diff --git a/py-polars/polars/_utils/construction/dataframe.py b/py-polars/polars/_utils/construction/dataframe.py
index c20a60c3162e..1986525eb290 100644
--- a/py-polars/polars/_utils/construction/dataframe.py
+++ b/py-polars/polars/_utils/construction/dataframe.py
@@ -1020,6 +1020,11 @@ def pandas_to_pydf(
 ) -> PyDataFrame:
     """Construct a PyDataFrame from a pandas DataFrame."""
     convert_index = include_index and not _pandas_has_default_index(data)
+    if convert_index and set(data.index.names).intersection(data.columns):
+        msg = (
+            "cannot create DataFrame with some index name duplicating some column name"
+        )
+        raise ValueError(msg)
     if not convert_index and all(
         is_simple_numpy_backed_pandas_series(data[col]) for col in data.columns
     ):
diff --git a/py-polars/tests/unit/interop/test_interop.py b/py-polars/tests/unit/interop/test_interop.py
index b357c12ff1f4..0d28dcb587e1 100644
--- a/py-polars/tests/unit/interop/test_interop.py
+++ b/py-polars/tests/unit/interop/test_interop.py
@@ -179,6 +179,74 @@ def test_from_pandas_duplicated_columns() -> None:
         pl.from_pandas(df)
 
 
+def test_from_pandas_exclude_index() -> None:
+    data = pd.DataFrame({"a": [1, 2], "b": [3, 4]}, index=pd.Index([5, 6], name="c"))
+    df = pl.from_pandas(data, include_index=False)
+    assert df.columns == ["a", "b"]
+    assert df.rows() == [(1, 3), (2, 4)]
+
+
+def test_from_pandas_include_index() -> None:
+    data = pd.DataFrame({"a": [1, 2], "b": [3, 4]}, index=pd.Index([5, 6], name="c"))
+    df = pl.from_pandas(data, include_index=True)
+    assert df.columns == ["c", "a", "b"]
+    assert df.rows() == [(5, 1, 3), (6, 2, 4)]
+
+
+def test_from_pandas_exclude_dup_index() -> None:
+    data = pd.DataFrame({"a": [1, 2], "b": [3, 4]}, index=pd.Index([5, 6], name="a"))
+    df = pl.from_pandas(data, include_index=False)
+    assert df.columns == ["a", "b"]
+    assert df.rows() == [(1, 3), (2, 4)]
+
+
+def test_from_pandas_include_dup_index() -> None:
+    data = pd.DataFrame({"a": [1, 2], "b": [3, 4]}, index=pd.Index([5, 6], name="a"))
+
+    with pytest.raises(ValueError):
+        pl.from_pandas(data, include_index=True)
+
+
+def test_from_pandas_exclude_multi_index() -> None:
+    data = pd.DataFrame(
+        {"a": [1, 2], "b": [3, 4]},
+        index=pd.MultiIndex.from_arrays([(5, 6), (7, 8)], names=["c", "d"]),
+    )
+    df = pl.from_pandas(data, include_index=False)
+    assert df.columns == ["a", "b"]
+    assert df.rows() == [(1, 3), (2, 4)]
+
+
+def test_from_pandas_include_multi_index() -> None:
+    data = pd.DataFrame(
+        {"a": [1, 2], "b": [3, 4]},
+        index=pd.MultiIndex.from_arrays([(5, 6), (7, 8)], names=["c", "d"]),
+    )
+    df = pl.from_pandas(data, include_index=True)
+    assert df.columns == ["c", "d", "a", "b"]
+    assert df.rows() == [(5, 7, 1, 3), (6, 8, 2, 4)]
+
+
+def test_from_pandas_exclude_dup_multi_index() -> None:
+    data = pd.DataFrame(
+        {"a": [1, 2], "b": [3, 4]},
+        index=pd.MultiIndex.from_arrays([(5, 6), (7, 8)], names=["b", "c"]),
+    )
+    df = pl.from_pandas(data, include_index=False)
+    assert df.columns == ["a", "b"]
+    assert df.rows() == [(1, 3), (2, 4)]
+
+
+def test_from_pandas_include_dup_multi_index() -> None:
+    data = pd.DataFrame(
+        {"a": [1, 2], "b": [3, 4]},
+        index=pd.MultiIndex.from_arrays([(5, 6), (7, 8)], names=["b", "c"]),
+    )
+
+    with pytest.raises(ValueError):
+        pl.from_pandas(data, include_index=True)
+
+
 def test_arrow_list_roundtrip() -> None:
     # https://github.com/pola-rs/polars/issues/1064
     tbl = pa.table({"a": [1], "b": [[1, 2]]})