ARROW-2298: [Python] Add unit tests to assert that float64 with NaN v…

…alues can be safely coerced to integer types when converting from pandas

This code used to fail in the past, but it has been fixed sometime since the issue was reported back in October 2018. This test case asserts the correct behavior so it can be maintained.

Author: Wes McKinney <[email protected]>

Closes #4682 from wesm/ARROW-2298 and squashes the following commits:

33d485e <Wes McKinney> Add unit tests to assert desired behavior according to JIRA issue

python/pyarrow/tests/test_pandas.py

@@ -767,6 +767,23 @@ def test_float_object_nulls(self):
         _check_pandas_roundtrip(df, expected=expected,
                                 expected_schema=schema)
 
+    def test_float_with_null_as_integer(self):
+        # ARROW-2298
+        s = pd.Series([np.nan, 1., 2., np.nan])
+
+        types = [pa.int8(), pa.int16(), pa.int32(), pa.int64(),
+                 pa.uint8(), pa.uint16(), pa.uint32(), pa.uint64()]
+        for ty in types:
+            result = pa.array(s, type=ty)
+            expected = pa.array([None, 1, 2, None], type=ty)
+            assert result.equals(expected)
+
+            df = pd.DataFrame({'has_nulls': s})
+            schema = pa.schema([pa.field('has_nulls', ty)])
+            result = pa.Table.from_pandas(df, schema=schema,
+                                          preserve_index=False)
+            assert result[0].data.chunk(0).equals(expected)
+
     def test_int_object_nulls(self):
         arr = np.array([None, 1, np.int64(3)] * 5, dtype=object)
         df = pd.DataFrame({'ints': arr})