Backport PR pandas-dev#38148: ENH: Improve performance for df.__setit…

…em__ with list-like indexers

asv_bench/benchmarks/indexing.py

@@ -358,6 +358,14 @@ def time_assign_with_setitem(self):
         for i in range(100):
             self.df[i] = np.random.randn(self.N)
 
+    def time_assign_list_like_with_setitem(self):
+        np.random.seed(1234)
+        self.df[list(range(100))] = np.random.randn(self.N, 100)
+
+    def time_assign_list_of_columns_concat(self):
+        df = DataFrame(np.random.randn(self.N, 100))
+        concat([self.df, df], axis=1)
+
 
 class ChainIndexing:
 

doc/source/whatsnew/v1.1.5.rst

@@ -23,6 +23,7 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrame.groupby` aggregation with out-of-bounds datetime objects in an object-dtype column (:issue:`36003`)
 - Fixed regression in ``df.groupby(..).rolling(..)`` with the resulting :class:`MultiIndex` when grouping by a label that is in the index (:issue:`37641`)
 - Fixed regression in :meth:`DataFrame.fillna` not filling ``NaN`` after other operations such as :meth:`DataFrame.pivot` (:issue:`36495`).
+- Fixed performance regression for :meth:`DataFrame.__setitem__` with list-like indexers (:issue:`37954`)
 
 .. ---------------------------------------------------------------------------
 

pandas/core/indexing.py

@@ -654,9 +654,8 @@ def _ensure_listlike_indexer(self, key, axis=None):
             and not com.is_bool_indexer(key)
             and all(is_hashable(k) for k in key)
         ):
-            for k in key:
-                if k not in self.obj:
-                    self.obj[k] = np.nan
+            keys = self.obj.columns.union(key, sort=False)
+            self.obj._mgr = self.obj._mgr.reindex_axis(keys, 0)
 
     def __setitem__(self, key, value):
         if isinstance(key, tuple):