fix(python): Fix DataFrame.__getitem__ for empty list input - df[[]]

py-polars/polars/_utils/getitem.py

@@ -145,20 +145,17 @@ def get_df_item_by_key(
         else:
             return _select_rows(selection, row_key)
 
-    # Single input, e.g. df[1]
-    elif isinstance(key, str):
+    # Single string input, e.g. df["a"]
+    if isinstance(key, str):
         # This case is required because empty strings are otherwise treated
         # as an empty Sequence in `_select_rows`
         return df.get_column(key)
-    elif isinstance(key, Sequence) and len(key) == 0:
-        # df[[]]
-        # TODO: This removes all columns, but it should remove all rows.
-        # https://github.com/pola-rs/polars/issues/4924
-        return df.__class__()
+
+    # Single input - df[1] - or multiple inputs - df["a", "b", "c"]
     try:
         return _select_rows(df, key)  # type: ignore[arg-type]
     except TypeError:
-        return _select_columns(df, key)  # type: ignore[arg-type]
+        return _select_columns(df, key)
 
 
 # `str` overlaps with `Sequence[str]`

py-polars/tests/unit/dataframe/test_getitem.py

@@ -234,6 +234,13 @@ def test_df_getitem_row_range_single_input() -> None:
     assert_frame_equal(result, expected)
 
 
+def test_df_getitem_row_empty_list_single_input() -> None:
+    df = pl.DataFrame({"a": [1, 2], "b": [5.0, 6.0]})
+    result = df[[]]
+    expected = df.clear()
+    assert_frame_equal(result, expected)
+
+
 def test_df_getitem() -> None:
     """Test all the methods to use [] on a dataframe."""
     df = pl.DataFrame({"a": [1.0, 2.0, 3.0, 4.0], "b": [3, 4, 5, 6]})
@@ -287,9 +294,6 @@ def test_df_getitem() -> None:
     # empty list with column selector drops rows but keeps columns
     assert_frame_equal(df[empty, :], df[:0])
 
-    # empty list without column select return empty frame
-    assert_frame_equal(df[empty], pl.DataFrame({}))
-
     # numpy array: assumed to be row indices if integers, or columns if strings
 
     # numpy array: positive idxs and empty idx