bringing tests back from 1.1.x

Author: stevenae

pandas/tests/frame/indexing/test_indexing.py

@@ -1414,6 +1414,72 @@ def test_loc_named_tuple_for_midx(self):
         )
         tm.assert_frame_equal(result, expected)
 
+    def test_lookup_float(self, float_frame):
+        df = float_frame
+        rows = list(df.index) * len(df.columns)
+        cols = list(df.columns) * len(df.index)
+        result = df.lookup(rows, cols)
+
+        expected = np.array([df.loc[r, c] for r, c in zip(rows, cols)])
+        tm.assert_numpy_array_equal(result, expected)
+
+    def test_lookup_mixed(self, float_string_frame):
+        df = float_string_frame
+        rows = list(df.index) * len(df.columns)
+        cols = list(df.columns) * len(df.index)
+        result = df.lookup(rows, cols)
+
+        expected = np.array(
+            [df.loc[r, c] for r, c in zip(rows, cols)], dtype=np.object_
+        )
+        tm.assert_almost_equal(result, expected)
+
+    def test_lookup_bool(self):
+        df = DataFrame(
+            {
+                "label": ["a", "b", "a", "c"],
+                "mask_a": [True, True, False, True],
+                "mask_b": [True, False, False, False],
+                "mask_c": [False, True, False, True],
+            }
+        )
+        df["mask"] = df.lookup(df.index, "mask_" + df["label"])
+
+        exp_mask = np.array(
+            [df.loc[r, c] for r, c in zip(df.index, "mask_" + df["label"])]
+        )
+
+        tm.assert_series_equal(df["mask"], Series(exp_mask, name="mask"))
+        assert df["mask"].dtype == np.bool_
+
+    def test_lookup_raises(self, float_frame):
+        with pytest.raises(KeyError, match="'One or more row labels was not found'"):
+            float_frame.lookup(["xyz"], ["A"])
+
+        with pytest.raises(KeyError, match="'One or more column labels was not found'"):
+            float_frame.lookup([float_frame.index[0]], ["xyz"])
+
+        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 = DataFrame(np.random.Generator(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)
+
     @pytest.mark.parametrize("indexer", [["a"], "a"])
     @pytest.mark.parametrize("col", [{}, {"b": 1}])
     def test_set_2d_casting_date_to_int(self, col, indexer):