PERF: improve performance of NDFrame.describe

asv_bench/benchmarks/frame_methods.py

@@ -512,3 +512,21 @@ def time_nlargest(self, keep):
 
     def time_nsmallest(self, keep):
         self.df.nsmallest(100, 'A', keep=keep)
+
+
+class Describe(object):
+
+    goal_time = 0.2
+
+    def setup(self):
+        self.df = DataFrame({
+            'a': np.random.randint(0, 100, int(1e6)),
+            'b': np.random.randint(0, 100, int(1e6)),
+            'c': np.random.randint(0, 100, int(1e6))
+        })
+
+    def time_series_describe(self):
+        self.df['a'].describe()
+
+    def time_dataframe_describe(self):
+        self.df.describe()

doc/source/whatsnew/v0.24.0.txt

@@ -63,8 +63,7 @@ Removal of prior version deprecations/changes
 Performance Improvements
 ~~~~~~~~~~~~~~~~~~~~~~~~
 
--
--
+- Improved performance of :func:`Series.describe` in case of numeric dtpyes (:issue:`21274`)
 -
 
 .. _whatsnew_0240.docs:

pandas/core/generic.py

@@ -8519,7 +8519,7 @@ def describe_numeric_1d(series):
             stat_index = (['count', 'mean', 'std', 'min'] +
                           formatted_percentiles + ['max'])
             d = ([series.count(), series.mean(), series.std(), series.min()] +
-                 [series.quantile(x) for x in percentiles] + [series.max()])
+                 series.quantile(percentiles).tolist() + [series.max()])
             return pd.Series(d, index=stat_index, name=series.name)
 
         def describe_categorical_1d(data):