fix: dataframe conditional where axis=1 failing on _NoDefault object is not suscriptable

Author: suzyahyah

doc/source/whatsnew/v3.0.0.rst

@@ -1205,6 +1205,7 @@ Other
 - Bug in :meth:`DataFrame.sort_index` when passing ``axis="columns"`` and ``ignore_index=True`` and ``ascending=False`` not returning a :class:`RangeIndex` columns (:issue:`57293`)
 - Bug in :meth:`DataFrame.sort_values` where sorting by a column explicitly named ``None`` raised a ``KeyError`` instead of sorting by the column as expected. (:issue:`61512`)
 - Bug in :meth:`DataFrame.transform` that was returning the wrong order unless the index was monotonically increasing. (:issue:`57069`)
+- Bug in :meth:`DataFrame.where` where ``axis=1`` argument returns a 'float object is not suscriptable' ``TypeError`` (:issue:`58190`)
 - Bug in :meth:`DataFrame.where` where using a non-bool type array in the function would return a ``ValueError`` instead of a ``TypeError`` (:issue:`56330`)
 - Bug in :meth:`Index.sort_values` when passing a key function that turns values into tuples, e.g. ``key=natsort.natsort_key``, would raise ``TypeError`` (:issue:`56081`)
 - Bug in :meth:`MultiIndex.fillna` error message was referring to ``isna`` instead of ``fillna`` (:issue:`60974`)

pandas/core/internals/managers.py

@@ -431,6 +431,8 @@ def apply(
                             kwargs[k] = obj.iloc[b.mgr_locs.indexer]._values
                         else:
                             kwargs[k] = obj.iloc[:, b.mgr_locs.indexer]._values
+                    elif isinstance(obj, lib._NoDefault):
+                        pass
                     else:
                         # otherwise we have an ndarray
                         kwargs[k] = obj[b.mgr_locs.indexer]

pandas/tests/series/indexing/test_where.py

@@ -443,3 +443,26 @@ def test_where_datetimelike_categorical(tz_naive_fixture):
     res = pd.DataFrame(lvals).where(mask[:, None], pd.DataFrame(rvals))
 
     tm.assert_frame_equal(res, pd.DataFrame(dr))
+
+
+@pytest.mark.parametrize(
+    "original,conditional,expected",
+    [
+        (
+            [[0.0, 0.5, 0.0], [0.1, 0.0, 0.2], [0.2, 0.0, 0.0]],
+            [True, True, False],
+            [[0.0, 0.5, 0.0], [0.1, 0.0, 0.2], [np.nan, np.nan, np.nan]],
+        ),
+        (
+            [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]],
+            [True, False, True],
+            [[1.0, 2.0, 3.0], [np.nan, np.nan, np.nan], [7.0, 8.0, 9.0]],
+        ),
+    ],
+)
+def test_where_axis1(original, conditional, expected):
+    # GH 58190, 58144
+    A = pd.DataFrame(original)
+    res = A.where(Series(conditional), axis=1)
+    expected = pd.DataFrame(expected)
+    tm.assert_frame_equal(res, expected)