diff --git a/asv_bench/benchmarks/attrs_caching.py b/asv_bench/benchmarks/attrs_caching.py
index 9210f1f2878d40..70eb15392710cb 100644
--- a/asv_bench/benchmarks/attrs_caching.py
+++ b/asv_bench/benchmarks/attrs_caching.py
@@ -1,5 +1,5 @@
 from .pandas_vb_common import *
-from pandas.util.decorators import cache_readonly
+from pandas.util._decorators import cache_readonly
 
 
 class DataFrameAttributes(object):
diff --git a/doc/source/merging.rst b/doc/source/merging.rst
index fb020727d077ed..170dde87c83638 100644
--- a/doc/source/merging.rst
+++ b/doc/source/merging.rst
@@ -13,7 +13,7 @@
 
    import matplotlib.pyplot as plt
    plt.close('all')
-   import pandas.util.doctools as doctools
+   import pandas.util._doctools as doctools
    p = doctools.TablePlotter()
 
 
diff --git a/doc/source/whatsnew/v0.20.0.txt b/doc/source/whatsnew/v0.20.0.txt
index 230c7c0b90ac0f..69863d2227f2c9 100644
--- a/doc/source/whatsnew/v0.20.0.txt
+++ b/doc/source/whatsnew/v0.20.0.txt
@@ -1238,10 +1238,10 @@ If indicated, a deprecation warning will be issued if you reference theses modul
     "pandas.types", "pandas.core.dtypes", ""
     "pandas.io.sas.saslib", "pandas.io.sas.libsas", ""
     "pandas._join", "pandas._libs.join", ""
-    "pandas._hash", "pandas.util.libhashing", ""
+    "pandas._hash", "pandas._libs.hashing", ""
     "pandas._period", "pandas._libs.period", ""
     "pandas._sparse", "pandas.core.sparse.libsparse", ""
-    "pandas._testing", "pandas.util.libtesting", ""
+    "pandas._testing", "pandas.util._testing", ""
     "pandas._window", "pandas.core.libwindow", ""
 
 
@@ -1254,6 +1254,8 @@ these are now the public subpackages.
 
 - The function :func:`~pandas.api.types.union_categoricals` is now importable from ``pandas.api.types``, formerly from ``pandas.types.concat`` (:issue:`15998`)
 - The type import ``pandas.tslib.NaTType`` is deprecated and can be replaced by using ``type(pandas.NaT)`` (:issue:`16146`)
+- The public functions in ``pandas.util.hashing`` deprecated from that locations, but are now importable from ``pandas.util`` (:issue:`16223`)
+- The modules in ``pandas.util``: ``decorators``, ``print_versions``, ``doctools``, `validators``, ``depr_module`` are now private (:issue:`16223`)
 
 .. _whatsnew_0200.privacy.errors:
 
@@ -1278,7 +1280,7 @@ The following are now part of this API:
     'UnsupportedFunctionCall']
 
 
-.. _whatsnew_0200.privay.testing:
+.. _whatsnew_0200.privacy.testing:
 
 ``pandas.testing``
 ^^^^^^^^^^^^^^^^^^
@@ -1292,14 +1294,13 @@ The following testing functions are now part of this API:
 - :func:`testing.assert_index_equal`
 
 
-.. _whatsnew_0200.privay.plotting:
+.. _whatsnew_0200.privacy.plotting:
 
 ``pandas.plotting``
 ^^^^^^^^^^^^^^^^^^^
 
 A new public ``pandas.plotting`` module has been added that holds plotting functionality that was previously in either ``pandas.tools.plotting`` or in the top-level namespace. See the :ref:`deprecations sections <whatsnew_0200.privacy.deprecate_plotting>` for more details.
 
-
 .. _whatsnew_0200.privacy.development:
 
 Other Development Changes
diff --git a/pandas/__init__.py b/pandas/__init__.py
index 20c7e0d9d59939..48ac9d173559da 100644
--- a/pandas/__init__.py
+++ b/pandas/__init__.py
@@ -50,17 +50,17 @@
 import pandas.tools.plotting
 plot_params = pandas.plotting._style._Options(deprecated=True)
 # do not import deprecate to top namespace
-scatter_matrix = pandas.util.decorators.deprecate(
+scatter_matrix = pandas.util._decorators.deprecate(
     'pandas.scatter_matrix', pandas.plotting.scatter_matrix,
     'pandas.plotting.scatter_matrix')
 
-from pandas.util.print_versions import show_versions
+from pandas.util._print_versions import show_versions
 from pandas.io.api import *
 from pandas.util._tester import test
 import pandas.testing
 
 # extension module deprecations
-from pandas.util.depr_module import _DeprecatedModule
+from pandas.util._depr_module import _DeprecatedModule
 
 json = _DeprecatedModule(deprmod='pandas.json',
                          moved={'dumps': 'pandas.io.json.dumps',
diff --git a/pandas/util/hashing.pyx b/pandas/_libs/hashing.pyx
similarity index 100%
rename from pandas/util/hashing.pyx
rename to pandas/_libs/hashing.pyx
diff --git a/pandas/compat/numpy/function.py b/pandas/compat/numpy/function.py
index d707ac66c4eabd..a324bf94171ce5 100644
--- a/pandas/compat/numpy/function.py
+++ b/pandas/compat/numpy/function.py
@@ -19,8 +19,8 @@
 """
 
 from numpy import ndarray
-from pandas.util.validators import (validate_args, validate_kwargs,
-                                    validate_args_and_kwargs)
+from pandas.util._validators import (validate_args, validate_kwargs,
+                                     validate_args_and_kwargs)
 from pandas.errors import UnsupportedFunctionCall
 from pandas.core.dtypes.common import is_integer, is_bool
 from pandas.compat import OrderedDict
diff --git a/pandas/core/api.py b/pandas/core/api.py
index 3e84720c32a1c9..265fb4004d9973 100644
--- a/pandas/core/api.py
+++ b/pandas/core/api.py
@@ -35,7 +35,7 @@
 from pandas.core.resample import TimeGrouper
 
 # see gh-14094.
-from pandas.util.depr_module import _DeprecatedModule
+from pandas.util._depr_module import _DeprecatedModule
 
 _removals = ['day', 'bday', 'businessDay', 'cday', 'customBusinessDay',
              'customBusinessMonthEnd', 'customBusinessMonthBegin',
diff --git a/pandas/core/base.py b/pandas/core/base.py
index fd0846b0ad33c8..a3ef24c80f8839 100644
--- a/pandas/core/base.py
+++ b/pandas/core/base.py
@@ -9,14 +9,14 @@
 from pandas.core.dtypes.missing import isnull
 from pandas.core.dtypes.generic import ABCDataFrame, ABCSeries, ABCIndexClass
 from pandas.core.dtypes.common import is_object_dtype, is_list_like, is_scalar
-from pandas.util.validators import validate_bool_kwarg
+from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core import common as com
 import pandas.core.nanops as nanops
 import pandas._libs.lib as lib
 from pandas.compat.numpy import function as nv
-from pandas.util.decorators import (Appender, cache_readonly,
-                                    deprecate_kwarg, Substitution)
+from pandas.util._decorators import (Appender, cache_readonly,
+                                     deprecate_kwarg, Substitution)
 from pandas.core.common import AbstractMethodError
 
 _shared_docs = dict()
diff --git a/pandas/core/categorical.py b/pandas/core/categorical.py
index a3667e9322959e..7eb86232cbb073 100644
--- a/pandas/core/categorical.py
+++ b/pandas/core/categorical.py
@@ -34,11 +34,11 @@
 import pandas.core.common as com
 from pandas.core.missing import interpolate_2d
 from pandas.compat.numpy import function as nv
-from pandas.util.decorators import (Appender, cache_readonly,
-                                    deprecate_kwarg, Substitution)
+from pandas.util._decorators import (Appender, cache_readonly,
+                                     deprecate_kwarg, Substitution)
 
-from pandas.util.terminal import get_terminal_size
-from pandas.util.validators import validate_bool_kwarg
+from pandas.io.formats.terminal import get_terminal_size
+from pandas.util._validators import validate_bool_kwarg
 from pandas.core.config import get_option
 
 
diff --git a/pandas/core/computation/eval.py b/pandas/core/computation/eval.py
index 15e13025a7c53c..22e376306280ac 100644
--- a/pandas/core/computation/eval.py
+++ b/pandas/core/computation/eval.py
@@ -11,7 +11,7 @@
 from pandas.core.computation.scope import _ensure_scope
 from pandas.compat import string_types
 from pandas.core.computation.engines import _engines
-from pandas.util.validators import validate_bool_kwarg
+from pandas.util._validators import validate_bool_kwarg
 
 
 def _check_engine(engine):
diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 67966374fcf9ad..e6ea58e7e05be1 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -80,8 +80,8 @@
                            OrderedDict, raise_with_traceback)
 from pandas import compat
 from pandas.compat.numpy import function as nv
-from pandas.util.decorators import Appender, Substitution
-from pandas.util.validators import validate_bool_kwarg
+from pandas.util._decorators import Appender, Substitution
+from pandas.util._validators import validate_bool_kwarg
 
 from pandas.core.indexes.period import PeriodIndex
 from pandas.core.indexes.datetimes import DatetimeIndex
diff --git a/pandas/core/generic.py b/pandas/core/generic.py
index 2bc64795b5f208..27a489293db8ff 100644
--- a/pandas/core/generic.py
+++ b/pandas/core/generic.py
@@ -51,8 +51,8 @@
 from pandas.compat import (map, zip, lzip, lrange, string_types,
                            isidentifier, set_function_name)
 import pandas.core.nanops as nanops
-from pandas.util.decorators import Appender, Substitution, deprecate_kwarg
-from pandas.util.validators import validate_bool_kwarg
+from pandas.util._decorators import Appender, Substitution, deprecate_kwarg
+from pandas.util._validators import validate_bool_kwarg
 from pandas.core import config
 
 # goal is to be able to define the docs close to function, while still being
@@ -1382,7 +1382,7 @@ def to_clipboard(self, excel=None, sep=None, **kwargs):
           - Windows: none
           - OS X: none
         """
-        from pandas.io import clipboard
+        from pandas.io.clipboard import clipboard
         clipboard.to_clipboard(self, excel=excel, sep=sep, **kwargs)
 
     def to_xarray(self):
diff --git a/pandas/core/groupby.py b/pandas/core/groupby.py
index 479d2f7d26eb65..91b55c414b507d 100644
--- a/pandas/core/groupby.py
+++ b/pandas/core/groupby.py
@@ -54,10 +54,10 @@
 from pandas.core.sorting import (get_group_index_sorter, get_group_index,
                                  compress_group_index, get_flattened_iterator,
                                  decons_obs_group_ids, get_indexer_dict)
-from pandas.util.decorators import (cache_readonly, Substitution,
-                                    Appender, make_signature)
+from pandas.util._decorators import (cache_readonly, Substitution,
+                                     Appender, make_signature)
 from pandas.io.formats.printing import pprint_thing
-from pandas.util.validators import validate_kwargs
+from pandas.util._validators import validate_kwargs
 
 import pandas.core.algorithms as algorithms
 import pandas.core.common as com
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 4345c74664bf5c..82f3bf3b154629 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -41,8 +41,8 @@
 
 from pandas.core.base import PandasObject, IndexOpsMixin
 import pandas.core.base as base
-from pandas.util.decorators import (Appender, Substitution, cache_readonly,
-                                    deprecate, deprecate_kwarg)
+from pandas.util._decorators import (Appender, Substitution, cache_readonly,
+                                     deprecate, deprecate_kwarg)
 from pandas.core.indexes.frozen import FrozenList
 import pandas.core.common as com
 import pandas.core.dtypes.concat as _concat
diff --git a/pandas/core/indexes/category.py b/pandas/core/indexes/category.py
index 760db4ba206757..395513d7b9b810 100644
--- a/pandas/core/indexes/category.py
+++ b/pandas/core/indexes/category.py
@@ -16,7 +16,7 @@
 from pandas.core.algorithms import take_1d
 
 
-from pandas.util.decorators import Appender, cache_readonly
+from pandas.util._decorators import Appender, cache_readonly
 from pandas.core.config import get_option
 from pandas.core.indexes.base import Index, _index_shared_docs
 import pandas.core.base as base
diff --git a/pandas/core/indexes/datetimelike.py b/pandas/core/indexes/datetimelike.py
index 387209ceb038f1..cd8559bcca03cb 100644
--- a/pandas/core/indexes/datetimelike.py
+++ b/pandas/core/indexes/datetimelike.py
@@ -28,7 +28,7 @@
 from pandas._libs.period import Period
 
 from pandas.core.indexes.base import Index, _index_shared_docs
-from pandas.util.decorators import Appender, cache_readonly
+from pandas.util._decorators import Appender, cache_readonly
 import pandas.core.dtypes.concat as _concat
 import pandas.tseries.frequencies as frequencies
 
diff --git a/pandas/core/indexes/datetimes.py b/pandas/core/indexes/datetimes.py
index b0264759f2f8d3..ec678b1577d81b 100644
--- a/pandas/core/indexes/datetimes.py
+++ b/pandas/core/indexes/datetimes.py
@@ -41,8 +41,8 @@
 from pandas.core.tools.datetimes import (
     parse_time_string, normalize_date, to_time)
 from pandas.core.tools.timedeltas import to_timedelta
-from pandas.util.decorators import (Appender, cache_readonly,
-                                    deprecate_kwarg, Substitution)
+from pandas.util._decorators import (Appender, cache_readonly,
+                                     deprecate_kwarg, Substitution)
 import pandas.core.common as com
 import pandas.tseries.offsets as offsets
 import pandas.core.tools.datetimes as tools
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index ccd0d8bee4abc2..039346cba56c8c 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -28,7 +28,7 @@
 from pandas.core.indexes.multi import MultiIndex
 from pandas.compat.numpy import function as nv
 from pandas.core import common as com
-from pandas.util.decorators import cache_readonly, Appender
+from pandas.util._decorators import cache_readonly, Appender
 from pandas.core.config import get_option
 
 import pandas.core.indexes.base as ibase
diff --git a/pandas/core/indexes/multi.py b/pandas/core/indexes/multi.py
index c760d2943b823e..7ef037d8f3536f 100644
--- a/pandas/core/indexes/multi.py
+++ b/pandas/core/indexes/multi.py
@@ -26,8 +26,8 @@
                                 is_null_slice)
 
 import pandas.core.base as base
-from pandas.util.decorators import (Appender, cache_readonly,
-                                    deprecate, deprecate_kwarg)
+from pandas.util._decorators import (Appender, cache_readonly,
+                                     deprecate, deprecate_kwarg)
 import pandas.core.common as com
 import pandas.core.missing as missing
 import pandas.core.algorithms as algos
@@ -718,7 +718,7 @@ def _inferred_type_levels(self):
     @cache_readonly
     def _hashed_values(self):
         """ return a uint64 ndarray of my hashed values """
-        from pandas.util.hashing import hash_tuples
+        from pandas.core.util.hashing import hash_tuples
         return hash_tuples(self)
 
     def _hashed_indexing_key(self, key):
@@ -740,7 +740,7 @@ def _hashed_indexing_key(self, key):
         we need to stringify if we have mixed levels
 
         """
-        from pandas.util.hashing import hash_tuples
+        from pandas.core.util.hashing import hash_tuples
 
         if not isinstance(key, tuple):
             return hash_tuples(key)
diff --git a/pandas/core/indexes/numeric.py b/pandas/core/indexes/numeric.py
index 21ba2a386d96a3..bdae0ac7ac5e93 100644
--- a/pandas/core/indexes/numeric.py
+++ b/pandas/core/indexes/numeric.py
@@ -11,7 +11,7 @@
 from pandas.core import algorithms
 from pandas.core.indexes.base import (
     Index, InvalidIndexError, _index_shared_docs)
-from pandas.util.decorators import Appender, cache_readonly
+from pandas.util._decorators import Appender, cache_readonly
 import pandas.core.indexes.base as ibase
 
 
diff --git a/pandas/core/indexes/period.py b/pandas/core/indexes/period.py
index 378661a49e20dc..15fd9b7dc2b6a4 100644
--- a/pandas/core/indexes/period.py
+++ b/pandas/core/indexes/period.py
@@ -40,8 +40,8 @@
 from pandas.core.indexes.base import _index_shared_docs, _ensure_index
 
 from pandas import compat
-from pandas.util.decorators import (Appender, Substitution, cache_readonly,
-                                    deprecate_kwarg)
+from pandas.util._decorators import (Appender, Substitution, cache_readonly,
+                                     deprecate_kwarg)
 from pandas.compat import zip, u
 
 import pandas.core.indexes.base as ibase
diff --git a/pandas/core/indexes/range.py b/pandas/core/indexes/range.py
index acd040693af2e9..b7a8e0b54a1289 100644
--- a/pandas/core/indexes/range.py
+++ b/pandas/core/indexes/range.py
@@ -13,7 +13,7 @@
 from pandas.compat import lrange, range
 from pandas.compat.numpy import function as nv
 from pandas.core.indexes.base import Index, _index_shared_docs
-from pandas.util.decorators import Appender, cache_readonly
+from pandas.util._decorators import Appender, cache_readonly
 import pandas.core.indexes.base as ibase
 
 from pandas.core.indexes.numeric import Int64Index
diff --git a/pandas/core/indexes/timedeltas.py b/pandas/core/indexes/timedeltas.py
index 1081787b2c0b02..ab94a5bffb4f94 100644
--- a/pandas/core/indexes/timedeltas.py
+++ b/pandas/core/indexes/timedeltas.py
@@ -27,7 +27,7 @@
 from pandas.core.indexes.base import _index_shared_docs
 import pandas.core.common as com
 import pandas.core.dtypes.concat as _concat
-from pandas.util.decorators import Appender, Substitution, deprecate_kwarg
+from pandas.util._decorators import Appender, Substitution, deprecate_kwarg
 from pandas.core.indexes.datetimelike import TimelikeOps, DatetimeIndexOpsMixin
 from pandas.core.tools.timedeltas import (
     to_timedelta, _coerce_scalar_to_timedelta_type)
diff --git a/pandas/core/internals.py b/pandas/core/internals.py
index 840206977cf301..15851a17274cac 100644
--- a/pandas/core/internals.py
+++ b/pandas/core/internals.py
@@ -64,8 +64,8 @@
 from pandas._libs.lib import BlockPlacement
 
 import pandas.core.computation.expressions as expressions
-from pandas.util.decorators import cache_readonly
-from pandas.util.validators import validate_bool_kwarg
+from pandas.util._decorators import cache_readonly
+from pandas.util._validators import validate_bool_kwarg
 
 from pandas import compat, _np_version_under1p9
 from pandas.compat import range, map, zip, u
diff --git a/pandas/core/ops.py b/pandas/core/ops.py
index 41a17a0957cbf8..e7cfbdb0fc9c6f 100644
--- a/pandas/core/ops.py
+++ b/pandas/core/ops.py
@@ -15,7 +15,7 @@
                           tslib as libts, algos as libalgos, iNaT)
 
 from pandas import compat
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 import pandas.core.computation.expressions as expressions
 
 from pandas.compat import bind_method
diff --git a/pandas/core/panel.py b/pandas/core/panel.py
index 39d2ebdeec3ace..d1f5b4587059cf 100644
--- a/pandas/core/panel.py
+++ b/pandas/core/panel.py
@@ -34,7 +34,7 @@
 from pandas.core.ops import _op_descriptions
 from pandas.core.series import Series
 from pandas.core.reshape.util import cartesian_product
-from pandas.util.decorators import (deprecate, Appender)
+from pandas.util._decorators import (deprecate, Appender)
 
 _shared_doc_kwargs = dict(
     axes='items, major_axis, minor_axis',
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index cbb2f6a93c2fd3..631b91c3aad11e 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -25,7 +25,7 @@
 from pandas._libs.lib import Timestamp
 from pandas._libs.period import IncompatibleFrequency
 
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 from pandas.core.generic import _shared_docs
 _shared_docs_kwargs = dict()
 
diff --git a/pandas/core/reshape/merge.py b/pandas/core/reshape/merge.py
index 1ca3786ecc1743..c55f4b5bf935f1 100644
--- a/pandas/core/reshape/merge.py
+++ b/pandas/core/reshape/merge.py
@@ -34,7 +34,7 @@
 from pandas.core.dtypes.missing import na_value_for_dtype
 from pandas.core.internals import (items_overlap_with_suffix,
                                    concatenate_block_managers)
-from pandas.util.decorators import Appender, Substitution
+from pandas.util._decorators import Appender, Substitution
 
 from pandas.core.sorting import is_int64_overflow_possible
 import pandas.core.algorithms as algos
diff --git a/pandas/core/reshape/reshape.py b/pandas/core/reshape/reshape.py
index a3cf80d758b7b0..00b52e75f66fb3 100644
--- a/pandas/core/reshape/reshape.py
+++ b/pandas/core/reshape/reshape.py
@@ -30,7 +30,7 @@
 from pandas._libs import algos as _algos, reshape as _reshape
 
 from pandas.core.frame import _shared_docs
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 from pandas.core.index import MultiIndex, _get_na_value
 
 
diff --git a/pandas/core/series.py b/pandas/core/series.py
index e5f1d91eedfec8..6ec163bbaa73da 100644
--- a/pandas/core/series.py
+++ b/pandas/core/series.py
@@ -60,7 +60,7 @@
 from pandas.core.indexes.timedeltas import TimedeltaIndex
 from pandas.core.indexes.period import PeriodIndex
 from pandas import compat
-from pandas.util.terminal import get_terminal_size
+from pandas.io.formats.terminal import get_terminal_size
 from pandas.compat import zip, u, OrderedDict, StringIO
 from pandas.compat.numpy import function as nv
 
@@ -70,8 +70,8 @@
 import pandas.core.common as com
 import pandas.core.nanops as nanops
 import pandas.io.formats.format as fmt
-from pandas.util.decorators import Appender, deprecate_kwarg, Substitution
-from pandas.util.validators import validate_bool_kwarg
+from pandas.util._decorators import Appender, deprecate_kwarg, Substitution
+from pandas.util._validators import validate_bool_kwarg
 
 from pandas._libs import index as libindex, tslib as libts, lib, iNaT
 from pandas.core.config import get_option
diff --git a/pandas/core/sparse/array.py b/pandas/core/sparse/array.py
index ef3600266c0370..dc34edd607ffb3 100644
--- a/pandas/core/sparse/array.py
+++ b/pandas/core/sparse/array.py
@@ -35,7 +35,7 @@
 import pandas.core.algorithms as algos
 import pandas.core.ops as ops
 import pandas.io.formats.printing as printing
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 from pandas.core.indexes.base import _index_shared_docs
 
 
diff --git a/pandas/core/sparse/frame.py b/pandas/core/sparse/frame.py
index 05c97fac4b53a2..378d4ed4514a9b 100644
--- a/pandas/core/sparse/frame.py
+++ b/pandas/core/sparse/frame.py
@@ -26,7 +26,7 @@
 import pandas.core.generic as generic
 from pandas.core.sparse.series import SparseSeries, SparseArray
 from pandas.core.sparse.libsparse import BlockIndex, get_blocks
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 import pandas.core.ops as ops
 
 
diff --git a/pandas/core/sparse/list.py b/pandas/core/sparse/list.py
index e69ad6d0ab7adc..e40cb30d37fda4 100644
--- a/pandas/core/sparse/list.py
+++ b/pandas/core/sparse/list.py
@@ -5,7 +5,7 @@
 
 from pandas.core.dtypes.common import is_scalar
 from pandas.core.sparse.array import SparseArray
-from pandas.util.validators import validate_bool_kwarg
+from pandas.util._validators import validate_bool_kwarg
 from pandas.core.sparse import libsparse as splib
 
 
diff --git a/pandas/core/sparse/series.py b/pandas/core/sparse/series.py
index a77bce8f06783a..52a07f340336e1 100644
--- a/pandas/core/sparse/series.py
+++ b/pandas/core/sparse/series.py
@@ -21,7 +21,7 @@
 import pandas.core.common as com
 import pandas.core.ops as ops
 import pandas._libs.index as _index
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 
 from pandas.core.sparse.array import (
     make_sparse, _sparse_array_op, SparseArray,
diff --git a/pandas/core/strings.py b/pandas/core/strings.py
index 5082ac7f80fbfe..c57d7a93624900 100644
--- a/pandas/core/strings.py
+++ b/pandas/core/strings.py
@@ -17,7 +17,7 @@
 from pandas.core.algorithms import take_1d
 import pandas.compat as compat
 from pandas.core.base import AccessorProperty, NoNewAttributesMixin
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 import re
 import pandas._libs.lib as lib
 import warnings
diff --git a/pandas/util/importing.py b/pandas/core/util/__init__.py
similarity index 100%
rename from pandas/util/importing.py
rename to pandas/core/util/__init__.py
diff --git a/pandas/core/util/hashing.py b/pandas/core/util/hashing.py
new file mode 100644
index 00000000000000..6a5343e8a8e252
--- /dev/null
+++ b/pandas/core/util/hashing.py
@@ -0,0 +1,282 @@
+"""
+data hash pandas / numpy objects
+"""
+import itertools
+
+import numpy as np
+from pandas._libs import hashing
+from pandas._libs.lib import is_bool_array
+from pandas.core.dtypes.generic import (
+    ABCMultiIndex,
+    ABCIndexClass,
+    ABCSeries,
+    ABCDataFrame)
+from pandas.core.dtypes.common import (
+    is_categorical_dtype, is_numeric_dtype,
+    is_datetime64_dtype, is_timedelta64_dtype,
+    is_list_like)
+
+# 16 byte long hashing key
+_default_hash_key = '0123456789123456'
+
+
+def _combine_hash_arrays(arrays, num_items):
+    """
+    Parameters
+    ----------
+    arrays : generator
+    num_items : int
+
+    Should be the same as CPython's tupleobject.c
+    """
+    try:
+        first = next(arrays)
+    except StopIteration:
+        return np.array([], dtype=np.uint64)
+
+    arrays = itertools.chain([first], arrays)
+
+    mult = np.uint64(1000003)
+    out = np.zeros_like(first) + np.uint64(0x345678)
+    for i, a in enumerate(arrays):
+        inverse_i = num_items - i
+        out ^= a
+        out *= mult
+        mult += np.uint64(82520 + inverse_i + inverse_i)
+    assert i + 1 == num_items, 'Fed in wrong num_items'
+    out += np.uint64(97531)
+    return out
+
+
+def hash_pandas_object(obj, index=True, encoding='utf8', hash_key=None,
+                       categorize=True):
+    """
+    Return a data hash of the Index/Series/DataFrame
+
+    .. versionadded:: 0.19.2
+
+    Parameters
+    ----------
+    index : boolean, default True
+        include the index in the hash (if Series/DataFrame)
+    encoding : string, default 'utf8'
+        encoding for data & key when strings
+    hash_key : string key to encode, default to _default_hash_key
+    categorize : bool, default True
+        Whether to first categorize object arrays before hashing. This is more
+        efficient when the array contains duplicate values.
+
+        .. versionadded:: 0.20.0
+
+    Returns
+    -------
+    Series of uint64, same length as the object
+
+    """
+    from pandas import Series
+    if hash_key is None:
+        hash_key = _default_hash_key
+
+    if isinstance(obj, ABCMultiIndex):
+        return Series(hash_tuples(obj, encoding, hash_key),
+                      dtype='uint64', copy=False)
+
+    if isinstance(obj, ABCIndexClass):
+        h = hash_array(obj.values, encoding, hash_key,
+                       categorize).astype('uint64', copy=False)
+        h = Series(h, index=obj, dtype='uint64', copy=False)
+    elif isinstance(obj, ABCSeries):
+        h = hash_array(obj.values, encoding, hash_key,
+                       categorize).astype('uint64', copy=False)
+        if index:
+            index_iter = (hash_pandas_object(obj.index,
+                                             index=False,
+                                             encoding=encoding,
+                                             hash_key=hash_key,
+                                             categorize=categorize).values
+                          for _ in [None])
+            arrays = itertools.chain([h], index_iter)
+            h = _combine_hash_arrays(arrays, 2)
+
+        h = Series(h, index=obj.index, dtype='uint64', copy=False)
+
+    elif isinstance(obj, ABCDataFrame):
+        hashes = (hash_array(series.values) for _, series in obj.iteritems())
+        num_items = len(obj.columns)
+        if index:
+            index_hash_generator = (hash_pandas_object(obj.index,
+                                                       index=False,
+                                                       encoding=encoding,
+                                                       hash_key=hash_key,
+                                                       categorize=categorize).values  # noqa
+                                    for _ in [None])
+            num_items += 1
+            hashes = itertools.chain(hashes, index_hash_generator)
+        h = _combine_hash_arrays(hashes, num_items)
+
+        h = Series(h, index=obj.index, dtype='uint64', copy=False)
+    else:
+        raise TypeError("Unexpected type for hashing %s" % type(obj))
+    return h
+
+
+def hash_tuples(vals, encoding='utf8', hash_key=None):
+    """
+    Hash an MultiIndex / list-of-tuples efficiently
+
+    .. versionadded:: 0.20.0
+
+    Parameters
+    ----------
+    vals : MultiIndex, list-of-tuples, or single tuple
+    encoding : string, default 'utf8'
+    hash_key : string key to encode, default to _default_hash_key
+
+    Returns
+    -------
+    ndarray of hashed values array
+    """
+
+    is_tuple = False
+    if isinstance(vals, tuple):
+        vals = [vals]
+        is_tuple = True
+    elif not is_list_like(vals):
+        raise TypeError("must be convertible to a list-of-tuples")
+
+    from pandas import Categorical, MultiIndex
+
+    if not isinstance(vals, ABCMultiIndex):
+        vals = MultiIndex.from_tuples(vals)
+
+    # create a list-of-Categoricals
+    vals = [Categorical(vals.labels[level],
+                        vals.levels[level],
+                        ordered=False,
+                        fastpath=True)
+            for level in range(vals.nlevels)]
+
+    # hash the list-of-ndarrays
+    hashes = (_hash_categorical(cat,
+                                encoding=encoding,
+                                hash_key=hash_key)
+              for cat in vals)
+    h = _combine_hash_arrays(hashes, len(vals))
+    if is_tuple:
+        h = h[0]
+
+    return h
+
+
+def _hash_categorical(c, encoding, hash_key):
+    """
+    Hash a Categorical by hashing its categories, and then mapping the codes
+    to the hashes
+
+    Parameters
+    ----------
+    c : Categorical
+    encoding : string, default 'utf8'
+    hash_key : string key to encode, default to _default_hash_key
+
+    Returns
+    -------
+    ndarray of hashed values array, same size as len(c)
+    """
+    hashed = hash_array(c.categories.values, encoding, hash_key,
+                        categorize=False)
+
+    # we have uint64, as we don't directly support missing values
+    # we don't want to use take_nd which will coerce to float
+    # instead, directly construt the result with a
+    # max(np.uint64) as the missing value indicator
+    #
+    # TODO: GH 15362
+
+    mask = c.isnull()
+    if len(hashed):
+        result = hashed.take(c.codes)
+    else:
+        result = np.zeros(len(mask), dtype='uint64')
+
+    if mask.any():
+        result[mask] = np.iinfo(np.uint64).max
+
+    return result
+
+
+def hash_array(vals, encoding='utf8', hash_key=None, categorize=True):
+    """
+    Given a 1d array, return an array of deterministic integers.
+
+    .. versionadded:: 0.19.2
+
+    Parameters
+    ----------
+    vals : ndarray, Categorical
+    encoding : string, default 'utf8'
+        encoding for data & key when strings
+    hash_key : string key to encode, default to _default_hash_key
+    categorize : bool, default True
+        Whether to first categorize object arrays before hashing. This is more
+        efficient when the array contains duplicate values.
+
+        .. versionadded:: 0.20.0
+
+    Returns
+    -------
+    1d uint64 numpy array of hash values, same length as the vals
+
+    """
+
+    if not hasattr(vals, 'dtype'):
+        raise TypeError("must pass a ndarray-like")
+
+    if hash_key is None:
+        hash_key = _default_hash_key
+
+    # For categoricals, we hash the categories, then remap the codes to the
+    # hash values. (This check is above the complex check so that we don't ask
+    # numpy if categorical is a subdtype of complex, as it will choke.
+    if is_categorical_dtype(vals.dtype):
+        return _hash_categorical(vals, encoding, hash_key)
+
+    # we'll be working with everything as 64-bit values, so handle this
+    # 128-bit value early
+    if np.issubdtype(vals.dtype, np.complex128):
+        return hash_array(vals.real) + 23 * hash_array(vals.imag)
+
+    # First, turn whatever array this is into unsigned 64-bit ints, if we can
+    # manage it.
+    if is_bool_array(vals):
+        vals = vals.astype('u8')
+    elif (is_datetime64_dtype(vals) or
+          is_timedelta64_dtype(vals)):
+        vals = vals.view('i8').astype('u8', copy=False)
+    elif (is_numeric_dtype(vals) and vals.dtype.itemsize <= 8):
+        vals = vals.view('u{}'.format(vals.dtype.itemsize)).astype('u8')
+    else:
+        # With repeated values, its MUCH faster to categorize object dtypes,
+        # then hash and rename categories. We allow skipping the categorization
+        # when the values are known/likely to be unique.
+        if categorize:
+            from pandas import factorize, Categorical, Index
+            codes, categories = factorize(vals, sort=False)
+            cat = Categorical(codes, Index(categories),
+                              ordered=False, fastpath=True)
+            return _hash_categorical(cat, encoding, hash_key)
+
+        try:
+            vals = hashing.hash_object_array(vals, hash_key, encoding)
+        except TypeError:
+            # we have mixed types
+            vals = hashing.hash_object_array(vals.astype(str).astype(object),
+                                             hash_key, encoding)
+
+    # Then, redistribute these 64-bit ints within the space of 64-bit ints
+    vals ^= vals >> 30
+    vals *= np.uint64(0xbf58476d1ce4e5b9)
+    vals ^= vals >> 27
+    vals *= np.uint64(0x94d049bb133111eb)
+    vals ^= vals >> 31
+    return vals
diff --git a/pandas/core/window.py b/pandas/core/window.py
index 6d8f12e982f12b..772e7422b27a95 100644
--- a/pandas/core/window.py
+++ b/pandas/core/window.py
@@ -37,8 +37,8 @@
 from pandas.tseries.offsets import DateOffset
 from pandas import compat
 from pandas.compat.numpy import function as nv
-from pandas.util.decorators import (Substitution, Appender,
-                                    cache_readonly)
+from pandas.util._decorators import (Substitution, Appender,
+                                     cache_readonly)
 from pandas.core.generic import _shared_docs
 from textwrap import dedent
 
diff --git a/pandas/io/api.py b/pandas/io/api.py
index e312e7bc2f300f..7f0d3c3631f639 100644
--- a/pandas/io/api.py
+++ b/pandas/io/api.py
@@ -5,7 +5,7 @@
 # flake8: noqa
 
 from pandas.io.parsers import read_csv, read_table, read_fwf
-from pandas.io.clipboard import read_clipboard
+from pandas.io.clipboard.clipboard import read_clipboard
 from pandas.io.excel import ExcelFile, ExcelWriter, read_excel
 from pandas.io.pytables import HDFStore, get_store, read_hdf
 from pandas.io.json import read_json
diff --git a/pandas/util/clipboard/__init__.py b/pandas/io/clipboard/__init__.py
similarity index 100%
rename from pandas/util/clipboard/__init__.py
rename to pandas/io/clipboard/__init__.py
diff --git a/pandas/io/clipboard.py b/pandas/io/clipboard/clipboard.py
similarity index 97%
rename from pandas/io/clipboard.py
rename to pandas/io/clipboard/clipboard.py
index 3c7ac528d83fdd..6252a02b0d63da 100644
--- a/pandas/io/clipboard.py
+++ b/pandas/io/clipboard/clipboard.py
@@ -26,7 +26,7 @@ def read_clipboard(sep='\s+', **kwargs):  # pragma: no cover
         raise NotImplementedError(
             'reading from clipboard only supports utf-8 encoding')
 
-    from pandas.util.clipboard import clipboard_get
+    from pandas.io.clipboard import clipboard_get
     from pandas.io.parsers import read_table
     text = clipboard_get()
 
@@ -92,7 +92,7 @@ def to_clipboard(obj, excel=None, sep=None, **kwargs):  # pragma: no cover
     if encoding is not None and encoding.lower().replace('-', '') != 'utf8':
         raise ValueError('clipboard only supports utf-8 encoding')
 
-    from pandas.util.clipboard import clipboard_set
+    from pandas.io.clipboard import clipboard_set
     if excel is None:
         excel = True
 
diff --git a/pandas/util/clipboard/clipboards.py b/pandas/io/clipboard/clipboards.py
similarity index 100%
rename from pandas/util/clipboard/clipboards.py
rename to pandas/io/clipboard/clipboards.py
diff --git a/pandas/util/clipboard/exceptions.py b/pandas/io/clipboard/exceptions.py
similarity index 100%
rename from pandas/util/clipboard/exceptions.py
rename to pandas/io/clipboard/exceptions.py
diff --git a/pandas/util/clipboard/windows.py b/pandas/io/clipboard/windows.py
similarity index 100%
rename from pandas/util/clipboard/windows.py
rename to pandas/io/clipboard/windows.py
diff --git a/pandas/io/excel.py b/pandas/io/excel.py
index fbb10ebdfc56de..f56b555163d5ab 100644
--- a/pandas/io/excel.py
+++ b/pandas/io/excel.py
@@ -29,7 +29,7 @@
 import pandas.compat.openpyxl_compat as openpyxl_compat
 from warnings import warn
 from distutils.version import LooseVersion
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 from textwrap import fill
 
 __all__ = ["read_excel", "ExcelWriter", "ExcelFile"]
diff --git a/pandas/io/formats/console.py b/pandas/io/formats/console.py
index 0e46b0073a53de..ab75e3fa253ced 100644
--- a/pandas/io/formats/console.py
+++ b/pandas/io/formats/console.py
@@ -4,7 +4,7 @@
 
 import sys
 import locale
-from pandas.util.terminal import get_terminal_size
+from pandas.io.formats.terminal import get_terminal_size
 
 # -----------------------------------------------------------------------------
 # Global formatting options
diff --git a/pandas/io/formats/format.py b/pandas/io/formats/format.py
index 43b0b5fbeee906..65098bb2aa4045 100644
--- a/pandas/io/formats/format.py
+++ b/pandas/io/formats/format.py
@@ -30,7 +30,7 @@
 from pandas import compat
 from pandas.compat import (StringIO, lzip, range, map, zip, u,
                            OrderedDict, unichr)
-from pandas.util.terminal import get_terminal_size
+from pandas.io.formats.terminal import get_terminal_size
 from pandas.core.config import get_option, set_option
 from pandas.io.common import _get_handle, UnicodeWriter, _expand_user
 from pandas.io.formats.printing import adjoin, justify, pprint_thing
diff --git a/pandas/io/formats/style.py b/pandas/io/formats/style.py
index 71c61998be0924..eac82ddde23187 100644
--- a/pandas/io/formats/style.py
+++ b/pandas/io/formats/style.py
@@ -29,7 +29,7 @@
 from pandas.core.generic import _shared_docs
 import pandas.core.common as com
 from pandas.core.indexing import _maybe_numeric_slice, _non_reducing_slice
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 try:
     import matplotlib.pyplot as plt
     from matplotlib import colors
diff --git a/pandas/util/terminal.py b/pandas/io/formats/terminal.py
similarity index 100%
rename from pandas/util/terminal.py
rename to pandas/io/formats/terminal.py
diff --git a/pandas/io/parsers.py b/pandas/io/parsers.py
index 95b1394c88ac2c..d9e163cb50695e 100755
--- a/pandas/io/parsers.py
+++ b/pandas/io/parsers.py
@@ -37,7 +37,7 @@
                               _NA_VALUES, _infer_compression)
 from pandas.core.tools import datetimes as tools
 
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 
 import pandas._libs.lib as lib
 import pandas.io.libparsers as libparsers
diff --git a/pandas/io/sas/sas_xport.py b/pandas/io/sas/sas_xport.py
index 76fc55154bc497..a43a5988a2ade8 100644
--- a/pandas/io/sas/sas_xport.py
+++ b/pandas/io/sas/sas_xport.py
@@ -14,7 +14,7 @@
 from pandas import compat
 import struct
 import numpy as np
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 import warnings
 
 _correct_line1 = ("HEADER RECORD*******LIBRARY HEADER RECORD!!!!!!!"
diff --git a/pandas/io/stata.py b/pandas/io/stata.py
index 691582629251a1..55cac83804cd90 100644
--- a/pandas/io/stata.py
+++ b/pandas/io/stata.py
@@ -27,7 +27,7 @@
 from pandas import compat, to_timedelta, to_datetime, isnull, DatetimeIndex
 from pandas.compat import lrange, lmap, lzip, text_type, string_types, range, \
     zip, BytesIO
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 import pandas as pd
 
 from pandas.io.common import get_filepath_or_buffer, BaseIterator
diff --git a/pandas/plotting/_core.py b/pandas/plotting/_core.py
index c3476d1443fc3a..e88979b14c8af2 100644
--- a/pandas/plotting/_core.py
+++ b/pandas/plotting/_core.py
@@ -9,7 +9,7 @@
 
 import numpy as np
 
-from pandas.util.decorators import cache_readonly
+from pandas.util._decorators import cache_readonly
 from pandas.core.base import PandasObject
 from pandas.core.dtypes.common import (
     is_list_like,
@@ -25,7 +25,7 @@
 from pandas.compat import range, lrange, map, zip, string_types
 import pandas.compat as compat
 from pandas.io.formats.printing import pprint_thing
-from pandas.util.decorators import Appender
+from pandas.util._decorators import Appender
 
 from pandas.plotting._compat import (_mpl_ge_1_3_1,
                                      _mpl_ge_1_5_0)
diff --git a/pandas/plotting/_misc.py b/pandas/plotting/_misc.py
index 93eceba9a3f026..20ada033c0f58a 100644
--- a/pandas/plotting/_misc.py
+++ b/pandas/plotting/_misc.py
@@ -4,7 +4,7 @@
 
 import numpy as np
 
-from pandas.util.decorators import deprecate_kwarg
+from pandas.util._decorators import deprecate_kwarg
 from pandas.core.dtypes.missing import notnull
 from pandas.compat import range, lrange, lmap, zip
 from pandas.io.formats.printing import pprint_thing
diff --git a/pandas/stats/moments.py b/pandas/stats/moments.py
index f98ffa26e0c2bb..f6c3a08c6721ac 100644
--- a/pandas/stats/moments.py
+++ b/pandas/stats/moments.py
@@ -8,7 +8,7 @@
 import numpy as np
 from pandas.core.dtypes.common import is_scalar
 from pandas.core.api import DataFrame, Series
-from pandas.util.decorators import Substitution, Appender
+from pandas.util._decorators import Substitution, Appender
 
 __all__ = ['rolling_count', 'rolling_max', 'rolling_min',
            'rolling_sum', 'rolling_mean', 'rolling_std', 'rolling_cov',
diff --git a/pandas/tests/frame/common.py b/pandas/tests/frame/common.py
index b9cd764c8704c7..b475d25eb5dac6 100644
--- a/pandas/tests/frame/common.py
+++ b/pandas/tests/frame/common.py
@@ -1,7 +1,7 @@
 import numpy as np
 
 from pandas import compat
-from pandas.util.decorators import cache_readonly
+from pandas.util._decorators import cache_readonly
 import pandas.util.testing as tm
 import pandas as pd
 
diff --git a/pandas/tests/io/formats/test_format.py b/pandas/tests/io/formats/test_format.py
index 3cea731cfd4404..648ff9387b5d87 100644
--- a/pandas/tests/io/formats/test_format.py
+++ b/pandas/tests/io/formats/test_format.py
@@ -29,7 +29,7 @@
 import pandas.io.formats.printing as printing
 
 import pandas.util.testing as tm
-from pandas.util.terminal import get_terminal_size
+from pandas.io.formats.terminal import get_terminal_size
 from pandas.core.config import (set_option, get_option, option_context,
                                 reset_option)
 
diff --git a/pandas/tests/io/test_clipboard.py b/pandas/tests/io/test_clipboard.py
index e9ffb2dca7ae5d..5ae4a18e8108c8 100644
--- a/pandas/tests/io/test_clipboard.py
+++ b/pandas/tests/io/test_clipboard.py
@@ -10,7 +10,7 @@
 from pandas import get_option
 from pandas.util import testing as tm
 from pandas.util.testing import makeCustomDataframe as mkdf
-from pandas.util.clipboard.exceptions import PyperclipException
+from pandas.io.clipboard.exceptions import PyperclipException
 
 
 try:
diff --git a/pandas/tests/plotting/common.py b/pandas/tests/plotting/common.py
index 9a24e4ae2dad00..444e5b12f212fe 100644
--- a/pandas/tests/plotting/common.py
+++ b/pandas/tests/plotting/common.py
@@ -7,7 +7,7 @@
 
 from pandas import DataFrame, Series
 from pandas.compat import zip, iteritems
-from pandas.util.decorators import cache_readonly
+from pandas.util._decorators import cache_readonly
 from pandas.core.dtypes.api import is_list_like
 import pandas.util.testing as tm
 from pandas.util.testing import (ensure_clean,
diff --git a/pandas/tests/series/common.py b/pandas/tests/series/common.py
index 613961e1c670f0..0c25dcb29c3b2a 100644
--- a/pandas/tests/series/common.py
+++ b/pandas/tests/series/common.py
@@ -1,4 +1,4 @@
-from pandas.util.decorators import cache_readonly
+from pandas.util._decorators import cache_readonly
 import pandas.util.testing as tm
 import pandas as pd
 
diff --git a/pandas/tests/util/__init__.py b/pandas/tests/util/__init__.py
new file mode 100644
index 00000000000000..e69de29bb2d1d6
diff --git a/pandas/tests/reshape/test_hashing.py b/pandas/tests/util/test_hashing.py
similarity index 94%
rename from pandas/tests/reshape/test_hashing.py
rename to pandas/tests/util/test_hashing.py
index 622768353dd50f..0d2122ff14221c 100644
--- a/pandas/tests/reshape/test_hashing.py
+++ b/pandas/tests/util/test_hashing.py
@@ -5,7 +5,8 @@
 import pandas as pd
 
 from pandas import DataFrame, Series, Index, MultiIndex
-from pandas.util.hashing import hash_array, hash_tuples, hash_pandas_object
+from pandas.util import hash_array, hash_pandas_object
+from pandas.core.util.hashing import hash_tuples
 import pandas.util.testing as tm
 
 
@@ -267,3 +268,18 @@ def test_hash_collisions(self):
         result = hash_array(np.asarray(L, dtype=object), 'utf8')
         tm.assert_numpy_array_equal(
             result, np.concatenate([expected1, expected2], axis=0))
+
+
+def test_deprecation():
+
+    with tm.assert_produces_warning(FutureWarning,
+                                    check_stacklevel=False):
+        from pandas.util.hashing import hash_pandas_object
+        obj = Series(list('abc'))
+        hash_pandas_object(obj, hash_key='9876543210123456')
+
+    with tm.assert_produces_warning(FutureWarning,
+                                    check_stacklevel=False):
+        from pandas.util.hashing import hash_array
+        obj = np.array([1, 2, 3])
+        hash_array(obj, hash_key='9876543210123456')
diff --git a/pandas/tests/test_testing.py b/pandas/tests/util/test_testing.py
similarity index 100%
rename from pandas/tests/test_testing.py
rename to pandas/tests/util/test_testing.py
diff --git a/pandas/tests/test_util.py b/pandas/tests/util/test_util.py
similarity index 98%
rename from pandas/tests/test_util.py
rename to pandas/tests/util/test_util.py
index e9e04f76704f2d..65e2cf7006ca8d 100644
--- a/pandas/tests/test_util.py
+++ b/pandas/tests/util/test_util.py
@@ -9,10 +9,10 @@
 import pytest
 from pandas.compat import intern
 from pandas.util._move import move_into_mutable_buffer, BadMove, stolenbuf
-from pandas.util.decorators import deprecate_kwarg
-from pandas.util.validators import (validate_args, validate_kwargs,
-                                    validate_args_and_kwargs,
-                                    validate_bool_kwarg)
+from pandas.util._decorators import deprecate_kwarg
+from pandas.util._validators import (validate_args, validate_kwargs,
+                                     validate_args_and_kwargs,
+                                     validate_bool_kwarg)
 
 import pandas.util.testing as tm
 
diff --git a/pandas/tseries/frequencies.py b/pandas/tseries/frequencies.py
index 06d70f14565184..dddf835424f67e 100644
--- a/pandas/tseries/frequencies.py
+++ b/pandas/tseries/frequencies.py
@@ -16,7 +16,7 @@
 import pandas.core.algorithms as algos
 from pandas.core.algorithms import unique
 from pandas.tseries.offsets import DateOffset
-from pandas.util.decorators import cache_readonly, deprecate_kwarg
+from pandas.util._decorators import cache_readonly, deprecate_kwarg
 import pandas.tseries.offsets as offsets
 
 from pandas._libs import lib, tslib
diff --git a/pandas/util/__init__.py b/pandas/util/__init__.py
index e69de29bb2d1d6..e86af930fef7c3 100644
--- a/pandas/util/__init__.py
+++ b/pandas/util/__init__.py
@@ -0,0 +1,2 @@
+from pandas.core.util.hashing import hash_pandas_object, hash_array   # noqa
+from pandas.util._decorators import Appender, Substitution, cache_readonly  # noqa
diff --git a/pandas/util/decorators.py b/pandas/util/_decorators.py
similarity index 100%
rename from pandas/util/decorators.py
rename to pandas/util/_decorators.py
diff --git a/pandas/util/depr_module.py b/pandas/util/_depr_module.py
similarity index 100%
rename from pandas/util/depr_module.py
rename to pandas/util/_depr_module.py
diff --git a/pandas/util/doctools.py b/pandas/util/_doctools.py
similarity index 100%
rename from pandas/util/doctools.py
rename to pandas/util/_doctools.py
diff --git a/pandas/util/print_versions.py b/pandas/util/_print_versions.py
similarity index 100%
rename from pandas/util/print_versions.py
rename to pandas/util/_print_versions.py
diff --git a/pandas/util/testing.pyx b/pandas/util/_testing.pyx
similarity index 100%
rename from pandas/util/testing.pyx
rename to pandas/util/_testing.pyx
diff --git a/pandas/util/validators.py b/pandas/util/_validators.py
similarity index 100%
rename from pandas/util/validators.py
rename to pandas/util/_validators.py
diff --git a/pandas/util/hashing.py b/pandas/util/hashing.py
index 3046c62a03f48c..de2f91f9f6b4a0 100644
--- a/pandas/util/hashing.py
+++ b/pandas/util/hashing.py
@@ -1,278 +1,18 @@
-"""
-data hash pandas / numpy objects
-"""
-import itertools
+import warnings
+import sys
 
-import numpy as np
-from pandas import Series, factorize, Categorical, Index, MultiIndex
-from pandas.util import libhashing as _hash
-from pandas._libs.lib import is_bool_array
-from pandas.core.dtypes.generic import (
-    ABCIndexClass,
-    ABCSeries,
-    ABCDataFrame)
-from pandas.core.dtypes.common import (
-    is_categorical_dtype, is_numeric_dtype,
-    is_datetime64_dtype, is_timedelta64_dtype,
-    is_list_like)
+m = sys.modules['pandas.util.hashing']
+for t in ['hash_pandas_object', 'hash_array']:
 
-# 16 byte long hashing key
-_default_hash_key = '0123456789123456'
+    def outer(t=t):
 
+        def wrapper(*args, **kwargs):
+            from pandas import util
+            warnings.warn("pandas.util.hashing is deprecated and will be "
+                          "removed in a future version, import "
+                          "from pandas.util",
+                          FutureWarning, stacklevel=3)
+            return getattr(util, t)(*args, **kwargs)
+        return wrapper
 
-def _combine_hash_arrays(arrays, num_items):
-    """
-    Parameters
-    ----------
-    arrays : generator
-    num_items : int
-
-    Should be the same as CPython's tupleobject.c
-    """
-    try:
-        first = next(arrays)
-    except StopIteration:
-        return np.array([], dtype=np.uint64)
-
-    arrays = itertools.chain([first], arrays)
-
-    mult = np.uint64(1000003)
-    out = np.zeros_like(first) + np.uint64(0x345678)
-    for i, a in enumerate(arrays):
-        inverse_i = num_items - i
-        out ^= a
-        out *= mult
-        mult += np.uint64(82520 + inverse_i + inverse_i)
-    assert i + 1 == num_items, 'Fed in wrong num_items'
-    out += np.uint64(97531)
-    return out
-
-
-def hash_pandas_object(obj, index=True, encoding='utf8', hash_key=None,
-                       categorize=True):
-    """
-    Return a data hash of the Index/Series/DataFrame
-
-    .. versionadded:: 0.19.2
-
-    Parameters
-    ----------
-    index : boolean, default True
-        include the index in the hash (if Series/DataFrame)
-    encoding : string, default 'utf8'
-        encoding for data & key when strings
-    hash_key : string key to encode, default to _default_hash_key
-    categorize : bool, default True
-        Whether to first categorize object arrays before hashing. This is more
-        efficient when the array contains duplicate values.
-
-        .. versionadded:: 0.20.0
-
-    Returns
-    -------
-    Series of uint64, same length as the object
-
-    """
-    if hash_key is None:
-        hash_key = _default_hash_key
-
-    if isinstance(obj, MultiIndex):
-        return Series(hash_tuples(obj, encoding, hash_key),
-                      dtype='uint64', copy=False)
-
-    if isinstance(obj, ABCIndexClass):
-        h = hash_array(obj.values, encoding, hash_key,
-                       categorize).astype('uint64', copy=False)
-        h = Series(h, index=obj, dtype='uint64', copy=False)
-    elif isinstance(obj, ABCSeries):
-        h = hash_array(obj.values, encoding, hash_key,
-                       categorize).astype('uint64', copy=False)
-        if index:
-            index_iter = (hash_pandas_object(obj.index,
-                                             index=False,
-                                             encoding=encoding,
-                                             hash_key=hash_key,
-                                             categorize=categorize).values
-                          for _ in [None])
-            arrays = itertools.chain([h], index_iter)
-            h = _combine_hash_arrays(arrays, 2)
-
-        h = Series(h, index=obj.index, dtype='uint64', copy=False)
-
-    elif isinstance(obj, ABCDataFrame):
-        hashes = (hash_array(series.values) for _, series in obj.iteritems())
-        num_items = len(obj.columns)
-        if index:
-            index_hash_generator = (hash_pandas_object(obj.index,
-                                                       index=False,
-                                                       encoding=encoding,
-                                                       hash_key=hash_key,
-                                                       categorize=categorize).values  # noqa
-                                    for _ in [None])
-            num_items += 1
-            hashes = itertools.chain(hashes, index_hash_generator)
-        h = _combine_hash_arrays(hashes, num_items)
-
-        h = Series(h, index=obj.index, dtype='uint64', copy=False)
-    else:
-        raise TypeError("Unexpected type for hashing %s" % type(obj))
-    return h
-
-
-def hash_tuples(vals, encoding='utf8', hash_key=None):
-    """
-    Hash an MultiIndex / list-of-tuples efficiently
-
-    .. versionadded:: 0.20.0
-
-    Parameters
-    ----------
-    vals : MultiIndex, list-of-tuples, or single tuple
-    encoding : string, default 'utf8'
-    hash_key : string key to encode, default to _default_hash_key
-
-    Returns
-    -------
-    ndarray of hashed values array
-    """
-
-    is_tuple = False
-    if isinstance(vals, tuple):
-        vals = [vals]
-        is_tuple = True
-    elif not is_list_like(vals):
-        raise TypeError("must be convertible to a list-of-tuples")
-
-    if not isinstance(vals, MultiIndex):
-        vals = MultiIndex.from_tuples(vals)
-
-    # create a list-of-Categoricals
-    vals = [Categorical(vals.labels[level],
-                        vals.levels[level],
-                        ordered=False,
-                        fastpath=True)
-            for level in range(vals.nlevels)]
-
-    # hash the list-of-ndarrays
-    hashes = (_hash_categorical(cat,
-                                encoding=encoding,
-                                hash_key=hash_key)
-              for cat in vals)
-    h = _combine_hash_arrays(hashes, len(vals))
-    if is_tuple:
-        h = h[0]
-
-    return h
-
-
-def _hash_categorical(c, encoding, hash_key):
-    """
-    Hash a Categorical by hashing its categories, and then mapping the codes
-    to the hashes
-
-    Parameters
-    ----------
-    c : Categorical
-    encoding : string, default 'utf8'
-    hash_key : string key to encode, default to _default_hash_key
-
-    Returns
-    -------
-    ndarray of hashed values array, same size as len(c)
-    """
-    hashed = hash_array(c.categories.values, encoding, hash_key,
-                        categorize=False)
-
-    # we have uint64, as we don't directly support missing values
-    # we don't want to use take_nd which will coerce to float
-    # instead, directly construt the result with a
-    # max(np.uint64) as the missing value indicator
-    #
-    # TODO: GH 15362
-
-    mask = c.isnull()
-    if len(hashed):
-        result = hashed.take(c.codes)
-    else:
-        result = np.zeros(len(mask), dtype='uint64')
-
-    if mask.any():
-        result[mask] = np.iinfo(np.uint64).max
-
-    return result
-
-
-def hash_array(vals, encoding='utf8', hash_key=None, categorize=True):
-    """
-    Given a 1d array, return an array of deterministic integers.
-
-    .. versionadded:: 0.19.2
-
-    Parameters
-    ----------
-    vals : ndarray, Categorical
-    encoding : string, default 'utf8'
-        encoding for data & key when strings
-    hash_key : string key to encode, default to _default_hash_key
-    categorize : bool, default True
-        Whether to first categorize object arrays before hashing. This is more
-        efficient when the array contains duplicate values.
-
-        .. versionadded:: 0.20.0
-
-    Returns
-    -------
-    1d uint64 numpy array of hash values, same length as the vals
-
-    """
-
-    if not hasattr(vals, 'dtype'):
-        raise TypeError("must pass a ndarray-like")
-
-    if hash_key is None:
-        hash_key = _default_hash_key
-
-    # For categoricals, we hash the categories, then remap the codes to the
-    # hash values. (This check is above the complex check so that we don't ask
-    # numpy if categorical is a subdtype of complex, as it will choke.
-    if is_categorical_dtype(vals.dtype):
-        return _hash_categorical(vals, encoding, hash_key)
-
-    # we'll be working with everything as 64-bit values, so handle this
-    # 128-bit value early
-    if np.issubdtype(vals.dtype, np.complex128):
-        return hash_array(vals.real) + 23 * hash_array(vals.imag)
-
-    # First, turn whatever array this is into unsigned 64-bit ints, if we can
-    # manage it.
-    if is_bool_array(vals):
-        vals = vals.astype('u8')
-    elif (is_datetime64_dtype(vals) or
-          is_timedelta64_dtype(vals)):
-        vals = vals.view('i8').astype('u8', copy=False)
-    elif (is_numeric_dtype(vals) and vals.dtype.itemsize <= 8):
-        vals = vals.view('u{}'.format(vals.dtype.itemsize)).astype('u8')
-    else:
-        # With repeated values, its MUCH faster to categorize object dtypes,
-        # then hash and rename categories. We allow skipping the categorization
-        # when the values are known/likely to be unique.
-        if categorize:
-            codes, categories = factorize(vals, sort=False)
-            cat = Categorical(codes, Index(categories),
-                              ordered=False, fastpath=True)
-            return _hash_categorical(cat, encoding, hash_key)
-
-        try:
-            vals = _hash.hash_object_array(vals, hash_key, encoding)
-        except TypeError:
-            # we have mixed types
-            vals = _hash.hash_object_array(vals.astype(str).astype(object),
-                                           hash_key, encoding)
-
-    # Then, redistribute these 64-bit ints within the space of 64-bit ints
-    vals ^= vals >> 30
-    vals *= np.uint64(0xbf58476d1ce4e5b9)
-    vals ^= vals >> 27
-    vals *= np.uint64(0x94d049bb133111eb)
-    vals ^= vals >> 31
-    return vals
+    setattr(m, t, outer(t))
diff --git a/pandas/util/testing.py b/pandas/util/testing.py
index 354e11ce0133a5..307dbeb0665e41 100644
--- a/pandas/util/testing.py
+++ b/pandas/util/testing.py
@@ -48,7 +48,7 @@
                     Index, MultiIndex,
                     Series, DataFrame, Panel, Panel4D)
 
-from pandas.util import libtesting
+from pandas.util import _testing
 from pandas.io.common import urlopen
 try:
     import pytest
@@ -184,7 +184,7 @@ def assert_almost_equal(left, right, check_exact=False,
                 else:
                     obj = 'Input'
                 assert_class_equal(left, right, obj=obj)
-        return libtesting.assert_almost_equal(
+        return _testing.assert_almost_equal(
             left, right,
             check_dtype=check_dtype,
             check_less_precise=check_less_precise,
@@ -220,7 +220,7 @@ def _check_isinstance(left, right, cls):
 def assert_dict_equal(left, right, compare_keys=True):
 
     _check_isinstance(left, right, dict)
-    return libtesting.assert_dict_equal(left, right, compare_keys=compare_keys)
+    return _testing.assert_dict_equal(left, right, compare_keys=compare_keys)
 
 
 def randbool(size=(), p=0.5):
@@ -937,10 +937,10 @@ def _get_ilevel_values(index, level):
                 .format(obj, np.round(diff, 5))
             raise_assert_detail(obj, msg, left, right)
     else:
-        libtesting.assert_almost_equal(left.values, right.values,
-                                       check_less_precise=check_less_precise,
-                                       check_dtype=exact,
-                                       obj=obj, lobj=left, robj=right)
+        _testing.assert_almost_equal(left.values, right.values,
+                                     check_less_precise=check_less_precise,
+                                     check_dtype=exact,
+                                     obj=obj, lobj=left, robj=right)
 
     # metadata comparison
     if check_names:
@@ -1273,10 +1273,10 @@ def assert_series_equal(left, right, check_dtype=True,
         assert_index_equal(l, r, obj='{0}.index'.format(obj))
 
     else:
-        libtesting.assert_almost_equal(left.get_values(), right.get_values(),
-                                       check_less_precise=check_less_precise,
-                                       check_dtype=check_dtype,
-                                       obj='{0}'.format(obj))
+        _testing.assert_almost_equal(left.get_values(), right.get_values(),
+                                     check_less_precise=check_less_precise,
+                                     check_dtype=check_dtype,
+                                     obj='{0}'.format(obj))
 
     # metadata comparison
     if check_names:
diff --git a/setup.py b/setup.py
index 6f3ddbe2ad9d0e..51aacf5e0b8455 100755
--- a/setup.py
+++ b/setup.py
@@ -116,7 +116,7 @@ def is_platform_mac():
     'join': ['_libs/join_helper.pxi.in', '_libs/join_func_helper.pxi.in'],
     'reshape': ['_libs/reshape_helper.pxi.in'],
     'hashtable': ['_libs/hashtable_class_helper.pxi.in',
-                   '_libs/hashtable_func_helper.pxi.in'],
+                  '_libs/hashtable_func_helper.pxi.in'],
     'index': ['_libs/index_class_helper.pxi.in'],
     'sparse': ['core/sparse/sparse_op_helper.pxi.in'],
     'interval': ['_libs/intervaltree.pxi.in']
@@ -337,10 +337,10 @@ class CheckSDist(sdist_class):
                  'pandas/_libs/algos.pyx',
                  'pandas/_libs/join.pyx',
                  'pandas/_libs/interval.pyx',
+                 'pandas/_libs/hashing.pyx',
                  'pandas/core/window.pyx',
                  'pandas/core/sparse/sparse.pyx',
-                 'pandas/util/testing.pyx',
-                 'pandas/tools/hash.pyx',
+                 'pandas/util/_testing.pyx',
                  'pandas/io/parsers.pyx',
                  'pandas/io/sas/sas.pyx']
 
@@ -526,10 +526,10 @@ def pxd(name):
     'core.sparse.libsparse': {'pyxfile': 'core/sparse/sparse',
                               'depends': (['pandas/core/sparse/sparse.pyx'] +
                                      _pxi_dep['sparse'])},
-    'util.libtesting': {'pyxfile': 'util/testing',
-                        'depends': ['pandas/util/testing.pyx']},
-    'util.libhashing': {'pyxfile': 'util/hashing',
-                        'depends': ['pandas/util/hashing.pyx']},
+    'util._testing': {'pyxfile': 'util/_testing',
+                      'depends': ['pandas/util/_testing.pyx']},
+    '_libs.hashing': {'pyxfile': '_libs/hashing',
+                      'depends': ['pandas/_libs/hashing.pyx']},
     'io.sas.libsas': {'pyxfile': 'io/sas/sas'},
     }
 
@@ -645,6 +645,7 @@ def pxd(name):
                 'pandas.core.reshape',
                 'pandas.core.sparse',
                 'pandas.core.tools',
+                'pandas.core.util',
                 'pandas.computation',
                 'pandas.errors',
                 'pandas.io',
@@ -652,6 +653,7 @@ def pxd(name):
                 'pandas.io.sas',
                 'pandas.io.msgpack',
                 'pandas.io.formats',
+                'pandas.io.clipboard',
                 'pandas._libs',
                 'pandas.plotting',
                 'pandas.stats',
@@ -679,9 +681,9 @@ def pxd(name):
                 'pandas.tests.tseries',
                 'pandas.tests.plotting',
                 'pandas.tests.tools',
+                'pandas.tests.util',
                 'pandas.tools',
                 'pandas.tseries',
-                'pandas.util.clipboard'
                 ],
       package_data={'pandas.tests': ['data/*.csv'],
                     'pandas.tests.indexes': ['data/*.pickle'],