REGR: non-unique, masked dtype index raising IndexError (#57061)

* fix masked indexing regression

* fix test

* fix test

* dedup resizing logic

* add types

Author: lukemanley

doc/source/whatsnew/v2.2.1.rst

@@ -17,6 +17,7 @@ Fixed regressions
 - Fixed performance regression in :meth:`Series.combine_first` (:issue:`55845`)
 - Fixed regression in :func:`merge_ordered` raising ``TypeError`` for ``fill_method="ffill"`` and ``how="left"`` (:issue:`57010`)
 - Fixed regression in :func:`wide_to_long` raising an ``AttributeError`` for string columns (:issue:`57066`)
+- Fixed regression in :meth:`DataFrame.loc` raising ``IndexError`` for non-unique, masked dtype indexes where result has more than 10,000 rows (:issue:`57027`)
 - Fixed regression in :meth:`DataFrameGroupBy.idxmin`, :meth:`DataFrameGroupBy.idxmax`, :meth:`SeriesGroupBy.idxmin`, :meth:`SeriesGroupBy.idxmax` ignoring the ``skipna`` argument (:issue:`57040`)
 - Fixed regression in :meth:`DataFrameGroupBy.idxmin`, :meth:`DataFrameGroupBy.idxmax`, :meth:`SeriesGroupBy.idxmin`, :meth:`SeriesGroupBy.idxmax` where values containing the minimum or maximum value for the dtype could produce incorrect results (:issue:`57040`)
 - Fixed regression in :meth:`Index.join` raising ``TypeError`` when joining an empty index to a non-empty index containing mixed dtype values (:issue:`57048`)

pandas/_libs/index.pyx

@@ -98,6 +98,20 @@ cdef ndarray _get_bool_indexer(ndarray values, object val, ndarray mask = None):
     return indexer.view(bool)
 
 
+cdef _maybe_resize_array(ndarray values, Py_ssize_t loc, Py_ssize_t max_length):
+    """
+    Resize array if loc is out of bounds.
+    """
+    cdef:
+        Py_ssize_t n = len(values)
+
+    if loc >= n:
+        while loc >= n:
+            n *= 2
+        values = np.resize(values, min(n, max_length))
+    return values
+
+
 # Don't populate hash tables in monotonic indexes larger than this
 _SIZE_CUTOFF = 1_000_000
 
@@ -456,27 +470,18 @@ cdef class IndexEngine:
             # found
             if val in d:
                 key = val
-
+                result = _maybe_resize_array(
+                    result,
+                    count + len(d[key]) - 1,
+                    max_alloc
+                )
                 for j in d[key]:
-
-                    # realloc if needed
-                    if count >= n_alloc:
-                        n_alloc *= 2
-                        if n_alloc > max_alloc:
-                            n_alloc = max_alloc
-                        result = np.resize(result, n_alloc)
-
                     result[count] = j
                     count += 1
 
             # value not found
             else:
-
-                if count >= n_alloc:
-                    n_alloc *= 2
-                    if n_alloc > max_alloc:
-                        n_alloc = max_alloc
-                    result = np.resize(result, n_alloc)
+                result = _maybe_resize_array(result, count, max_alloc)
                 result[count] = -1
                 count += 1
                 missing[count_missing] = i
@@ -1214,37 +1219,31 @@ cdef class MaskedIndexEngine(IndexEngine):
 
             if PySequence_GetItem(target_mask, i):
                 if na_pos:
+                    result = _maybe_resize_array(
+                        result,
+                        count + len(na_pos) - 1,
+                        max_alloc,
+                    )
                     for na_idx in na_pos:
-                        # realloc if needed
-                        if count >= n_alloc:
-                            n_alloc *= 2
-                            if n_alloc > max_alloc:
-                                n_alloc = max_alloc
-
                         result[count] = na_idx
                         count += 1
                     continue
 
             elif val in d:
                 # found
                 key = val
-
+                result = _maybe_resize_array(
+                    result,
+                    count + len(d[key]) - 1,
+                    max_alloc,
+                )
                 for j in d[key]:
-
-                    # realloc if needed
-                    if count >= n_alloc:
-                        n_alloc *= 2
-                        if n_alloc > max_alloc:
-                            n_alloc = max_alloc
-
                     result[count] = j
                     count += 1
                 continue
 
             # value not found
-            if count >= n_alloc:
-                n_alloc += 10_000
-                result = np.resize(result, n_alloc)
+            result = _maybe_resize_array(result, count, max_alloc)
             result[count] = -1
             count += 1
             missing[count_missing] = i

pandas/tests/indexing/test_loc.py

@@ -3347,3 +3347,15 @@ def test_getitem_loc_str_periodindex(self):
             index = pd.period_range(start="2000", periods=20, freq="B")
             series = Series(range(20), index=index)
             assert series.loc["2000-01-14"] == 9
+
+    def test_loc_nonunique_masked_index(self):
+        # GH 57027
+        ids = list(range(11))
+        index = Index(ids * 1000, dtype="Int64")
+        df = DataFrame({"val": np.arange(len(index), dtype=np.intp)}, index=index)
+        result = df.loc[ids]
+        expected = DataFrame(
+            {"val": index.argsort(kind="stable").astype(np.intp)},
+            index=Index(np.array(ids).repeat(1000), dtype="Int64"),
+        )
+        tm.assert_frame_equal(result, expected)