Merge branch 'indexing_ndim_0' into string_dtype_tests

# Conflicts:
#	doc/source/whatsnew/v2.1.2.rst

Author: phofl

doc/source/whatsnew/v2.1.2.rst

@@ -25,6 +25,7 @@ Bug fixes
 - Fixed bug in :meth:`DataFrame.interpolate` raising incorrect error message (:issue:`55347`)
 - Fixed bug in :meth:`DataFrame.resample` not respecting ``closed`` and ``label`` arguments for :class:`~pandas.tseries.offsets.BusinessDay` (:issue:`55282`)
 - Fixed bug in :meth:`DataFrame.resample` where bin edges were not correct for :class:`~pandas.tseries.offsets.BusinessDay` (:issue:`55281`)
+- Fixed bug in :meth:`DataFrame.__setitem__` not inferring string dtype for zero-dimensional array with ``infer_string=True`` (:issue:`TODO`)
 - Fixed bug in :meth:`Categorical.equals` if other has arrow backed string dtype (:issue:`TODO`)
 - Fixed bug in :meth:`Index.insert` raising when inserting ``None`` into :class:`Index` with ``dtype="string[pyarrow_numpy]"`` (issue:`TODO`)
 - Fixed bug in :meth:`Series.rank` for ``string[pyarrow_numpy]`` dtype (:issue:`TODO`)

pandas/core/construction.py

@@ -562,7 +562,14 @@ def sanitize_array(
     if not is_list_like(data):
         if index is None:
             raise ValueError("index must be specified when data is not list-like")
-        data = construct_1d_arraylike_from_scalar(data, len(index), dtype)
+        if isinstance(data, str) and using_pyarrow_string_dtype():
+            from pandas.core.arrays.string_ import StringDtype
+
+            dtype = StringDtype("pyarrow_numpy")
+            data = dtype.construct_array_type()._from_sequence_of_strings([data])
+        else:
+            data = construct_1d_arraylike_from_scalar(data, len(index), dtype)
+
         return data
 
     elif isinstance(data, ABCExtensionArray):

pandas/tests/frame/indexing/test_indexing.py

@@ -1918,6 +1918,18 @@ def test_adding_new_conditional_column() -> None:
     tm.assert_frame_equal(df, expected)
 
 
+def test_add_new_column_infer_string():
+    # GH#
+    df = DataFrame({"x": [1]})
+    with pd.option_context("future.infer_string", True):
+        df.loc[df["x"] == 1, "y"] = "1"
+    expected = DataFrame(
+        {"x": [1], "y": Series(["1"], dtype="string[pyarrow_numpy]")},
+        columns=Index(["x", "y"], dtype="string[pyarrow_numpy]"),
+    )
+    tm.assert_frame_equal(df, expected)
+
+
 class TestSetitemValidation:
     # This is adapted from pandas/tests/arrays/masked/test_indexing.py
     # but checks for warnings instead of errors.