BUG: frame.lookup with non-unique axes (#33045)

Author: jbrockmendel

doc/source/whatsnew/v1.1.0.rst

@@ -337,6 +337,7 @@ Indexing
 - Bug in :meth:`DataFrame.loc:` and :meth:`Series.loc` with a :class:`DatetimeIndex`, :class:`TimedeltaIndex`, or :class:`PeriodIndex` incorrectly allowing lookups of non-matching datetime-like dtypes (:issue:`32650`)
 - Bug in :meth:`Series.__getitem__` indexing with non-standard scalars, e.g. ``np.dtype`` (:issue:`32684`)
 - Bug in :class:`Index` constructor where an unhelpful error message was raised for ``numpy`` scalars (:issue:`33017`)
+- Bug in :meth:`DataFrame.lookup` incorrectly raising an ``AttributeError`` when ``frame.index`` or ``frame.columns`` is not unique; this will now raise a ``ValueError`` with a helpful error message (:issue:`33041`)
 
 Missing
 ^^^^^^^

pandas/core/frame.py

@@ -3525,6 +3525,9 @@ def lookup(self, row_labels, col_labels) -> np.ndarray:
         n = len(row_labels)
         if n != len(col_labels):
             raise ValueError("Row labels must have same size as column labels")
+        if not (self.index.is_unique and self.columns.is_unique):
+            # GH#33041
+            raise ValueError("DataFrame.lookup requires unique index and columns")
 
         thresh = 1000
         if not self._is_mixed_type or n > thresh:

pandas/tests/frame/indexing/test_indexing.py

@@ -1424,6 +1424,24 @@ def test_lookup_raises(self, float_frame):
         with pytest.raises(ValueError, match="same size"):
             float_frame.lookup(["a", "b", "c"], ["a"])
 
+    def test_lookup_requires_unique_axes(self):
+        # GH#33041 raise with a helpful error message
+        df = pd.DataFrame(np.random.randn(6).reshape(3, 2), columns=["A", "A"])
+
+        rows = [0, 1]
+        cols = ["A", "A"]
+
+        # homogeneous-dtype case
+        with pytest.raises(ValueError, match="requires unique index and columns"):
+            df.lookup(rows, cols)
+        with pytest.raises(ValueError, match="requires unique index and columns"):
+            df.T.lookup(cols, rows)
+
+        # heterogeneous dtype
+        df["B"] = 0
+        with pytest.raises(ValueError, match="requires unique index and columns"):
+            df.lookup(rows, cols)
+
     def test_set_value(self, float_frame):
         for idx in float_frame.index:
             for col in float_frame.columns: