BUG: astype(float) in Index does the wrong thing

doc/source/v0.14.1.txt

@@ -229,7 +229,8 @@ Bug Fixes
 
 
 
-
+- Bug in ``Index.astype(float)`` where it would return an ``object`` dtype
+  ``Index`` (:issue:`7464`).
 
 
 

pandas/core/index.py

@@ -140,6 +140,8 @@ def __new__(cls, data, dtype=None, copy=False, name=None, fastpath=False,
 
             if issubclass(data.dtype.type, np.integer):
                 return Int64Index(data, copy=copy, dtype=dtype, name=name)
+            if issubclass(data.dtype.type, np.floating):
+                return Float64Index(data, copy=copy, dtype=dtype, name=name)
 
             subarr = com._asarray_tuplesafe(data, dtype=object)
 
@@ -1986,7 +1988,8 @@ def inferred_type(self):
     def astype(self, dtype):
         if np.dtype(dtype) not in (np.object, np.float64):
             raise TypeError('Setting %s dtype to anything other than '
-                            'float64 or object is not supported' % self.__class__)
+                            'float64 or object is not supported' %
+                            self.__class__)
         return Index(self.values, name=self.name, dtype=dtype)
 
     def _convert_scalar_indexer(self, key, typ=None):
@@ -2020,7 +2023,7 @@ def get_value(self, series, key):
         k = _values_from_object(key)
         loc = self.get_loc(k)
         new_values = series.values[loc]
-        if np.isscalar(new_values):
+        if np.isscalar(new_values) or new_values is None:
             return new_values
 
         new_index = self[loc]

pandas/tests/test_index.py

@@ -905,6 +905,7 @@ def test_nan_first_take_datetime(self):
         exp = Index([idx[-1], idx[0], idx[1]])
         tm.assert_index_equal(res, exp)
 
+
 class TestFloat64Index(tm.TestCase):
     _multiprocess_can_split_ = True
 
@@ -1041,6 +1042,13 @@ def test_nan_multiple_containment(self):
         np.testing.assert_array_equal(i.isin([np.nan]),
                                       np.array([False, False]))
 
+    def test_astype_from_object(self):
+        index = Index([1.0, np.nan, 0.2], dtype='object')
+        result = index.astype(float)
+        expected = Float64Index([1.0, np.nan, 0.2])
+        tm.assert_equal(result.dtype, expected.dtype)
+        tm.assert_index_equal(result, expected)
+
 
 class TestInt64Index(tm.TestCase):
     _multiprocess_can_split_ = True