TST GH#40498 Add benchmark tests for fillna using value.

Author: Mike Phung

asv_bench/benchmarks/frame_methods.py

@@ -374,7 +374,7 @@ class Fillna:
 
     params = (
         [True, False],
-        ["pad", "bfill"],
+        [None, "pad", "bfill"],
         [
             "float64",
             "float32",
@@ -400,15 +400,19 @@ def setup(self, inplace, method, dtype):
             }
             self.df = DataFrame({f"col_{i}": data[dtype] for i in range(M)})
             self.df[::2] = None
+            self.value = (
+                dict(zip(self.df.columns, data[dtype][:M])) if not method else None
+            )
         else:
-            values = np.random.randn(N, M)
-            values[::2] = np.nan
+            data = np.random.randn(N, M)
             if dtype == "Int64":
-                values = values.round()
-            self.df = DataFrame(values, dtype=dtype)
+                data = data.round()
+            self.df = DataFrame({f"col_{i}": data[i] for i in range(M)})
+            self.df[::2] = None
+            self.value = dict(zip(self.df.columns, data[M])) if not method else None
 
     def time_frame_fillna(self, inplace, method, dtype):
-        self.df.fillna(inplace=inplace, method=method)
+        self.df.fillna(value=self.value, inplace=inplace, method=method)
 
 
 class Dropna:

asv_bench/benchmarks/series_methods.py

@@ -6,6 +6,7 @@
     NaT,
     Series,
     date_range,
+    timedelta_range,
 )
 
 from .pandas_vb_common import tm
@@ -42,6 +43,49 @@ def time_nsmallest(self, keep):
         self.s.nsmallest(3, keep=keep)
 
 
+class Fillna:
+
+    params = (
+        [True, False],
+        [None, "pad", "bfill"],
+        [
+            "float64",
+            "float32",
+            "object",
+            "Int64",
+            "Float64",
+            "datetime64[ns]",
+            "datetime64[ns, tz]",
+            "timedelta64[ns]",
+        ],
+    )
+    param_names = ["inplace", "method", "dtype"]
+
+    def setup(self, inplace, method, dtype):
+        N = 10000
+        if dtype in ("datetime64[ns]", "datetime64[ns, tz]", "timedelta64[ns]"):
+            data = {
+                "datetime64[ns]": date_range("2011-01-01", freq="H", periods=N),
+                "datetime64[ns, tz]": date_range(
+                    "2011-01-01", freq="H", periods=N, tz="Asia/Tokyo"
+                ),
+                "timedelta64[ns]": timedelta_range(start="1 day", periods=N, freq="1D"),
+            }
+            self.ser = Series(data[dtype])
+            self.ser[::2] = None
+            self.value = dict(zip(self.ser.index, data[dtype])) if not method else None
+        else:
+            data = np.random.randn(N)
+            if dtype == "Int64":
+                data = data.round()
+            self.ser = Series(data, dtype=dtype)
+            self.ser[::2] = None
+            self.value = dict(zip(self.ser.index, data)) if not method else None
+
+    def time_series_fillna(self, inplace, method, dtype):
+        self.ser.fillna(value=self.value, inplace=inplace, method=method)
+
+
 class Dropna:
 
     params = ["int", "datetime"]