PERF: categorical rank GH#15498

no need to rename categories where they are already ordered

Author: jeet63

pandas/core/algorithms.py

@@ -974,6 +974,9 @@ def _get_data_algo(values, func_map):
 
     f = None
 
+    if is_categorical_dtype(values):
+        values = values._values_for_rank()
+
     if is_float_dtype(values):
         f = func_map['float64']
         values = _ensure_float64(values)
@@ -990,10 +993,6 @@ def _get_data_algo(values, func_map):
         f = func_map['uint64']
         values = _ensure_uint64(values)
 
-    elif is_categorical_dtype(values):
-        f = func_map['float64']
-        values = values._values_for_rank()
-
     else:
         values = _ensure_object(values)
 

pandas/core/categorical.py

@@ -1420,9 +1420,11 @@ def _values_for_rank(self):
         if self.ordered:
             values = self.codes
             mask = values == -1
-            values = values.astype('float64')
             if mask.any():
+                values = values.astype('float64')
                 values[mask] = np.nan
+        elif self.categories.is_monotonic:
+            values = np.array(self)
         else:
             values = np.array(
                 self.rename_categories(Series(self.categories).rank())

pandas/tests/series/test_analytics.py

@@ -1083,6 +1083,16 @@ def test_rank_categorical(self):
         res = unordered.rank()
         assert_series_equal(res, exp_unordered)
 
+        unordered1 = pd.Series(
+            [1, 2, 3, 4, 5, 6],
+        ).astype('category').cat.set_categories(
+            [1, 2, 3, 4, 5, 6],
+            ordered=False
+        )
+        exp_unordered1 = pd.Series([1., 2., 3., 4., 5., 6.])
+        res1 = unordered1.rank()
+        assert_series_equal(res1, exp_unordered1)
+
         # Test na_option for rank data
         na_ser = pd.Series(
             ['first', 'second', 'third', 'fourth', 'fifth', 'sixth', np.NaN]