Working tests (excl missing data)

Author: WillAyd

pandas/_libs/groupby.pyx

@@ -131,7 +131,7 @@ def group_rank_object(ndarray[float64_t, ndim=2] out,
     cdef:
         int tiebreak
         Py_ssize_t i, j, N, K
-        int64_t val_start=0, grp_start=0, dups=0, sum_ranks=0
+        int64_t val_start=0, grp_start=0, dups=0, sum_ranks=0, vals_seen=1
         ndarray[int64_t] _as
         bint pct, ascending
 
@@ -160,20 +160,21 @@ def group_rank_object(ndarray[float64_t, ndim=2] out,
                 out[_as[j], 0] = i - grp_start + 1
         elif tiebreak == TIEBREAK_FIRST:
             for j in range(i - dups + 1, i + 1):
-                out[_as[j], 0] = j + 1
-        elif tiebreak == TIEBREAK_FIRST_DESCENDING:
-            for j in range(i - dups + 1, i + 1):
-                out[_as[j], 0]  = 2 * (i - grp_start) - j - dups + 2
+                if ascending:
+                    out[_as[j], 0] = j + 1
+                else:
+                    out[_as[j], 0] = 2 * i - j - dups + 2
         elif tiebreak == TIEBREAK_DENSE:
             for j in range(i - dups + 1, i + 1):
-                out[_as[j], 0] = val_start - grp_start
+                out[_as[j], 0] = vals_seen
 
         if (i == N - 1 or (
                 (values[_as[i], 0] != values[_as[i+1], 0]) and not
                 (values[_as[i], 0] is np.nan and values[_as[i+1], 0] is np.nan)
                 )):
             dups = sum_ranks = 0
             val_start = i
+            vals_seen += 1
 
         if i == N - 1 or labels[_as[i]] != labels[_as[i+1]]:
             if pct:

pandas/_libs/groupby_helper.pxi.in

@@ -457,7 +457,7 @@ def group_rank_{{name}}(ndarray[float64_t, ndim=2] out,
     cdef:
         int tiebreak
         Py_ssize_t i, j, N, K
-        int64_t val_start=0, grp_start=0, dups=0, sum_ranks=0
+        int64_t val_start=0, grp_start=0, dups=0, sum_ranks=0, vals_seen=1
         ndarray[int64_t] _as
         bint pct, ascending
 
@@ -493,20 +493,23 @@ def group_rank_{{name}}(ndarray[float64_t, ndim=2] out,
                         out[_as[j], 0] = 2 * i - j - dups + 2
             elif tiebreak == TIEBREAK_DENSE:
                 for j in range(i - dups + 1, i + 1):
-                    out[_as[j], 0] = val_start - grp_start
+                    out[_as[j], 0] = vals_seen
+
             if (i == N - 1 or (
                     (values[_as[i], 0] != values[_as[i+1], 0]) and not
                     (isnan(values[_as[i], 0]) and
                      isnan(values[_as[i+1], 0])
                     ))):
                 dups = sum_ranks = 0
                 val_start = i
+                vals_seen += 1
 
             if i == N - 1 or labels[_as[i]] != labels[_as[i+1]]:
                 if pct:
                     for j in range(grp_start, i + 1):
                         out[_as[j], 0] = out[_as[j], 0] / (i - grp_start + 1)
                 grp_start = i + 1
+                vals_seen = 1
 
 {{endfor}}