy array with string type #3601
  • None
  • np.str_
  • "U10"
• pandas.Series with string dtype clib.conversion._to_numpy: Add tests for pandas.Series with pandas string dtype #3607
  • None
  • np.str_
  • "U10"
  • string[python]
  • string[pyarrow]
  • string[pyarrow_numpy]
• pyarrow.array with string dtype clib.conversion._to_numpy: Add tests for pyarrow.array with pyarrow string types #3608
  • None
  • string
  • utf8
  • large_string
  • large_utf8
  • string_view

Datetime dtypes

• Python sequence of datetime-like objects: clib.conversion._to_numpy: Add tests for Python sequence of datetime-like objects #3758
  • ISO 8601 string format
  • datetime.date
  • datetime.datetime
  • datetime.time
  • np.datetime64
  • pandas.Timestamp
  • pyarrow.TimestampScalar
• NumPy datetime64 clib.conversion._to_numpy: Add tests for numpy array with np.datetime64 dtypes #3687
  • date unit: Y, M, W, D
  • time unit: h, m, s, ms, us, ns
  • time unit: ps, fs, as
• pandas.Series
  • np.datetime64 clib.conversion._to_numpy: Add tests for pandas.Series with datetime dtypes #3670
  • pandas.DatetimeTZDtype clib.conversion._to_numpy: Add tests for pandas.Series with datetime dtypes #3670
  • pa.timestamp clib.conversion._to_numpy: Add tests for pandas.Series with datetime dtypes #3670
  • pa.date32/date32[D][pyarrow] clib.conversion._to_numpy: Add tests for pandas.Series with pyarrow date32/date64 types #3610
  • pa.date64/date64[ms][pyarrow] clib.conversion._to_numpy: Add tests for pandas.Series with pyarrow date32/date64 types #3610
  • pa.time32
  • pa.time64
• pyarrow.array
  • date32 clib.conversion._to_numpy: Add tests for pyarrow.array with date32/date64 dtype #3609
  • date64 clib.conversion._to_numpy: Add tests for pyarrow.array with date32/date64 dtype #3609
  • timestamp clib.conversion._to_numpy: Add tests for PyArrow's timestamp type #3621
  • time32
  • time64

Timedelta dtypes

Bool