BUG: support for "level=" when reset_index() is called with a flat Index

doc/source/whatsnew/v0.20.2.txt

@@ -42,7 +42,7 @@ Conversion
 Indexing
 ^^^^^^^^
 
-
+- Bug in ``DataFrame.reset_index(level=)`` with single level index (:issue:`16263`)
 
 
 I/O

pandas/core/frame.py

@@ -3012,12 +3012,12 @@ def _maybe_casted_values(index, labels=None):
             return values
 
         new_index = _default_index(len(new_obj))
-        if isinstance(self.index, MultiIndex):
-            if level is not None:
-                if not isinstance(level, (tuple, list)):
-                    level = [level]
-                level = [self.index._get_level_number(lev) for lev in level]
-                if len(level) < len(self.index.levels):
+        if level is not None:
+            if not isinstance(level, (tuple, list)):
+                level = [level]
+            level = [self.index._get_level_number(lev) for lev in level]
+            if isinstance(self.index, MultiIndex):
+                if len(level) < self.index.nlevels:
                     new_index = self.index.droplevel(level)
 
         if not drop:
@@ -3033,6 +3033,8 @@ def _maybe_casted_values(index, labels=None):
 
             multi_col = isinstance(self.columns, MultiIndex)
             for i, (lev, lab) in reversed(list(enumerate(to_insert))):
+                if not (level is None or i in level):
+                    continue
                 name = names[i]
                 if multi_col:
                     col_name = (list(name) if isinstance(name, tuple)
@@ -3049,11 +3051,9 @@ def _maybe_casted_values(index, labels=None):
                     missing = self.columns.nlevels - len(name_lst)
                     name_lst += [col_fill] * missing
                     name = tuple(name_lst)
-
                 # to ndarray and maybe infer different dtype
                 level_values = _maybe_casted_values(lev, lab)
-                if level is None or i in level:
-                    new_obj.insert(0, name, level_values)
+                new_obj.insert(0, name, level_values)
 
         new_obj.index = new_index
         if not inplace:

pandas/tests/frame/test_alter_axes.py

@@ -641,6 +641,43 @@ def test_reset_index(self):
         xp = xp.set_index(['B'], append=True)
         assert_frame_equal(rs, xp, check_names=False)
 
+    def test_reset_index_level(self):
+        df = pd.DataFrame([[1, 2, 3, 4], [5, 6, 7, 8]],
+                          columns=['A', 'B', 'C', 'D'])
+
+        for levels in ['A', 'B'], [0, 1]:
+            # With MultiIndex
+            result = df.set_index(['A', 'B']).reset_index(level=levels[0])
+            tm.assert_frame_equal(result, df.set_index('B'))
+
+            result = df.set_index(['A', 'B']).reset_index(level=levels[:1])
+            tm.assert_frame_equal(result, df.set_index('B'))
+
+            result = df.set_index(['A', 'B']).reset_index(level=levels)
+            tm.assert_frame_equal(result, df)
+
+            result = df.set_index(['A', 'B']).reset_index(level=levels,
+                                                          drop=True)
+            tm.assert_frame_equal(result, df[['C', 'D']])
+
+            # With single-level Index (GH 16263)
+            result = df.set_index('A').reset_index(level=levels[0])
+            tm.assert_frame_equal(result, df)
+
+            result = df.set_index('A').reset_index(level=levels[:1])
+            tm.assert_frame_equal(result, df)
+
+            result = df.set_index(['A']).reset_index(level=levels[0],
+                                                     drop=True)
+            tm.assert_frame_equal(result, df[['B', 'C', 'D']])
+
+        # Missing levels - for both MultiIndex and single-level Index:
+        for idx_lev in ['A', 'B'], ['A']:
+            with tm.assert_raises_regex(KeyError, 'Level E '):
+                df.set_index(idx_lev).reset_index(level=['A', 'E'])
+            with tm.assert_raises_regex(IndexError, 'Too many levels'):
+                df.set_index(idx_lev).reset_index(level=[0, 1, 2])
+
     def test_reset_index_right_dtype(self):
         time = np.arange(0.0, 10, np.sqrt(2) / 2)
         s1 = Series((9.81 * time ** 2) / 2,

pandas/tests/series/test_alter_axes.py

@@ -141,6 +141,45 @@ def test_reset_index(self):
         tm.assert_index_equal(rs.index, Index(index.get_level_values(1)))
         assert isinstance(rs, Series)
 
+    def test_reset_index_level(self):
+        df = pd.DataFrame([[1, 2, 3], [4, 5, 6]],
+                          columns=['A', 'B', 'C'])
+
+        for levels in ['A', 'B'], [0, 1]:
+            # With MultiIndex
+            s = df.set_index(['A', 'B'])['C']
+
+            result = s.reset_index(level=levels[0])
+            tm.assert_frame_equal(result, df.set_index('B'))
+
+            result = s.reset_index(level=levels[:1])
+            tm.assert_frame_equal(result, df.set_index('B'))
+
+            result = s.reset_index(level=levels)
+            tm.assert_frame_equal(result, df)
+
+            result = df.set_index(['A', 'B']).reset_index(level=levels,
+                                                          drop=True)
+            tm.assert_frame_equal(result, df[['C']])
+
+            with tm.assert_raises_regex(KeyError, 'Level E '):
+                s.reset_index(level=['A', 'E'])
+
+            # With single-level Index
+            s = df.set_index('A')['B']
+
+            result = s.reset_index(level=levels[0])
+            tm.assert_frame_equal(result, df[['A', 'B']])
+
+            result = s.reset_index(level=levels[:1])
+            tm.assert_frame_equal(result, df[['A', 'B']])
+
+            result = s.reset_index(level=levels[0], drop=True)
+            tm.assert_series_equal(result, df['B'])
+
+            with tm.assert_raises_regex(IndexError, 'Too many levels'):
+                s.reset_index(level=[0, 1, 2])
+
     def test_reset_index_range(self):
         # GH 12071
         s = pd.Series(range(2), name='A', dtype='int64')