REF/POC: Share groupby/series algos (rank)

asv_bench/benchmarks/frame_methods.py

@@ -597,6 +597,19 @@ def time_frame_quantile(self, axis):
         self.df.quantile([0.1, 0.5], axis=axis)
 
 
+class Rank:
+    param_names = ["dtype"]
+    params = [
+        ["int", "uint", "float", "object"],
+    ]
+
+    def setup(self, dtype):
+        self.df = DataFrame(np.random.randn(10000, 10), columns=range(10), dtype=dtype)
+
+    def time_rank(self, dtype):
+        self.df.rank()
+
+
 class GetDtypeCounts:
     # 2807
     def setup(self):

asv_bench/benchmarks/groupby.py

@@ -29,7 +29,6 @@
         "skew",
         "cumprod",
         "cummax",
-        "rank",
         "pct_change",
         "min",
         "var",

asv_bench/benchmarks/series_methods.py

@@ -349,4 +349,18 @@ def time_func(self, func, N, dtype):
         self.func()
 
 
+class Rank:
+
+    param_names = ["dtype"]
+    params = [
+        ["int", "uint", "float", "object"],
+    ]
+
+    def setup(self, dtype):
+        self.s = Series(np.random.randint(0, 1000, size=100000), dtype=dtype)
+
+    def time_rank(self, dtype):
+        self.s.rank()
+
+
 from .pandas_vb_common import setup  # noqa: F401 isort:skip