jorisvandenbossche commented on a change in pull request #12178:
URL: https://github.com/apache/arrow/pull/12178#discussion_r798436243
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File path: python/pyarrow/tests/test_pandas.py
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@@ -4082,6 +4082,66 @@ def test_array_to_pandas():
# tm.assert_series_equal(result, expected)
+def test_to_pandas_types_mapper():
+ # https://issues.apache.org/jira/browse/ARROW-9664
+ if Version(pd.__version__) < Version("1.0.0"):
+ pytest.skip("ExtensionDtype to_pandas method missing")
+
+ data = pa.array([1, 2, 3], pa.int64())
+
+ # Test with mapper function
+ types_mapper = {pa.int64(): pd.Int64Dtype()}.get
+ result = data.to_pandas(types_mapper=types_mapper)
+ assert result.dtype == types_mapper(data.type)
+
+ # Test mapper function returning None
+ types_mapper = {pa.int64(): None}.get
+ result = data.to_pandas(types_mapper=types_mapper)
+ assert result.dtype == data.type.to_pandas_dtype()
+
+ # Test mapper function not containing the dtype
+ types_mapper = {pa.float64(): pd.Float64Dtype()}.get
+ result = data.to_pandas(types_mapper=types_mapper)
+ assert result.dtype == data.type.to_pandas_dtype()
+
+ # Test for the interval extension dtype
+ # -> ignores mapping and uses default conversion
+ types_mapper = {pa.float64(): pd.IntervalDtype()}.get
+ result = data.to_pandas(types_mapper=types_mapper)
Review comment:
So from an offline discussion: conclusion is that we can just remove
this additional test case with interval dtype, since using the storage type
would not work with pandas, and converting a plain pyarrow array to a pandas
extension dtype is already covered by the int64 case above.
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