diff --git a/.travis.yml b/.travis.yml
index bd5cac8955c8d..4cbe7f86bd2fa 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -73,6 +73,10 @@ matrix:
       env:
         - JOB="3.6_NUMPY_DEV" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate"
     # In allow_failures
+    - dist: trusty
+      env:
+        - JOB="3.6_ASV" ASV=true
+    # In allow_failures
     - dist: trusty
       env:
         - JOB="3.6_DOC" DOC=true
@@ -93,6 +97,9 @@ matrix:
       - dist: trusty
         env:
           - JOB="3.6_NUMPY_DEV" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate"
+      - dist: trusty
+        env:
+          - JOB="3.6_ASV" ASV=true
       - dist: trusty
         env:
           - JOB="3.6_DOC" DOC=true
@@ -128,6 +135,7 @@ script:
   - ci/script_single.sh
   - ci/script_multi.sh
   - ci/lint.sh
+  - ci/asv.sh
   - echo "checking imports"
   - source activate pandas && python ci/check_imports.py
   - echo "script done"
diff --git a/asv_bench/benchmarks/algorithms.py b/asv_bench/benchmarks/algorithms.py
index 45d62163ae80b..cccd38ef11251 100644
--- a/asv_bench/benchmarks/algorithms.py
+++ b/asv_bench/benchmarks/algorithms.py
@@ -1,3 +1,4 @@
+import warnings
 from importlib import import_module
 
 import numpy as np
@@ -83,7 +84,8 @@ def setup(self):
         self.all = self.uniques.repeat(10)
 
     def time_match_string(self):
-        pd.match(self.all, self.uniques)
+        with warnings.catch_warnings(record=True):
+            pd.match(self.all, self.uniques)
 
 
 class Hashing(object):
diff --git a/asv_bench/benchmarks/categoricals.py b/asv_bench/benchmarks/categoricals.py
index 1613ca1b97f4b..7743921003353 100644
--- a/asv_bench/benchmarks/categoricals.py
+++ b/asv_bench/benchmarks/categoricals.py
@@ -1,3 +1,5 @@
+import warnings
+
 import numpy as np
 import pandas as pd
 import pandas.util.testing as tm
@@ -119,11 +121,15 @@ def setup(self):
 
         self.s_str = pd.Series(tm.makeCategoricalIndex(N, ncats)).astype(str)
         self.s_str_cat = self.s_str.astype('category')
-        self.s_str_cat_ordered = self.s_str.astype('category', ordered=True)
+        with warnings.catch_warnings(record=True):
+            self.s_str_cat_ordered = self.s_str.astype('category',
+                                                       ordered=True)
 
         self.s_int = pd.Series(np.random.randint(0, ncats, size=N))
         self.s_int_cat = self.s_int.astype('category')
-        self.s_int_cat_ordered = self.s_int.astype('category', ordered=True)
+        with warnings.catch_warnings(record=True):
+            self.s_int_cat_ordered = self.s_int.astype('category',
+                                                       ordered=True)
 
     def time_rank_string(self):
         self.s_str.rank()
diff --git a/asv_bench/benchmarks/frame_methods.py b/asv_bench/benchmarks/frame_methods.py
index 4cecf12a27042..4ff71c706cd34 100644
--- a/asv_bench/benchmarks/frame_methods.py
+++ b/asv_bench/benchmarks/frame_methods.py
@@ -1,4 +1,6 @@
 import string
+import warnings
+
 import numpy as np
 import pandas.util.testing as tm
 from pandas import (DataFrame, Series, MultiIndex, date_range, period_range,
@@ -15,7 +17,8 @@ def setup(self):
         self.df = DataFrame(np.random.randn(10000, 25))
         self.df['foo'] = 'bar'
         self.df['bar'] = 'baz'
-        self.df = self.df.consolidate()
+        with warnings.catch_warnings(record=True):
+            self.df = self.df.consolidate()
 
     def time_frame_get_numeric_data(self):
         self.df._get_numeric_data()
@@ -141,8 +144,8 @@ class Repr(object):
     def setup(self):
         nrows = 10000
         data = np.random.randn(nrows, 10)
-        idx = MultiIndex.from_arrays(np.tile(np.random.randn(3, nrows / 100),
-                                             100))
+        arrays = np.tile(np.random.randn(3, int(nrows / 100)), 100)
+        idx = MultiIndex.from_arrays(arrays)
         self.df3 = DataFrame(data, index=idx)
         self.df4 = DataFrame(data, index=np.random.randn(nrows))
         self.df_tall = DataFrame(np.random.randn(nrows, 10))
diff --git a/asv_bench/benchmarks/gil.py b/asv_bench/benchmarks/gil.py
index 7d63d78084270..21c1ccf46e1c4 100644
--- a/asv_bench/benchmarks/gil.py
+++ b/asv_bench/benchmarks/gil.py
@@ -1,9 +1,13 @@
 import numpy as np
 import pandas.util.testing as tm
-from pandas import (DataFrame, Series, rolling_median, rolling_mean,
-                    rolling_min, rolling_max, rolling_var, rolling_skew,
-                    rolling_kurt, rolling_std, read_csv, factorize, date_range)
+from pandas import DataFrame, Series, read_csv, factorize, date_range
 from pandas.core.algorithms import take_1d
+try:
+    from pandas import (rolling_median, rolling_mean, rolling_min, rolling_max,
+                        rolling_var, rolling_skew, rolling_kurt, rolling_std)
+    have_rolling_methods = True
+except ImportError:
+    have_rolling_methods = False
 try:
     from pandas._libs import algos
 except ImportError:
@@ -171,8 +175,7 @@ def run(period):
 class ParallelRolling(object):
 
     goal_time = 0.2
-    params = ['rolling_median', 'rolling_mean', 'rolling_min', 'rolling_max',
-              'rolling_var', 'rolling_skew', 'rolling_kurt', 'rolling_std']
+    params = ['median', 'mean', 'min', 'max', 'var', 'skew', 'kurt', 'std']
     param_names = ['method']
 
     def setup(self, method):
@@ -181,34 +184,28 @@ def setup(self, method):
         win = 100
         arr = np.random.rand(100000)
         if hasattr(DataFrame, 'rolling'):
-            rolling = {'rolling_median': 'median',
-                       'rolling_mean': 'mean',
-                       'rolling_min': 'min',
-                       'rolling_max': 'max',
-                       'rolling_var': 'var',
-                       'rolling_skew': 'skew',
-                       'rolling_kurt': 'kurt',
-                       'rolling_std': 'std'}
             df = DataFrame(arr).rolling(win)
 
             @test_parallel(num_threads=2)
             def parallel_rolling():
-                getattr(df, rolling[method])()
+                getattr(df, method)()
             self.parallel_rolling = parallel_rolling
-        else:
-            rolling = {'rolling_median': rolling_median,
-                       'rolling_mean': rolling_mean,
-                       'rolling_min': rolling_min,
-                       'rolling_max': rolling_max,
-                       'rolling_var': rolling_var,
-                       'rolling_skew': rolling_skew,
-                       'rolling_kurt': rolling_kurt,
-                       'rolling_std': rolling_std}
+        elif have_rolling_methods:
+            rolling = {'median': rolling_median,
+                       'mean': rolling_mean,
+                       'min': rolling_min,
+                       'max': rolling_max,
+                       'var': rolling_var,
+                       'skew': rolling_skew,
+                       'kurt': rolling_kurt,
+                       'std': rolling_std}
 
             @test_parallel(num_threads=2)
             def parallel_rolling():
                 rolling[method](arr, win)
             self.parallel_rolling = parallel_rolling
+        else:
+            raise NotImplementedError
 
     def time_rolling(self, method):
         self.parallel_rolling()
diff --git a/asv_bench/benchmarks/groupby.py b/asv_bench/benchmarks/groupby.py
index 4dfd215e6dc3a..8aa67d8bc6a6a 100644
--- a/asv_bench/benchmarks/groupby.py
+++ b/asv_bench/benchmarks/groupby.py
@@ -1,3 +1,4 @@
+import warnings
 from string import ascii_letters
 from itertools import product
 from functools import partial
@@ -340,7 +341,8 @@ def time_dt_size(self):
         self.df.groupby(['dates']).size()
 
     def time_dt_timegrouper_size(self):
-        self.df.groupby(TimeGrouper(key='dates', freq='M')).size()
+        with warnings.catch_warnings(record=True):
+            self.df.groupby(TimeGrouper(key='dates', freq='M')).size()
 
     def time_category_size(self):
         self.draws.groupby(self.cats).size()
@@ -467,7 +469,7 @@ class SumMultiLevel(object):
 
     def setup(self):
         N = 50
-        self.df = DataFrame({'A': range(N) * 2,
+        self.df = DataFrame({'A': list(range(N)) * 2,
                              'B': range(N * 2),
                              'C': 1}).set_index(['A', 'B'])
 
diff --git a/asv_bench/benchmarks/indexing.py b/asv_bench/benchmarks/indexing.py
index b35f00db2b054..77e013e1e4fb0 100644
--- a/asv_bench/benchmarks/indexing.py
+++ b/asv_bench/benchmarks/indexing.py
@@ -1,3 +1,5 @@
+import warnings
+
 import numpy as np
 import pandas.util.testing as tm
 from pandas import (Series, DataFrame, MultiIndex, Int64Index, Float64Index,
@@ -91,7 +93,8 @@ def time_getitem_pos_slice(self, index):
         self.s[:80000]
 
     def time_get_value(self, index):
-        self.s.get_value(self.lbl)
+        with warnings.catch_warnings(record=True):
+            self.s.get_value(self.lbl)
 
     def time_getitem_scalar(self, index):
         self.s[self.lbl]
@@ -112,7 +115,8 @@ def setup(self):
         self.bool_obj_indexer = self.bool_indexer.astype(object)
 
     def time_get_value(self):
-        self.df.get_value(self.idx_scalar, self.col_scalar)
+        with warnings.catch_warnings(record=True):
+            self.df.get_value(self.idx_scalar, self.col_scalar)
 
     def time_ix(self):
         self.df.ix[self.idx_scalar, self.col_scalar]
@@ -231,11 +235,13 @@ class PanelIndexing(object):
     goal_time = 0.2
 
     def setup(self):
-        self.p = Panel(np.random.randn(100, 100, 100))
-        self.inds = range(0, 100, 10)
+        with warnings.catch_warnings(record=True):
+            self.p = Panel(np.random.randn(100, 100, 100))
+            self.inds = range(0, 100, 10)
 
     def time_subset(self):
-        self.p.ix[(self.inds, self.inds, self.inds)]
+        with warnings.catch_warnings(record=True):
+            self.p.ix[(self.inds, self.inds, self.inds)]
 
 
 class MethodLookup(object):
@@ -295,7 +301,8 @@ def setup(self):
     def time_insert(self):
         np.random.seed(1234)
         for i in range(100):
-            self.df.insert(0, i, np.random.randn(self.N))
+            self.df.insert(0, i, np.random.randn(self.N),
+                           allow_duplicates=True)
 
     def time_assign_with_setitem(self):
         np.random.seed(1234)
diff --git a/asv_bench/benchmarks/io/hdf.py b/asv_bench/benchmarks/io/hdf.py
index 5c0e9586c1cb5..4b6e1d69af92d 100644
--- a/asv_bench/benchmarks/io/hdf.py
+++ b/asv_bench/benchmarks/io/hdf.py
@@ -1,3 +1,5 @@
+import warnings
+
 import numpy as np
 from pandas import DataFrame, Panel, date_range, HDFStore, read_hdf
 import pandas.util.testing as tm
@@ -105,22 +107,25 @@ class HDFStorePanel(BaseIO):
 
     def setup(self):
         self.fname = '__test__.h5'
-        self.p = Panel(np.random.randn(20, 1000, 25),
-                       items=['Item%03d' % i for i in range(20)],
-                       major_axis=date_range('1/1/2000', periods=1000),
-                       minor_axis=['E%03d' % i for i in range(25)])
-        self.store = HDFStore(self.fname)
-        self.store.append('p1', self.p)
+        with warnings.catch_warnings(record=True):
+            self.p = Panel(np.random.randn(20, 1000, 25),
+                           items=['Item%03d' % i for i in range(20)],
+                           major_axis=date_range('1/1/2000', periods=1000),
+                           minor_axis=['E%03d' % i for i in range(25)])
+            self.store = HDFStore(self.fname)
+            self.store.append('p1', self.p)
 
     def teardown(self):
         self.store.close()
         self.remove(self.fname)
 
     def time_read_store_table_panel(self):
-        self.store.select('p1')
+        with warnings.catch_warnings(record=True):
+            self.store.select('p1')
 
     def time_write_store_table_panel(self):
-        self.store.append('p2', self.p)
+        with warnings.catch_warnings(record=True):
+            self.store.append('p2', self.p)
 
 
 class HDF(BaseIO):
diff --git a/asv_bench/benchmarks/join_merge.py b/asv_bench/benchmarks/join_merge.py
index 5b40a29d54683..de0a3b33da147 100644
--- a/asv_bench/benchmarks/join_merge.py
+++ b/asv_bench/benchmarks/join_merge.py
@@ -1,3 +1,4 @@
+import warnings
 import string
 
 import numpy as np
@@ -26,7 +27,8 @@ def setup(self):
         self.mdf1['obj2'] = 'bar'
         self.mdf1['int1'] = 5
         try:
-            self.mdf1.consolidate(inplace=True)
+            with warnings.catch_warnings(record=True):
+                self.mdf1.consolidate(inplace=True)
         except:
             pass
         self.mdf2 = self.mdf1.copy()
@@ -75,16 +77,23 @@ class ConcatPanels(object):
     param_names = ['axis', 'ignore_index']
 
     def setup(self, axis, ignore_index):
-        panel_c = Panel(np.zeros((10000, 200, 2), dtype=np.float32, order='C'))
-        self.panels_c = [panel_c] * 20
-        panel_f = Panel(np.zeros((10000, 200, 2), dtype=np.float32, order='F'))
-        self.panels_f = [panel_f] * 20
+        with warnings.catch_warnings(record=True):
+            panel_c = Panel(np.zeros((10000, 200, 2),
+                                     dtype=np.float32,
+                                     order='C'))
+            self.panels_c = [panel_c] * 20
+            panel_f = Panel(np.zeros((10000, 200, 2),
+                            dtype=np.float32,
+                            order='F'))
+            self.panels_f = [panel_f] * 20
 
     def time_c_ordered(self, axis, ignore_index):
-        concat(self.panels_c, axis=axis, ignore_index=ignore_index)
+        with warnings.catch_warnings(record=True):
+            concat(self.panels_c, axis=axis, ignore_index=ignore_index)
 
     def time_f_ordered(self, axis, ignore_index):
-        concat(self.panels_f, axis=axis, ignore_index=ignore_index)
+        with warnings.catch_warnings(record=True):
+            concat(self.panels_f, axis=axis, ignore_index=ignore_index)
 
 
 class ConcatDataFrames(object):
diff --git a/asv_bench/benchmarks/offset.py b/asv_bench/benchmarks/offset.py
index 034e861e7fc01..e161b887ee86f 100644
--- a/asv_bench/benchmarks/offset.py
+++ b/asv_bench/benchmarks/offset.py
@@ -1,4 +1,5 @@
 # -*- coding: utf-8 -*-
+import warnings
 from datetime import datetime
 
 import numpy as np
@@ -76,7 +77,8 @@ def setup(self, offset):
         self.data = pd.Series(rng)
 
     def time_add_offset(self, offset):
-        self.data + offset
+        with warnings.catch_warnings(record=True):
+            self.data + offset
 
 
 class OffsetDatetimeIndexArithmetic(object):
@@ -90,7 +92,8 @@ def setup(self, offset):
         self.data = pd.date_range(start='1/1/2000', periods=N, freq='T')
 
     def time_add_offset(self, offset):
-        self.data + offset
+        with warnings.catch_warnings(record=True):
+            self.data + offset
 
 
 class OffestDatetimeArithmetic(object):
diff --git a/asv_bench/benchmarks/panel_ctor.py b/asv_bench/benchmarks/panel_ctor.py
index 456fe959c5aa3..ce946c76ed199 100644
--- a/asv_bench/benchmarks/panel_ctor.py
+++ b/asv_bench/benchmarks/panel_ctor.py
@@ -1,3 +1,4 @@
+import warnings
 from datetime import datetime, timedelta
 
 from pandas import DataFrame, DatetimeIndex, date_range
@@ -19,7 +20,8 @@ def setup(self):
             self.data_frames[x] = df
 
     def time_from_dict(self):
-        Panel.from_dict(self.data_frames)
+        with warnings.catch_warnings(record=True):
+            Panel.from_dict(self.data_frames)
 
 
 class SameIndexes(object):
@@ -34,7 +36,8 @@ def setup(self):
         self.data_frames = dict(enumerate([df] * 100))
 
     def time_from_dict(self):
-        Panel.from_dict(self.data_frames)
+        with warnings.catch_warnings(record=True):
+            Panel.from_dict(self.data_frames)
 
 
 class TwoIndexes(object):
@@ -53,4 +56,5 @@ def setup(self):
         self.data_frames = dict(enumerate(dfs))
 
     def time_from_dict(self):
-        Panel.from_dict(self.data_frames)
+        with warnings.catch_warnings(record=True):
+            Panel.from_dict(self.data_frames)
diff --git a/asv_bench/benchmarks/panel_methods.py b/asv_bench/benchmarks/panel_methods.py
index 9ee1949b311db..a5b1a92e9cf67 100644
--- a/asv_bench/benchmarks/panel_methods.py
+++ b/asv_bench/benchmarks/panel_methods.py
@@ -1,3 +1,5 @@
+import warnings
+
 import numpy as np
 
 from .pandas_vb_common import Panel, setup  # noqa
@@ -10,10 +12,13 @@ class PanelMethods(object):
     param_names = ['axis']
 
     def setup(self, axis):
-        self.panel = Panel(np.random.randn(100, 1000, 100))
+        with warnings.catch_warnings(record=True):
+            self.panel = Panel(np.random.randn(100, 1000, 100))
 
     def time_pct_change(self, axis):
-        self.panel.pct_change(1, axis=axis)
+        with warnings.catch_warnings(record=True):
+            self.panel.pct_change(1, axis=axis)
 
     def time_shift(self, axis):
-        self.panel.shift(1, axis=axis)
+        with warnings.catch_warnings(record=True):
+            self.panel.shift(1, axis=axis)
diff --git a/asv_bench/benchmarks/reindex.py b/asv_bench/benchmarks/reindex.py
index 69a1a604b1ccc..413427a16f40b 100644
--- a/asv_bench/benchmarks/reindex.py
+++ b/asv_bench/benchmarks/reindex.py
@@ -167,10 +167,6 @@ def setup(self):
         col_array2 = col_array.copy()
         col_array2[:, :10000] = np.nan
         self.col_array_list = list(col_array)
-        self.col_array_list2 = list(col_array2)
 
     def time_lib_fast_zip(self):
         lib.fast_zip(self.col_array_list)
-
-    def time_lib_fast_zip_fillna(self):
-        lib.fast_zip_fillna(self.col_array_list2)
diff --git a/asv_bench/benchmarks/reshape.py b/asv_bench/benchmarks/reshape.py
index bd3b580d9d130..9044b080c45f9 100644
--- a/asv_bench/benchmarks/reshape.py
+++ b/asv_bench/benchmarks/reshape.py
@@ -104,9 +104,9 @@ def setup(self):
         self.letters = list('ABCD')
         yrvars = [l + str(num)
                   for l, num in product(self.letters, range(1, nyrs + 1))]
-
+        columns = [str(i) for i in range(nidvars)] + yrvars
         self.df = DataFrame(np.random.randn(N, nidvars + len(yrvars)),
-                            columns=list(range(nidvars)) + yrvars)
+                            columns=columns)
         self.df['id'] = self.df.index
 
     def time_wide_to_long_big(self):
diff --git a/asv_bench/benchmarks/strings.py b/asv_bench/benchmarks/strings.py
index 4435327e1eb38..b203c8b0fa5c9 100644
--- a/asv_bench/benchmarks/strings.py
+++ b/asv_bench/benchmarks/strings.py
@@ -1,3 +1,5 @@
+import warnings
+
 import numpy as np
 from pandas import Series
 import pandas.util.testing as tm
@@ -23,7 +25,8 @@ def time_endswith(self):
         self.s.str.endswith('A')
 
     def time_extract(self):
-        self.s.str.extract('(\\w*)A(\\w*)')
+        with warnings.catch_warnings(record=True):
+            self.s.str.extract('(\\w*)A(\\w*)')
 
     def time_findall(self):
         self.s.str.findall('[A-Z]+')
diff --git a/asv_bench/benchmarks/timeseries.py b/asv_bench/benchmarks/timeseries.py
index ea2f077f980d0..e1a6bc7a68e9d 100644
--- a/asv_bench/benchmarks/timeseries.py
+++ b/asv_bench/benchmarks/timeseries.py
@@ -1,3 +1,4 @@
+import warnings
 from datetime import timedelta
 
 import numpy as np
@@ -74,7 +75,8 @@ def setup(self):
                                                   freq='S'))
 
     def time_infer_dst(self):
-        self.index.tz_localize('US/Eastern', infer_dst=True)
+        with warnings.catch_warnings(record=True):
+            self.index.tz_localize('US/Eastern', infer_dst=True)
 
 
 class ResetIndex(object):
@@ -365,7 +367,7 @@ class ToDatetimeCache(object):
 
     def setup(self, cache):
         N = 10000
-        self.unique_numeric_seconds = range(N)
+        self.unique_numeric_seconds = list(range(N))
         self.dup_numeric_seconds = [1000] * N
         self.dup_string_dates = ['2000-02-11'] * N
         self.dup_string_with_tz = ['2000-02-11 15:00:00-0800'] * N
diff --git a/ci/asv.sh b/ci/asv.sh
new file mode 100755
index 0000000000000..1e9a8d6380eb5
--- /dev/null
+++ b/ci/asv.sh
@@ -0,0 +1,35 @@
+#!/bin/bash
+
+echo "inside $0"
+
+source activate pandas
+
+RET=0
+
+if [ "$ASV" ]; then
+    echo "Check for failed asv benchmarks"
+
+    cd asv_bench
+
+    asv machine --yes
+
+    time asv dev | tee failed_asv.txt
+
+    echo "The following asvs benchmarks (if any) failed."
+
+    cat failed_asv.txt | grep "failed" failed_asv.txt
+
+    if [ $? = "0" ]; then
+        RET=1
+    fi
+
+    echo "DONE displaying failed asvs benchmarks."
+
+    rm failed_asv.txt
+
+    echo "Check for failed asv benchmarks DONE"
+else
+    echo "NOT checking for failed asv benchmarks"
+fi
+
+exit $RET
diff --git a/ci/requirements-3.6_ASV.build b/ci/requirements-3.6_ASV.build
new file mode 100644
index 0000000000000..bc72eed2a0d4e
--- /dev/null
+++ b/ci/requirements-3.6_ASV.build
@@ -0,0 +1,5 @@
+python=3.6*
+python-dateutil
+pytz
+numpy=1.13*
+cython
diff --git a/ci/requirements-3.6_ASV.run b/ci/requirements-3.6_ASV.run
new file mode 100644
index 0000000000000..6c45e3371e9cf
--- /dev/null
+++ b/ci/requirements-3.6_ASV.run
@@ -0,0 +1,25 @@
+ipython
+ipykernel
+ipywidgets
+sphinx=1.5*
+nbconvert
+nbformat
+notebook
+matplotlib
+seaborn
+scipy
+lxml
+beautifulsoup4
+html5lib
+pytables
+python-snappy
+openpyxl
+xlrd
+xlwt
+xlsxwriter
+sqlalchemy
+numexpr
+bottleneck
+statsmodels
+xarray
+pyqt
diff --git a/ci/requirements-3.6_ASV.sh b/ci/requirements-3.6_ASV.sh
new file mode 100755
index 0000000000000..8a46f85dbb6bc
--- /dev/null
+++ b/ci/requirements-3.6_ASV.sh
@@ -0,0 +1,7 @@
+#!/bin/bash
+
+source activate pandas
+
+echo "[install ASV_BUILD deps]"
+
+pip install git+https://github.com/spacetelescope/asv
diff --git a/ci/script_multi.sh b/ci/script_multi.sh
index c1fa756ece965..766e51625fbe6 100755
--- a/ci/script_multi.sh
+++ b/ci/script_multi.sh
@@ -37,6 +37,9 @@ if [ "$PIP_BUILD_TEST" ] || [ "$CONDA_BUILD_TEST" ]; then
 elif [ "$DOC" ]; then
     echo "We are not running pytest as this is a doc-build"
 
+elif [ "$ASV" ]; then
+    echo "We are not running pytest as this is an asv-build"
+
 elif [ "$COVERAGE" ]; then
     echo pytest -s -n 2 -m "not single" --cov=pandas --cov-report xml:/tmp/cov-multiple.xml --junitxml=/tmp/multiple.xml --strict $TEST_ARGS pandas
     pytest -s -n 2 -m "not single" --cov=pandas --cov-report xml:/tmp/cov-multiple.xml --junitxml=/tmp/multiple.xml --strict $TEST_ARGS pandas
diff --git a/ci/script_single.sh b/ci/script_single.sh
index 005c648ee025f..153847ab2e8c9 100755
--- a/ci/script_single.sh
+++ b/ci/script_single.sh
@@ -22,6 +22,9 @@ if [ "$PIP_BUILD_TEST" ] || [ "$CONDA_BUILD_TEST" ]; then
 elif [ "$DOC" ]; then
     echo "We are not running pytest as this is a doc-build"
 
+elif [ "$ASV" ]; then
+    echo "We are not running pytest as this is an asv-build"
+
 elif [ "$COVERAGE" ]; then
     echo pytest -s -m "single" --strict --cov=pandas --cov-report xml:/tmp/cov-single.xml --junitxml=/tmp/single.xml $TEST_ARGS pandas
     pytest -s -m "single" --strict --cov=pandas --cov-report xml:/tmp/cov-single.xml --junitxml=/tmp/single.xml $TEST_ARGS pandas