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BUG: Fix regression when using Series with arrow string array #52076

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Mar 22, 2023
Merged

BUG: Fix regression when using Series with arrow string array #52076

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eb75042
BUG: Fix regression when using Series with arrow string array
phofl Mar 19, 2023
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phofl Mar 21, 2023
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1 change: 0 additions & 1 deletion pandas/_libs/lib.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -752,7 +752,6 @@ cpdef ndarray[object] ensure_string_array(
out = arr.astype(str).astype(object)
out[arr.isna()] = na_value
return out

arr = arr.to_numpy()
elif not util.is_array(arr):
arr = np.array(arr, dtype="object")
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3 changes: 3 additions & 0 deletions pandas/core/arrays/string_.py
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Expand Up @@ -352,6 +352,9 @@ def _from_sequence(cls, scalars, *, dtype: Dtype | None = None, copy: bool = Fal
result[na_values] = libmissing.NA

else:
if hasattr(scalars, "type"):
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Why can't we do an actual isinstance check?

If we have some helper method is_pyarrow_array like the following, this should be quite easy?

def is_pyarrow_array(obj):
    if _pyarrow_installed:
        return isinstance(obj, pa.Array)
    return False

with variables _pyarrow_installed and pa filled in once on first import.

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PR that does this -> #52830

# pyarrow array
scalars = np.array(scalars)
# convert non-na-likes to str, and nan-likes to StringDtype().na_value
result = lib.ensure_string_array(scalars, na_value=libmissing.NA, copy=copy)

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2 changes: 2 additions & 0 deletions pandas/core/arrays/string_arrow.py
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Expand Up @@ -151,6 +151,8 @@ def _from_sequence(cls, scalars, dtype: Dtype | None = None, copy: bool = False)
result = scalars._data
result = lib.ensure_string_array(result, copy=copy, convert_na_value=False)
return cls(pa.array(result, mask=na_values, type=pa.string()))
elif isinstance(scalars, (pa.Array, pa.ChunkedArray)):
return cls(pc.cast(scalars, pa.string()))

# convert non-na-likes to str
result = lib.ensure_string_array(scalars, copy=copy)
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8 changes: 8 additions & 0 deletions pandas/tests/extension/test_arrow.py
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Expand Up @@ -2353,6 +2353,14 @@ def test_concat_empty_arrow_backed_series(dtype):
tm.assert_series_equal(result, expected)


@pytest.mark.parametrize("dtype", ["string", "string[pyarrow]"])
def test_series_from_string_array(dtype):
arr = pa.array("the quick brown fox".split())
ser = pd.Series(arr, dtype=dtype)
expected = pd.Series(ArrowExtensionArray(arr), dtype=dtype)
tm.assert_series_equal(ser, expected)


# _data was renamed to _pa_data
class OldArrowExtensionArray(ArrowExtensionArray):
def __getstate__(self):
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