Backport PR #42644: BUG: KeyError when a series popped from data frame with bool indexer

doc/source/whatsnew/v1.3.2.rst

@@ -15,6 +15,7 @@ including other versions of pandas.
 Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - Performance regression in :meth:`DataFrame.isin` and :meth:`Series.isin` for nullable data types (:issue:`42714`)
+- Regression in updating values of :class:`pandas.Series` using boolean index, created by using :meth:`pandas.DataFrame.pop` (:issue:`42530`)
 -
 -
 

pandas/core/series.py

@@ -1228,14 +1228,15 @@ def _maybe_update_cacher(
             # a copy
             if ref is None:
                 del self._cacher
+            elif len(self) == len(ref) and self.name in ref.columns:
+                # GH#42530 self.name must be in ref.columns
+                # to ensure column still in dataframe
+                # otherwise, either self or ref has swapped in new arrays
+                ref._maybe_cache_changed(cacher[0], self)
             else:
-                if len(self) == len(ref):
-                    # otherwise, either self or ref has swapped in new arrays
-                    ref._maybe_cache_changed(cacher[0], self)
-                else:
-                    # GH#33675 we have swapped in a new array, so parent
-                    #  reference to self is now invalid
-                    ref._item_cache.pop(cacher[0], None)
+                # GH#33675 we have swapped in a new array, so parent
+                #  reference to self is now invalid
+                ref._item_cache.pop(cacher[0], None)
 
         super()._maybe_update_cacher(clear=clear, verify_is_copy=verify_is_copy)
 

pandas/tests/series/indexing/test_setitem.py

@@ -8,6 +8,7 @@
 
 from pandas import (
     Categorical,
+    DataFrame,
     DatetimeIndex,
     Index,
     MultiIndex,
@@ -906,3 +907,17 @@ def val(self):
     def is_inplace(self, obj):
         # This is specific to the 4 cases currently implemented for this class.
         return obj.dtype.kind != "i"
+
+
+def test_setitem_with_bool_indexer():
+    # GH#42530
+
+    df = DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]})
+    result = df.pop("b")
+    result[[True, False, False]] = 9
+    expected = Series(data=[9, 5, 6], name="b")
+    tm.assert_series_equal(result, expected)
+
+    df.loc[[True, False, False], "a"] = 10
+    expected = DataFrame({"a": [10, 2, 3]})
+    tm.assert_frame_equal(df, expected)