BUG #11638 return correct dtype for int and float

doc/source/whatsnew/v0.17.1.txt

@@ -164,6 +164,7 @@ Bug Fixes
 - Bug in ``squeeze()`` with zero length arrays (:issue:`11230`, :issue:`8999`)
 - Bug in ``describe()`` dropping column names for hierarchical indexes (:issue:`11517`)
 - Bug in ``DataFrame.pct_change()`` not propagating ``axis`` keyword on ``.fillna`` method (:issue:`11150`)
+- Bug in ``core.common._infer_dtype_from_scalar()`` do not upcast int and float (:issue:`11638`)
 
 
 

pandas/core/common.py

@@ -1002,8 +1002,7 @@ def _infer_fill_value(val):
 
 
 def _infer_dtype_from_scalar(val):
-    """ interpret the dtype from a scalar, upcast floats and ints
-        return the new value and the dtype """
+    """ interpret the dtype from a scalar """
 
     dtype = np.object_
 
@@ -1037,12 +1036,17 @@ def _infer_dtype_from_scalar(val):
     elif is_bool(val):
         dtype = np.bool_
 
-    # provide implicity upcast on scalars
     elif is_integer(val):
-        dtype = np.int64
+        if isinstance(val, int):
+            dtype = np.int64
+        else:
+            dtype = type(val)
 
     elif is_float(val):
-        dtype = np.float64
+        if isinstance(val, float):
+            dtype = np.float64
+        else:
+            dtype = type(val)
 
     elif is_complex(val):
         dtype = np.complex_

pandas/tests/test_common.py

@@ -98,6 +98,37 @@ def test_abc_types(self):
         self.assertIsInstance(pd.Period('2012', freq='A-DEC'), com.ABCPeriod)
 
 
+class TestInferDtype(tm.TestCase):
+    df = pd.DataFrame({'one': np.arange(6, dtype=np.int8)})
+
+    def test_preserves_correct_dtype(self):
+        # Test that data type is preserved . #5782
+
+        self.df.loc[1, 'one'] = 6
+        self.assertEqual(self.df.dtypes.one, np.dtype(np.int8))
+        self.df.one = np.int8(7)
+        self.assertEqual(self.df.dtypes.one, np.dtype(np.int8))
+
+    def test_infer_dtype_from_scalar(self):
+        # Test that _infer_dtype_from_scalar is returning correct dtype for int and float.
+
+        data = np.int8(12)
+        dtype, val = com._infer_dtype_from_scalar(data)
+        self.assertEqual(dtype, np.int8)
+
+        data = 12
+        dtype, val = com._infer_dtype_from_scalar(data)
+        self.assertEqual(dtype, np.int64)
+
+        data = np.float16(2.0)
+        dtype, val = com._infer_dtype_from_scalar(data)
+        self.assertEqual(dtype, np.float16)
+
+        data = np.float(12)
+        dtype, val = com._infer_dtype_from_scalar(data)
+        self.assertEqual(dtype, np.float64)
+
+
 def test_notnull():
     assert notnull(1.)
     assert not notnull(None)