diff --git a/sparsity/sparse_frame.py b/sparsity/sparse_frame.py
index 9574e5b..6f015c6 100644
--- a/sparsity/sparse_frame.py
+++ b/sparsity/sparse_frame.py
@@ -789,7 +789,7 @@ def drop_duplicate_idx(self, **kwargs):
 
         Returns
         -------
-        dropeed: SparseFrame
+        dropped: SparseFrame
         """
         mask = ~self.index.duplicated(**kwargs)
         return SparseFrame(self.data[mask], index=self.index.values[mask],
@@ -798,7 +798,10 @@ def drop_duplicate_idx(self, **kwargs):
     def __getitem__(self, item):
         if item is None:
             raise ValueError('Cannot label index with a null key.')
-        if not isinstance(item, (tuple, list)):
+        if not isinstance(item, (pd.Series, np.ndarray, pd.Index, list,
+                                 tuple)):
+            # TODO: tuple probably should be a separate case as in Pandas
+            #  where it is used with Multiindex
             item = [item]
         if len(item) > 0:
             return self.reindex_axis(item, axis=1)
diff --git a/sparsity/test/test_sparse_frame.py b/sparsity/test/test_sparse_frame.py
index 3295c95..44b21f0 100644
--- a/sparsity/test/test_sparse_frame.py
+++ b/sparsity/test/test_sparse_frame.py
@@ -6,6 +6,7 @@
 
 import numpy as np
 import pandas as pd
+import pandas.testing as pdt
 import pytest
 from moto import mock_s3
 from scipy import sparse
@@ -575,6 +576,7 @@ def test_npz_io_s3(complex_example):
 def test_getitem():
     id_ = np.identity(10)
     sf = SparseFrame(id_, columns=list('abcdefghij'))
+
     assert sf['a'].data.todense()[0] == 1
     assert sf['j'].data.todense()[9] == 1
     assert np.all(sf[['a', 'b']].data.todense() == np.asmatrix(id_[:, [0, 1]]))
@@ -588,6 +590,13 @@ def test_getitem():
     with pytest.raises(ValueError):
         sf[None]
 
+    idx = pd.Index(list('abc'))
+    pdt.assert_index_equal(idx, sf[idx].columns)
+    pdt.assert_index_equal(idx, sf[idx.to_series()].columns)
+    pdt.assert_index_equal(idx, sf[idx.tolist()].columns)
+    pdt.assert_index_equal(idx, sf[tuple(idx)].columns)
+    pdt.assert_index_equal(idx, sf[idx.values].columns)
+
 
 def test_vstack():
     frames = []