BUG: Fix quantile calculation pandas-dev#33200

Author: mabelvj

pandas/_libs/groupby.pyx

@@ -779,10 +779,9 @@ def group_quantile(ndarray[float64_t] out,
                 non_na_counts[lab] += 1
 
     # Get an index of values sorted by labels and then values
-    sort_arr = np.arange(len(labels), dtype=np.int64)
-    mask = labels != -1
-    order = (np.asarray(values)[mask], labels[mask])
-    sort_arr[mask] = np.lexsort(order).astype(np.int64, copy=False)
+    labels[labels==-1] = np.max(labels) + 1
+    order = (values, labels)
+    sort_arr= np.lexsort(order).astype(np.int64, copy=False)
     with nogil:
         for i in range(ngroups):
             # Figure out how many group elements there are
@@ -820,9 +819,7 @@ def group_quantile(ndarray[float64_t] out,
 
             # Increment the index reference in sorted_arr for the next group
             grp_start += grp_sz
-    print(out)
-    # out = np.roll(out, -(len(out) - np.sum(counts)))
-    print(out)
+
 
 # ----------------------------------------------------------------------
 # group_nth, group_last, group_rank

pandas/tests/groupby/test_function.py

@@ -1510,7 +1510,8 @@ def test_quantile_missing_group_values_no_segfaults():
 @pytest.mark.parametrize(
     "key, val, expected_key, expected_val",
     [
-        ([1.0, np.nan, 3.0, np.nan], range(4), [1.0, 3.0], [0.0, 1.0]),
+        ([1.0, np.nan, 3.0, np.nan], range(4), [1.0, 3.0], [0.0, 2.0]),
+        ([1.0, np.nan, 2.0, 2.0], range(4), [1.0, 2.0], [0.0, 2.5]),
         (["a", "b", "b", np.nan], range(4), ["a", "b"], [0, 1.5]),
     ],
 )