CLN: move pandas.types -> pandas.core.types

xref #13634

Author: jreback

asv_bench/benchmarks/categoricals.py

@@ -1,6 +1,6 @@
 from .pandas_vb_common import *
 try:
-    from pandas.types.concat import union_categoricals
+    from pandas.core.types.concat import union_categoricals
 except ImportError:
     pass
 

doc/source/whatsnew/v0.20.0.txt

@@ -1000,12 +1000,13 @@ New Behavior:
    In [11]: index.memory_usage(deep=True)
    Out[11]: 260
 
-.. _whatsnew_0200.api_breaking.extensions:
+.. _whatsnew_0200.api_breaking.privacy:
 
-Extension Modules Moved
-^^^^^^^^^^^^^^^^^^^^^^^
+Modules Privacy Has Changed
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Some formerly public c/c++/cython extension modules have been moved and/or renamed. These are all removed from the public API.
+Some formerly public python/c/c++/cython extension modules have been moved and/or renamed. These are all removed from the public API.
+Further more, the ``pandas.core``, ``pandas.io``, and ``pandas.util`` top-level modules are now considered to be PRIVATE.
 If indicated, a deprecation warning will be issued if you reference that module. (:issue:`12588`)
 
 .. csv-table::
@@ -1022,6 +1023,7 @@ If indicated, a deprecation warning will be issued if you reference that module.
     "pandas.hashtable", "pandas._libs.hashtable", ""
     "pandas.json", "pandas.io.json.libjson", "X"
     "pandas.parser", "pandas.io.libparsers", "X"
+    "pandas.types", "pandas.core.types", ""
     "pandas.io.sas.saslib", "pandas.io.sas.libsas", ""
     "pandas._testing", "pandas.util.libtesting", ""
     "pandas._sparse", "pandas.sparse.libsparse", ""

pandas/api/types/__init__.py

@@ -1,4 +1,4 @@
 """ public toolkit API """
 
-from pandas.types.api import *  # noqa
+from pandas.core.types.api import *  # noqa
 del np  # noqa

pandas/compat/numpy/function.py

@@ -22,7 +22,7 @@
 from pandas.util.validators import (validate_args, validate_kwargs,
                                     validate_args_and_kwargs)
 from pandas.errors import UnsupportedFunctionCall
-from pandas.types.common import is_integer, is_bool
+from pandas.core.types.common import is_integer, is_bool
 from pandas.compat import OrderedDict
 
 

pandas/computation/ops.py

@@ -7,7 +7,7 @@
 
 import numpy as np
 
-from pandas.types.common import is_list_like, is_scalar
+from pandas.core.types.common import is_list_like, is_scalar
 import pandas as pd
 from pandas.compat import PY3, string_types, text_type
 import pandas.core.common as com

pandas/computation/pytables.py

@@ -5,7 +5,7 @@
 import numpy as np
 import pandas as pd
 
-from pandas.types.common import is_list_like
+from pandas.core.types.common import is_list_like
 import pandas.core.common as com
 from pandas.compat import u, string_types, DeepChainMap
 from pandas.core.base import StringMixin

pandas/core/algorithms.py

@@ -7,10 +7,11 @@
 import numpy as np
 
 from pandas import compat, _np_version_under1p8
-from pandas.types.cast import maybe_promote
-from pandas.types.generic import (ABCSeries, ABCIndex,
-                                  ABCIndexClass, ABCCategorical)
-from pandas.types.common import (
+from pandas.core.types.cast import maybe_promote
+from pandas.core.types.generic import (
+    ABCSeries, ABCIndex,
+    ABCIndexClass, ABCCategorical)
+from pandas.core.types.common import (
     is_unsigned_integer_dtype, is_signed_integer_dtype,
     is_integer_dtype, is_complex_dtype,
     is_categorical_dtype, is_sparse,
@@ -25,7 +26,7 @@
     _ensure_float64, _ensure_uint64,
     _ensure_int64)
 from pandas.compat.numpy import _np_version_under1p10
-from pandas.types.missing import isnull
+from pandas.core.types.missing import isnull
 
 import pandas.core.common as com
 from pandas.compat import string_types

pandas/core/api.py

@@ -5,7 +5,7 @@
 import numpy as np
 
 from pandas.core.algorithms import factorize, unique, value_counts
-from pandas.types.missing import isnull, notnull
+from pandas.core.types.missing import isnull, notnull
 from pandas.core.categorical import Categorical
 from pandas.core.groupby import Grouper
 from pandas.formats.format import set_eng_float_format

pandas/core/base.py

@@ -6,9 +6,9 @@
 from pandas.compat import builtins
 import numpy as np
 
-from pandas.types.missing import isnull
-from pandas.types.generic import ABCDataFrame, ABCSeries, ABCIndexClass
-from pandas.types.common import is_object_dtype, is_list_like, is_scalar
+from pandas.core.types.missing import isnull
+from pandas.core.types.generic import ABCDataFrame, ABCSeries, ABCIndexClass
+from pandas.core.types.common import is_object_dtype, is_list_like, is_scalar
 from pandas.util.validators import validate_bool_kwarg
 
 from pandas.core import common as com
@@ -725,7 +725,7 @@ def _aggregate_multiple_funcs(self, arg, _level, _axis):
             # we are concatting non-NDFrame objects,
             # e.g. a list of scalars
 
-            from pandas.types.cast import is_nested_object
+            from pandas.core.types.cast import is_nested_object
             from pandas import Series
             result = Series(results, index=keys, name=self.name)
             if is_nested_object(result):

pandas/core/categorical.py

@@ -8,21 +8,24 @@
 from pandas.compat import u, lzip
 from pandas._libs import lib, algos as libalgos
 
-from pandas.types.generic import ABCSeries, ABCIndexClass, ABCCategoricalIndex
-from pandas.types.missing import isnull, notnull
-from pandas.types.cast import (maybe_infer_to_datetimelike,
-                               coerce_indexer_dtype)
-from pandas.types.dtypes import CategoricalDtype
-from pandas.types.common import (_ensure_int64,
-                                 _ensure_object,
-                                 _ensure_platform_int,
-                                 is_dtype_equal,
-                                 is_datetimelike,
-                                 is_categorical,
-                                 is_categorical_dtype,
-                                 is_integer_dtype, is_bool,
-                                 is_list_like, is_sequence,
-                                 is_scalar)
+from pandas.core.types.generic import (
+    ABCSeries, ABCIndexClass, ABCCategoricalIndex)
+from pandas.core.types.missing import isnull, notnull
+from pandas.core.types.cast import (
+    maybe_infer_to_datetimelike,
+    coerce_indexer_dtype)
+from pandas.core.types.dtypes import CategoricalDtype
+from pandas.core.types.common import (
+    _ensure_int64,
+    _ensure_object,
+    _ensure_platform_int,
+    is_dtype_equal,
+    is_datetimelike,
+    is_categorical,
+    is_categorical_dtype,
+    is_integer_dtype, is_bool,
+    is_list_like, is_sequence,
+    is_scalar)
 from pandas.core.common import is_null_slice
 
 from pandas.core.algorithms import factorize, take_1d, unique1d
@@ -1215,7 +1218,7 @@ def value_counts(self, dropna=True):
 
         """
         from numpy import bincount
-        from pandas.types.missing import isnull
+        from pandas.core.types.missing import isnull
         from pandas.core.series import Series
         from pandas.core.index import CategoricalIndex