Rebase and parametrize tests

1. Moved tests to series-/frame-level test_rank (from test_stats) per pandas-dev#15658.
2. Parametrize `series/test_rank` for `pct=True`.

pandas/tests/frame/test_rank.py

@@ -218,7 +218,8 @@ def test_rank_methods_frame(self):
                         expected = expected.astype('float64')
                     tm.assert_frame_equal(result, expected)
 
-    def test_rank_dense_(self):
+    def test_rank_dense_method(self):
+        # GH15630, pct should be on 100% basis even when method='dense'
         df = DataFrame([['2012', 'B', 3], ['2012', 'A', 2], ['2012', 'A', 1]])
         result = df.rank(method='dense', pct=True)
         expected = DataFrame([[1., 1., 1.],

pandas/tests/series/test_rank.py

@@ -287,25 +287,6 @@ def test_rank_dense_method(self):
                 expected = Series(exp).astype(result.dtype)
                 assert_series_equal(result, expected)
 
-    def test_rank_dense_(self):
-        # GH15630, pct should be on 100% basis even when method='dense'
-        in_out = [([1], [1.]),
-                  ([2], [1.]),
-                  ([0], [1.]),
-                  ([2, 2], [1., 1.]),
-                  ([1, 2, 3], [1. / 3, 2. / 3, 3. / 3]),
-                  ([4, 2, 1], [3. / 3, 2. / 3, 1. / 3],),
-                  ([1, 1, 5, 5, 3], [1. / 3, 1. / 3, 3. / 3, 3. / 3, 2. / 3]),
-                  ([-5, -4, -3, -2, -1],
-                   [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])]
-
-        for ser, exp in in_out:
-            for dtype in dtypes:
-                s = Series(ser).astype(dtype)
-                result = s.rank(method='dense', pct=True)
-                expected = Series(exp).astype(result.dtype)
-                assert_series_equal(result, expected)
-
     def test_rank_descending(self):
         dtypes = ['O', 'f8', 'i8']
 
@@ -341,3 +322,23 @@ def test_rank_object_bug(self):
         # smoke tests
         Series([np.nan] * 32).astype(object).rank(ascending=True)
         Series([np.nan] * 32).astype(object).rank(ascending=False)
+
+
+@pytest.mark.parametrize('dtype', ['O', 'f8', 'i8'])
+@pytest.mark.parametrize('ser, exp', [
+    ([1], [1.]),
+    ([2], [1.]),
+    ([0], [1.]),
+    ([2, 2], [1., 1.]),
+    ([1, 2, 3], [1. / 3, 2. / 3, 3. / 3]),
+    ([4, 2, 1], [3. / 3, 2. / 3, 1. / 3],),
+    ([1, 1, 5, 5, 3], [1. / 3, 1. / 3, 3. / 3, 3. / 3, 2. / 3]),
+    ([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
+def test_rank_pct(dtype, ser, exp):
+        # GH15630, pct should be on 100% basis even when method='dense'
+        # TODO: add other methods (i.e. 'average', 'min', 'max', 'first')
+
+        s = Series(ser).astype(dtype)
+        result = s.rank(method='dense', pct=True)
+        expected = Series(exp).astype(result.dtype)
+        assert_series_equal(result, expected)