Clean up DataFrame.setitem behavior for duplicate columns

pandas/core/frame.py

@@ -128,6 +128,7 @@
 from pandas.core.arrays.sparse import SparseFrameAccessor
 from pandas.core.construction import extract_array, sanitize_masked_array
 from pandas.core.generic import NDFrame, _shared_docs
+from pandas.core.indexers import check_key_length
 from pandas.core.indexes import base as ibase
 from pandas.core.indexes.api import (
     DatetimeIndex,
@@ -3223,9 +3224,8 @@ def _setitem_array(self, key, value):
             self._check_setitem_copy()
             self.iloc[indexer] = value
         else:
-            if isinstance(value, DataFrame) and self.columns.is_unique:
-                if len(value.columns) != len(key):
-                    raise ValueError("Columns must be same length as key")
+            if isinstance(value, DataFrame):
+                check_key_length(self.columns, key, value)
                 for k1, k2 in zip(key, value.columns):
                     self[k1] = value[k2]
             else:

pandas/core/indexers.py

@@ -1,6 +1,9 @@
 """
 Low-dependency indexing utilities.
 """
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
 import warnings
 
 import numpy as np
@@ -17,6 +20,10 @@
 )
 from pandas.core.dtypes.generic import ABCIndex, ABCSeries
 
+if TYPE_CHECKING:
+    from pandas.core.frame import DataFrame
+    from pandas.core.indexes.base import Index
+
 # -----------------------------------------------------------
 # Indexer Identification
 
@@ -376,6 +383,32 @@ def unpack_1tuple(tup):
     return tup
 
 
+def check_key_length(columns: Index, key, value: DataFrame):
+    """
+    Checks if a key used as indexer has the same length as the columns it is
+    associated with.
+
+    Parameters
+    ----------
+    columns : Index The columns of the DataFrame to index.
+    key : A list-like of keys to index with.
+    value : DataFrame The value to set for the keys.
+
+    Raises
+    ------
+    ValueError: If the length of key is not equal to the number of columns in value
+                or if the number of columns referenced by key is not equal to number
+                of columns.
+    """
+    if columns.is_unique:
+        if len(value.columns) != len(key):
+            raise ValueError("Columns must be same length as key")
+    else:
+        # Missing keys in columns are represented as -1
+        if len(columns.get_indexer_non_unique(key)[0]) != len(value.columns):
+            raise ValueError("Columns must be same length as key")
+
+
 # -----------------------------------------------------------
 # Public indexer validation
 

pandas/tests/frame/indexing/test_setitem.py

@@ -378,11 +378,23 @@ def test_setitem_df_wrong_column_number(self, cols):
     def test_setitem_listlike_indexer_duplicate_columns(self):
         # GH#38604
         df = DataFrame([[1, 2, 3]], columns=["a", "b", "b"])
-        rhs = DataFrame([[10, 11, 12]], columns=["d", "e", "c"])
+        rhs = DataFrame([[10, 11, 12]], columns=["a", "b", "b"])
         df[["a", "b"]] = rhs
         expected = DataFrame([[10, 11, 12]], columns=["a", "b", "b"])
         tm.assert_frame_equal(df, expected)
 
+        df[["c", "b"]] = rhs
+        expected = DataFrame([[10, 11, 12, 10]], columns=["a", "b", "b", "c"])
+        tm.assert_frame_equal(df, expected)
+
+    def test_setitem_listlike_indexer_duplicate_columns_not_equal_length(self):
+        # GH#39403
+        df = DataFrame([[1, 2, 3]], columns=["a", "b", "b"])
+        rhs = DataFrame([[10, 11]], columns=["a", "b"])
+        msg = "Columns must be same length as key"
+        with pytest.raises(ValueError, match=msg):
+            df[["a", "b"]] = rhs
+
 
 class TestDataFrameSetItemWithExpansion:
     def test_setitem_listlike_views(self):