diff --git a/pandas/core/groupby/base.py b/pandas/core/groupby/base.py
index a148f7e0cab87..ebba4a0a9395d 100644
--- a/pandas/core/groupby/base.py
+++ b/pandas/core/groupby/base.py
@@ -69,35 +69,22 @@ def _gotitem(self, key, ndim, subset=None):
 
 # special case to prevent duplicate plots when catching exceptions when
 # forwarding methods from NDFrames
-plotting_methods = frozenset(['plot', 'boxplot', 'hist'])
+plotting_methods = frozenset(['plot', 'hist'])
 
 common_apply_whitelist = frozenset([
-    'last', 'first',
-    'head', 'tail', 'median',
-    'mean', 'sum', 'min', 'max',
-    'cumcount', 'ngroup',
-    'resample',
-    'rank', 'quantile',
-    'fillna',
-    'mad',
-    'any', 'all',
-    'take',
-    'idxmax', 'idxmin',
-    'shift', 'tshift',
-    'ffill', 'bfill',
-    'pct_change', 'skew',
-    'corr', 'cov', 'diff',
+    'quantile', 'fillna', 'mad', 'take',
+    'idxmax', 'idxmin', 'tshift',
+    'skew', 'corr', 'cov', 'diff'
 ]) | plotting_methods
 
 series_apply_whitelist = ((common_apply_whitelist |
                            {'nlargest', 'nsmallest',
                             'is_monotonic_increasing',
-                            'is_monotonic_decreasing'}) -
-                          {'boxplot'}) | frozenset(['dtype', 'unique'])
+                            'is_monotonic_decreasing'})
+                          ) | frozenset(['dtype', 'unique'])
 
 dataframe_apply_whitelist = ((common_apply_whitelist |
-                              frozenset(['dtypes', 'corrwith'])) -
-                             {'boxplot'})
+                              frozenset(['dtypes', 'corrwith'])))
 
 cython_transforms = frozenset(['cumprod', 'cumsum', 'shift',
                                'cummin', 'cummax'])
diff --git a/pandas/tests/groupby/test_whitelist.py b/pandas/tests/groupby/test_whitelist.py
index e0f1730d6909f..a451acebcdba4 100644
--- a/pandas/tests/groupby/test_whitelist.py
+++ b/pandas/tests/groupby/test_whitelist.py
@@ -14,35 +14,16 @@
 AGG_FUNCTIONS_WITH_SKIPNA = ['skew', 'mad']
 
 df_whitelist = [
-    'last',
-    'first',
-    'mean',
-    'sum',
-    'min',
-    'max',
-    'head',
-    'tail',
-    'cumcount',
-    'ngroup',
-    'resample',
-    'rank',
     'quantile',
     'fillna',
     'mad',
-    'any',
-    'all',
     'take',
     'idxmax',
     'idxmin',
-    'shift',
     'tshift',
-    'ffill',
-    'bfill',
-    'pct_change',
     'skew',
     'plot',
     'hist',
-    'median',
     'dtypes',
     'corrwith',
     'corr',
@@ -57,35 +38,16 @@ def df_whitelist_fixture(request):
 
 
 s_whitelist = [
-    'last',
-    'first',
-    'mean',
-    'sum',
-    'min',
-    'max',
-    'head',
-    'tail',
-    'cumcount',
-    'ngroup',
-    'resample',
-    'rank',
     'quantile',
     'fillna',
     'mad',
-    'any',
-    'all',
     'take',
     'idxmax',
     'idxmin',
-    'shift',
     'tshift',
-    'ffill',
-    'bfill',
-    'pct_change',
     'skew',
     'plot',
     'hist',
-    'median',
     'dtype',
     'corr',
     'cov',
@@ -150,17 +112,8 @@ def test_groupby_whitelist(df_letters, whitelist):
 def check_whitelist(obj, df, m):
     # check the obj for a particular whitelist m
 
-    # these are aliases so ok to have the alias __name__
-    alias = {'bfill': 'backfill',
-             'ffill': 'pad',
-             'boxplot': None}
-
     gb = obj.groupby(df.letters)
 
-    m = alias.get(m, m)
-    if m is None:
-        return
-
     f = getattr(type(gb), m)
 
     # name