BUG: replace complex64 with complex128

As mentioned in #1098.

Author: tkf

pandas/core/internals.py

@@ -1116,7 +1116,7 @@ def form_blocks(data, axes):
         blocks.append(float_block)
 
     if len(complex_dict):
-        complex_block = _simple_blockify(complex_dict, items, np.complex64)
+        complex_block = _simple_blockify(complex_dict, items, np.complex128)
         blocks.append(complex_block)
 
     if len(int_dict):
@@ -1222,7 +1222,7 @@ def _interleaved_dtype(blocks):
     elif have_dt64 and not have_float and not have_complex:
         return np.datetime64
     elif have_complex:
-        return np.complex64
+        return np.complex128
     else:
         return np.float64
 

pandas/src/inference.pyx

@@ -11,7 +11,7 @@ _TYPE_MAP = {
     np.uint64: 'integer',
     np.float32: 'floating',
     np.float64: 'floating',
-    np.complex64: 'complex',
+    np.complex128: 'complex',
     np.complex128: 'complex',
     np.string_: 'string',
     np.unicode_: 'unicode',
@@ -223,7 +223,7 @@ def maybe_convert_numeric(ndarray[object] values, set na_values):
     cdef:
         Py_ssize_t i, n
         ndarray[float64_t] floats
-        ndarray[complex64_t] complexes
+        ndarray[complex128_t] complexes
         ndarray[int64_t] ints
         bint seen_float = 0
         bint seen_complex = 0
@@ -233,7 +233,7 @@ def maybe_convert_numeric(ndarray[object] values, set na_values):
     n = len(values)
 
     floats = np.empty(n, dtype='f8')
-    complexes = np.empty(n, dtype='c8')
+    complexes = np.empty(n, dtype='c16')
     ints = np.empty(n, dtype='i8')
 
     for i from 0 <= i < n:
@@ -278,7 +278,7 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0,
     cdef:
         Py_ssize_t i, n
         ndarray[float64_t] floats
-        ndarray[complex64_t] complexes
+        ndarray[complex128_t] complexes
         ndarray[int64_t] ints
         ndarray[uint8_t] bools
         bint seen_float = 0
@@ -293,7 +293,7 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0,
     n = len(objects)
 
     floats = np.empty(n, dtype='f8')
-    complexes = np.empty(n, dtype='c8')
+    complexes = np.empty(n, dtype='c16')
     ints = np.empty(n, dtype='i8')
     bools = np.empty(n, dtype=np.uint8)
 

pandas/tests/test_frame.py

@@ -1693,7 +1693,7 @@ def test_constructor_scalar_inference(self):
         self.assert_(df['int'].dtype == np.int64)
         self.assert_(df['bool'].dtype == np.bool_)
         self.assert_(df['float'].dtype == np.float64)
-        self.assert_(df['complex'].dtype == np.complex64)
+        self.assert_(df['complex'].dtype == np.complex128)
         self.assert_(df['object'].dtype == np.object_)
 
     def test_constructor_DataFrame(self):

pandas/tests/test_internals.py

@@ -27,7 +27,7 @@ def get_float_ex(cols=['a', 'c', 'e']):
     return make_block(floats, cols, TEST_COLS)
 
 def get_complex_ex(cols=['h']):
-    complexes = (get_float_mat(N, 1).T * 1j).astype(np.complex64)
+    complexes = (get_float_mat(N, 1).T * 1j).astype(np.complex128)
     return make_block(complexes, cols, TEST_COLS)
 
 def get_obj_ex(cols=['b', 'd']):
@@ -211,7 +211,7 @@ def test_block_id_vector_item_dtypes(self):
 
         result = self.mgr.item_dtypes
         expected = ['float64', 'object', 'float64', 'object', 'float64',
-                    'bool', 'int64', 'complex64']
+                    'bool', 'int64', 'complex128']
         self.assert_(np.array_equal(result, expected))
 
     def test_union_block_items(self):