removing kendall tests (#29401)

Author: Deepan Das

asv_bench/benchmarks/stat_ops.py

@@ -7,20 +7,14 @@
 
 class FrameOps:
 
-    params = [ops, ["float", "int"], [0, 1], [True, False]]
-    param_names = ["op", "dtype", "axis", "use_bottleneck"]
+    params = [ops, ["float", "int"], [0, 1]]
+    param_names = ["op", "dtype", "axis"]
 
-    def setup(self, op, dtype, axis, use_bottleneck):
+    def setup(self, op, dtype, axis):
         df = pd.DataFrame(np.random.randn(100000, 4)).astype(dtype)
-        try:
-            pd.options.compute.use_bottleneck = use_bottleneck
-        except TypeError:
-            from pandas.core import nanops
-
-            nanops._USE_BOTTLENECK = use_bottleneck
         self.df_func = getattr(df, op)
 
-    def time_op(self, op, dtype, axis, use_bottleneck):
+    def time_op(self, op, dtype, axis):
         self.df_func(axis=axis)
 
 
@@ -46,20 +40,14 @@ def time_op(self, level, op):
 
 class SeriesOps:
 
-    params = [ops, ["float", "int"], [True, False]]
-    param_names = ["op", "dtype", "use_bottleneck"]
+    params = [ops, ["float", "int"]]
+    param_names = ["op", "dtype"]
 
-    def setup(self, op, dtype, use_bottleneck):
+    def setup(self, op, dtype):
         s = pd.Series(np.random.randn(100000)).astype(dtype)
-        try:
-            pd.options.compute.use_bottleneck = use_bottleneck
-        except TypeError:
-            from pandas.core import nanops
-
-            nanops._USE_BOTTLENECK = use_bottleneck
         self.s_func = getattr(s, op)
 
-    def time_op(self, op, dtype, use_bottleneck):
+    def time_op(self, op, dtype):
         self.s_func()
 
 
@@ -101,61 +89,49 @@ def time_average_old(self, constructor, pct):
 
 class Correlation:
 
-    params = [["spearman", "kendall", "pearson"], [True, False]]
-    param_names = ["method", "use_bottleneck"]
+    params = [["spearman", "kendall", "pearson"]]
+    param_names = ["method"]
 
-    def setup(self, method, use_bottleneck):
-        try:
-            pd.options.compute.use_bottleneck = use_bottleneck
-        except TypeError:
-            from pandas.core import nanops
+    def setup(self, method):
+        self.df = pd.DataFrame(np.random.randn(500, 15))
+        self.df2 = pd.DataFrame(np.random.randn(500, 15))
+        self.df_wide = pd.DataFrame(np.random.randn(500, 100))
+        self.df_wide_nans = self.df_wide.where(np.random.random((500, 100)) < 0.9)
+        self.s = pd.Series(np.random.randn(500))
+        self.s2 = pd.Series(np.random.randn(500))
 
-            nanops._USE_BOTTLENECK = use_bottleneck
-        self.df = pd.DataFrame(np.random.randn(1000, 30))
-        self.df2 = pd.DataFrame(np.random.randn(1000, 30))
-        self.df_wide = pd.DataFrame(np.random.randn(1000, 200))
-        self.df_wide_nans = self.df_wide.where(np.random.random((1000, 200)) < 0.9)
-        self.s = pd.Series(np.random.randn(1000))
-        self.s2 = pd.Series(np.random.randn(1000))
-
-    def time_corr(self, method, use_bottleneck):
+    def time_corr(self, method):
         self.df.corr(method=method)
 
-    def time_corr_wide(self, method, use_bottleneck):
+    def time_corr_wide(self, method):
         self.df_wide.corr(method=method)
 
-    def time_corr_wide_nans(self, method, use_bottleneck):
+    def time_corr_wide_nans(self, method):
         self.df_wide_nans.corr(method=method)
 
-    def peakmem_corr_wide(self, method, use_bottleneck):
+    def peakmem_corr_wide(self, method):
         self.df_wide.corr(method=method)
 
-    def time_corr_series(self, method, use_bottleneck):
+    def time_corr_series(self, method):
         self.s.corr(self.s2, method=method)
 
-    def time_corrwith_cols(self, method, use_bottleneck):
+    def time_corrwith_cols(self, method):
         self.df.corrwith(self.df2, method=method)
 
-    def time_corrwith_rows(self, method, use_bottleneck):
+    def time_corrwith_rows(self, method):
         self.df.corrwith(self.df2, axis=1, method=method)
 
 
 class Covariance:
 
-    params = [[True, False]]
-    param_names = ["use_bottleneck"]
-
-    def setup(self, use_bottleneck):
-        try:
-            pd.options.compute.use_bottleneck = use_bottleneck
-        except TypeError:
-            from pandas.core import nanops
+    params = []
+    param_names = []
 
-            nanops._USE_BOTTLENECK = use_bottleneck
+    def setup(self):
         self.s = pd.Series(np.random.randn(100000))
         self.s2 = pd.Series(np.random.randn(100000))
 
-    def time_cov_series(self, use_bottleneck):
+    def time_cov_series(self):
         self.s.cov(self.s2)