BUG: Fixed handling of non-list value_vars in melt

doc/source/whatsnew/v0.20.0.txt

@@ -517,3 +517,4 @@ Bug Fixes
 
 - Bug in ``DataFrame.boxplot`` where ``fontsize`` was not applied to the tick labels on both axes (:issue:`15108`)
 - Bug in ``Series.replace`` and ``DataFrame.replace`` which failed on empty replacement dicts (:issue:`15289`)
+- Bug in ``pd.melt`` where passing a tuple value for ``value_vars`` caused a TypeError (:issue:`15348`)

pandas/core/reshape.py

@@ -761,16 +761,18 @@ def melt(frame, id_vars=None, value_vars=None, var_name=None,
     """
     # TODO: what about the existing index?
     if id_vars is not None:
-        if not isinstance(id_vars, (tuple, list, np.ndarray)):
+        if not is_list_like(id_vars):
             id_vars = [id_vars]
         else:
             id_vars = list(id_vars)
     else:
         id_vars = []
 
     if value_vars is not None:
-        if not isinstance(value_vars, (tuple, list, np.ndarray)):
+        if not is_list_like(value_vars):
             value_vars = [value_vars]
+        else:
+            value_vars = list(value_vars)
         frame = frame.loc[:, id_vars + value_vars]
     else:
         frame = frame.copy()

pandas/tests/test_reshape.py

@@ -56,6 +56,19 @@ def test_value_vars(self):
                               columns=['id1', 'id2', 'variable', 'value'])
         tm.assert_frame_equal(result4, expected4)
 
+    def test_value_vars_types(self):
+        expected = DataFrame({'id1': self.df['id1'].tolist() * 2,
+                              'id2': self.df['id2'].tolist() * 2,
+                              'variable': ['A'] * 10 + ['B'] * 10,
+                              'value': (self.df['A'].tolist() +
+                                        self.df['B'].tolist())},
+                             columns=['id1', 'id2', 'variable', 'value'])
+
+        for type_ in (tuple, list, np.array):
+            result = melt(self.df, id_vars=['id1', 'id2'],
+                          value_vars=type_(('A', 'B')))
+            tm.assert_frame_equal(result, expected)
+
     def test_custom_var_name(self):
         result5 = melt(self.df, var_name=self.var_name)
         self.assertEqual(result5.columns.tolist(), ['var', 'value'])