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Revert "ENH: Improve performance for df.__setitem__ with list-like indexers" #38208

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Dec 1, 2020
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8 changes: 0 additions & 8 deletions asv_bench/benchmarks/indexing.py
Original file line number Diff line number Diff line change
Expand Up @@ -358,14 +358,6 @@ 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:

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1 change: 0 additions & 1 deletion doc/source/whatsnew/v1.1.5.rst
Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,6 @@ 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`)
- Fixed performance regression in ``df.groupby(..).rolling(..)`` (:issue:`38038`)
- Fixed regression in :meth:`MultiIndex.intersection` returning duplicates when at least one of the indexes had duplicates (:issue:`36915`)

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13 changes: 11 additions & 2 deletions pandas/core/indexing.py
Original file line number Diff line number Diff line change
Expand Up @@ -672,8 +672,17 @@ def _ensure_listlike_indexer(self, key, axis=None, value=None):
and not com.is_bool_indexer(key)
and all(is_hashable(k) for k in key)
):
keys = self.obj.columns.union(key, sort=False)
self.obj._mgr = self.obj._mgr.reindex_axis(keys, 0)
for i, k in enumerate(key):
if k not in self.obj:
if value is None:
self.obj[k] = np.nan
elif is_array_like(value) and value.ndim == 2:
# GH#37964 have to select columnwise in case of array
self.obj[k] = value[:, i]
elif is_list_like(value):
self.obj[k] = value[i]
else:
self.obj[k] = value

def __setitem__(self, key, value):
if isinstance(key, tuple):
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