Improved type checking and tests. Added whatsnew note.

Author: jbradt

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

@@ -761,15 +761,15 @@ 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)

pandas/tests/test_reshape.py

@@ -57,18 +57,17 @@ def test_value_vars(self):
         tm.assert_frame_equal(result4, expected4)
 
     def test_value_vars_types(self):
-        result_with_tuple = melt(self.df, id_vars=['id1', 'id2'], value_vars=('A', 'B'))
-        result_with_array = melt(self.df, id_vars=['id1', 'id2'], value_vars=np.array(['A', 'B']))
-
         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'])
 
-        tm.assert_frame_equal(result_with_tuple, expected)
-        tm.assert_frame_equal(result_with_array, expected)
+        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)