updating according to comments

Author: tp

Diff for: doc/source/whatsnew/v0.22.0.txt

@@ -87,7 +87,7 @@ Deprecations
 ~~~~~~~~~~~~
 
 - ``Series.from_array`` and ``SparseSeries.from_array`` are deprecated. Use the normal constructor ``Series(..)`` and ``SparseSeries(..)`` instead (:issue:`18213`).
-- ``NDFrame.as_matrix`` is deprecated. Use ``NDFrame.values`` instead (:issue:`18458`).
+- ``DataFrame.as_matrix`` is deprecated. Use ``DataFrame.values`` instead (:issue:`18458`).
 -
 
 .. _whatsnew_0220.prior_deprecations:

Diff for: pandas/core/generic.py

@@ -3735,8 +3735,8 @@ def _get_bool_data(self):
 
     def as_matrix(self, columns=None):
         """
-        DEPRECATED: This method will be removed in a future version.
-        Use :meth:`NDFrame.values` instead.
+        DEPRECATED: as_matrix will be removed in a future version.
+        Use :meth:`DataFrame.values` instead.
 
         Convert the frame to its Numpy-array representation.
 
@@ -3773,8 +3773,8 @@ def as_matrix(self, columns=None):
         --------
         pandas.DataFrame.values
         """
-        warnings.warn("This method will be removed in a future version. "
-                      "Use ``.values`` instead.")
+        warnings.warn("method ``as_matrix`` will be removed in a future version. "
+                      "Use ``values`` instead.", FutureWarning, stacklevel=2)
         self._consolidate_inplace()
         if self._AXIS_REVERSED:
             return self._data.as_matrix(columns).T
@@ -3797,9 +3797,7 @@ def values(self):
         will result in a flot64 dtype.
         """
         self._consolidate_inplace()
-        if self._AXIS_REVERSED:
-            return self._data.as_matrix().T
-        return self._data.as_matrix()
+        return self._data.as_matrix(transpose=self._AXIS_REVERSED)
 
     @property
     def _values(self):

Diff for: pandas/core/internals.py

@@ -3670,19 +3670,22 @@ def copy(self, deep=True, mgr=None):
         return self.apply('copy', axes=new_axes, deep=deep,
                           do_integrity_check=False)
 
-    def as_matrix(self, items=None):
+    def as_matrix(self, transpose=False, items=None):
         if len(self.blocks) == 0:
-            return np.empty(self.shape, dtype=float)
+            arr = np.empty(self.shape, dtype=float)
+            return arr.transpose() if transpose else arr
 
         if items is not None:
             mgr = self.reindex_axis(items, axis=0)
         else:
             mgr = self
 
         if self._is_single_block or not self.is_mixed_type:
-            return mgr.blocks[0].get_values()
+            arr = mgr.blocks[0].get_values
         else:
-            return mgr._interleave()
+            arr = mgr._interleave()
+
+        return arr.transpose() if transpose else arr
 
     def _interleave(self):
         """

Diff for: pandas/tests/frame/test_api.py

@@ -257,7 +257,7 @@ def test_values(self):
                     assert value == frame[col][i]
 
         # mixed type
-        mat = self.mixed_frame.as_matrix(['foo', 'A'])
+        mat = self.mixed_frame[['foo', 'A']].values
         assert mat[0, 0] == 'bar'
 
         df = self.klass({'real': [1, 2, 3], 'complex': [1j, 2j, 3j]})
@@ -369,6 +369,13 @@ def test_values(self):
         self.frame.values[:, 0] = 5.
         assert (self.frame.values[:, 0] == 5).all()
 
+    def test_as_matrix_deprecated(self):
+        # GH18458
+        with tm.assert_produces_warning(FutureWarning):
+            result = self.frame.as_matrix()
+        expected = self.frame.values
+        tm.assert_numpy_array_equal(result, expected)
+
     def test_deepcopy(self):
         cp = deepcopy(self.frame)
         series = cp['A']

Diff for: pandas/tests/frame/test_block_internals.py

@@ -67,10 +67,10 @@ def test_consolidate_inplace(self):
         for letter in range(ord('A'), ord('Z')):
             self.frame[chr(letter)] = chr(letter)
 
-    def test_as_matrix_consolidate(self):
+    def test_values_consolidate(self):
         self.frame['E'] = 7.
         assert not self.frame._data.is_consolidated()
-        _ = self.frame.as_matrix()  # noqa
+        _ = self.frame.values  # noqa
         assert self.frame._data.is_consolidated()
 
     def test_modify_values(self):
@@ -91,50 +91,50 @@ def test_boolean_set_uncons(self):
         self.frame[self.frame > 1] = 2
         assert_almost_equal(expected, self.frame.values)
 
-    def test_as_matrix_numeric_cols(self):
+    def test_values_numeric_cols(self):
         self.frame['foo'] = 'bar'
 
-        values = self.frame.as_matrix(['A', 'B', 'C', 'D'])
+        values = self.frame[['A', 'B', 'C', 'D']].values
         assert values.dtype == np.float64
 
-    def test_as_matrix_lcd(self):
+    def test_values_lcd(self):
 
         # mixed lcd
-        values = self.mixed_float.as_matrix(['A', 'B', 'C', 'D'])
+        values = self.mixed_float[['A', 'B', 'C', 'D']].values
         assert values.dtype == np.float64
 
-        values = self.mixed_float.as_matrix(['A', 'B', 'C'])
+        values = self.mixed_float[['A', 'B', 'C']].values
         assert values.dtype == np.float32
 
-        values = self.mixed_float.as_matrix(['C'])
+        values = self.mixed_float[['C']].values
         assert values.dtype == np.float16
 
         # GH 10364
         # B uint64 forces float because there are other signed int types
-        values = self.mixed_int.as_matrix(['A', 'B', 'C', 'D'])
+        values = self.mixed_int[['A', 'B', 'C', 'D']].values
         assert values.dtype == np.float64
 
-        values = self.mixed_int.as_matrix(['A', 'D'])
+        values = self.mixed_int[['A', 'D']].values
         assert values.dtype == np.int64
 
         # B uint64 forces float because there are other signed int types
-        values = self.mixed_int.as_matrix(['A', 'B', 'C'])
+        values = self.mixed_int[['A', 'B', 'C']].values
         assert values.dtype == np.float64
 
         # as B and C are both unsigned, no forcing to float is needed
-        values = self.mixed_int.as_matrix(['B', 'C'])
+        values = self.mixed_int[['B', 'C']].values
         assert values.dtype == np.uint64
 
-        values = self.mixed_int.as_matrix(['A', 'C'])
+        values = self.mixed_int[['A', 'C']].values
         assert values.dtype == np.int32
 
-        values = self.mixed_int.as_matrix(['C', 'D'])
+        values = self.mixed_int[['C', 'D']].values
         assert values.dtype == np.int64
 
-        values = self.mixed_int.as_matrix(['A'])
+        values = self.mixed_int[['A']].values
         assert values.dtype == np.int32
 
-        values = self.mixed_int.as_matrix(['C'])
+        values = self.mixed_int[['C']].values
         assert values.dtype == np.uint8
 
     def test_constructor_with_convert(self):