From 1a46ac04fac9eae5c24a0c1d12e5db3b928f3611 Mon Sep 17 00:00:00 2001
From: MichaelTiemann <72577720+MichaelTiemannOSC@users.noreply.github.com>
Date: Wed, 19 Oct 2022 08:08:36 -0400
Subject: [PATCH] Fixes needed to help Pint-Pandas pass tests when
 HAS_UNCERTAINTIES enabled.

Signed-off-by: MichaelTiemann <72577720+MichaelTiemannOSC@users.noreply.github.com>
---
 pandas/core/indexing.py                |  3 ++-
 pandas/tests/extension/base/setitem.py | 26 +++++++++++++++++++++++---
 2 files changed, 25 insertions(+), 4 deletions(-)

diff --git a/pandas/core/indexing.py b/pandas/core/indexing.py
index 913aa2e5b0e18..53f28c1ccc813 100644
--- a/pandas/core/indexing.py
+++ b/pandas/core/indexing.py
@@ -1825,7 +1825,7 @@ def _setitem_with_indexer_split_path(self, indexer, value, name: str):
 
         # we need an iterable, with a ndim of at least 1
         # eg. don't pass through np.array(0)
-        if is_list_like_indexer(value) and getattr(value, "ndim", 1) > 0:
+        if is_list_like_indexer(value) and np.iterable(value) and getattr(value, "ndim", 1) > 0:
 
             if isinstance(value, ABCDataFrame):
                 self._setitem_with_indexer_frame_value(indexer, value, name)
@@ -1977,6 +1977,7 @@ def _setitem_single_column(self, loc: int, value, plane_indexer):
             pass
         elif (
             is_array_like(value)
+            and getattr(value, "shape", False)
             and len(value.shape) > 0
             and self.obj.shape[0] == value.shape[0]
             and not is_empty_indexer(pi)
diff --git a/pandas/tests/extension/base/setitem.py b/pandas/tests/extension/base/setitem.py
index 8dbf7d47374a6..8fabacb2214c5 100644
--- a/pandas/tests/extension/base/setitem.py
+++ b/pandas/tests/extension/base/setitem.py
@@ -1,6 +1,15 @@
 import numpy as np
 import pytest
 
+try:
+    import uncertainties.unumpy as unp
+    from uncertainties import ufloat, UFloat
+    HAS_UNCERTAINTIES = True
+    _ufloat_nan = ufloat(np.nan, 0)
+except ImportError:
+    unp = np
+    HAS_UNCERTAINTIES = False
+
 from pandas.core.dtypes.dtypes import (
     DatetimeTZDtype,
     IntervalDtype,
@@ -97,7 +106,11 @@ def test_setitem_scalar(self, data, setter):
         assert arr[0] == data[1]
 
     def test_setitem_loc_scalar_mixed(self, data):
-        df = pd.DataFrame({"A": np.arange(len(data)), "B": data})
+        if HAS_UNCERTAINTIES:
+            scalar_data = np.arange(len(data)) + ufloat(0, 0)
+        else:
+            scalar_data = np.arange(len(data))
+        df = pd.DataFrame({"A": scalar_data , "B": data})
         df.loc[0, "B"] = data[1]
         assert df.loc[0, "B"] == data[1]
 
@@ -112,7 +125,11 @@ def test_setitem_loc_scalar_multiple_homogoneous(self, data):
         assert df.loc[10, "B"] == data[1]
 
     def test_setitem_iloc_scalar_mixed(self, data):
-        df = pd.DataFrame({"A": np.arange(len(data)), "B": data})
+        if HAS_UNCERTAINTIES:
+            scalar_data = np.arange(len(data)) + ufloat(0, 0)
+        else:
+            scalar_data = np.arange(len(data))
+        df = pd.DataFrame({"A": scalar_data , "B": data})
         df.iloc[0, 1] = data[1]
         assert df.loc[0, "B"] == data[1]
 
@@ -427,7 +444,10 @@ def test_delitem_series(self, data):
         # GH#40763
         ser = pd.Series(data, name="data")
 
-        taker = np.arange(len(ser))
+        if HAS_UNCERTAINTIES:
+            taker = np.arange(len(ser)) + ufloat(0, 0)
+        else:
+            taker = np.arange(len(ser))
         taker = np.delete(taker, 1)
 
         expected = ser[taker]