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pyarrow: Support pyarrow arrays with string/large_string/string_view types #3619

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merged 1 commit into from
Nov 15, 2024
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pyarrow: Support pyarrow arrays with string/large_string/string_view types #3619

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11 changes: 8 additions & 3 deletions pygmt/clib/conversion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -156,8 +156,13 @@ def _to_numpy(data: Any) -> np.ndarray:
array
The C contiguous NumPy array.
"""
# Mapping of unsupported dtypes to the expected NumPy dtype.
dtypes: dict[str, str | type] = {
# Mapping of unsupported dtypes to expected NumPy dtypes.
dtypes: dict[str, type | str] = {
# For string dtypes.
"large_string": np.str_, # pa.large_string and pa.large_utf8
"string": np.str_, # pa.string and pa.utf8
"string_view": np.str_, # pa.string_view
# For datetime dtypes.
"date32[day][pyarrow]": "datetime64[D]",
"date64[ms][pyarrow]": "datetime64[ms]",
}
Expand All @@ -173,7 +178,7 @@ def _to_numpy(data: Any) -> np.ndarray:
# we can remove the workaround in PyGMT v0.17.0.
array = np.ascontiguousarray(data.astype(float))
else:
vec_dtype = str(getattr(data, "dtype", ""))
vec_dtype = str(getattr(data, "dtype", getattr(data, "type", "")))
array = np.ascontiguousarray(data, dtype=dtypes.get(vec_dtype))
return array

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