TST: [ArrowStringArray] more parameterised testing - part 3 #40755
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simonjayhawkins
added
Testing
| @@ -254,9 +254,9 @@ def test_replace2(self): | |||
| assert (ser[6:10] == -1).all() | |||
| assert (ser[20:30] == -1).all() | |||
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| def test_replace_with_dictlike_and_string_dtype(self): | |||
| def test_replace_with_dictlike_and_string_dtype(self, nullable_string_dtype): | |||
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arrow_string behaves the same as string
>>> pd.__version__
'1.3.0.dev0+1219.gccc6a707e2'
>>>
>>> s = pd.Series(["one", "two", np.nan], dtype="string")
>>>
>>> s
0 one
1 two
2 <NA>
dtype: string
>>>
>>> s.replace({"one": "1", "two": "2"})
0 1
1 2
2 <NA>
dtype: object
>>>
is this correct?
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I would say that's a bug, but that's in any case unrelated for this PR (there are a few open issues related to replace with nullable dtypes, so it might already be covered)
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See eg #40732 (for other nullable dtypes)
pandas/tests/io/test_parquet.py
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| df = pd.DataFrame( | ||
| { | ||
| "a": pd.Series([1, 2, 3], dtype="Int64"), | ||
| "b": pd.Series([1, 2, 3], dtype="UInt32"), | ||
| "c": pd.Series(["a", None, "c"], dtype="string"), | ||
| "d": pd.Series(["a", None, "c"], dtype="arrow_string"), |
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this test is @td.skip_if_no("pyarrow", min_version="0.15.0") so safe to add here.
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maybe not ImportError: pyarrow>=1.0.0 is required for PyArrow backed StringArray.
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Yeah, this test has a minimum of 0.15. I would make a separate, dedicated test for ArrowStringArray
pandas/tests/io/test_parquet.py
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| @@ -812,11 +812,15 @@ def test_write_with_schema(self, pa): | |||
| def test_additional_extension_arrays(self, pa): | |||
| # test additional ExtensionArrays that are supported through the | |||
| # __arrow_array__ protocol | |||
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| from pandas.core.arrays.string_arrow import ArrowStringDtype # noqa: F401 | |||
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force registration of "arrow_string", not strictly necessary but won't be missed as ArrowStringDtype will be removed.
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Thanks! |
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