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
 

pandas/core/common.py

@@ -13,12 +13,12 @@
 from pandas import compat
 from pandas.compat import long, zip, iteritems
 from pandas.core.config import get_option
-from pandas.types.generic import ABCSeries
-from pandas.types.common import _NS_DTYPE
-from pandas.types.inference import _iterable_not_string
-from pandas.types.missing import isnull
+from pandas.core.types.generic import ABCSeries
+from pandas.core.types.common import _NS_DTYPE
+from pandas.core.types.inference import _iterable_not_string
+from pandas.core.types.missing import isnull
 from pandas.api import types
-from pandas.types import common
+from pandas.core.types import common
 
 # compat
 from pandas.errors import (  # noqa
@@ -60,7 +60,7 @@ def wrapper(*args, **kwargs):
             warnings.warn("pandas.core.common.{t} is deprecated. "
                           "These are not longer public API functions, "
                           "but can be imported from "
-                          "pandas.types.common.{t} instead".format(t=t),
+                          "pandas.core.types.common.{t} instead".format(t=t),
                           DeprecationWarning, stacklevel=3)
             return getattr(common, t)(*args, **kwargs)
         return wrapper
@@ -73,7 +73,7 @@ def wrapper(*args, **kwargs):
 def array_equivalent(*args, **kwargs):
     warnings.warn("'pandas.core.common.array_equivalent' is deprecated and "
                   "is no longer public API", DeprecationWarning, stacklevel=2)
-    from pandas.types import missing
+    from pandas.core.types import missing
     return missing.array_equivalent(*args, **kwargs)
 
 

pandas/core/config_init.py

@@ -415,7 +415,7 @@ def mpl_style_cb(key):
 
 
 def use_inf_as_null_cb(key):
-    from pandas.types.missing import _use_inf_as_null
+    from pandas.core.types.missing import _use_inf_as_null
     _use_inf_as_null(key)
 
 

pandas/core/frame.py

@@ -23,38 +23,40 @@
 import numpy as np
 import numpy.ma as ma
 
-from pandas.types.cast import (maybe_upcast, infer_dtype_from_scalar,
-                               maybe_cast_to_datetime,
-                               maybe_infer_to_datetimelike,
-                               maybe_convert_platform,
-                               maybe_downcast_to_dtype,
-                               invalidate_string_dtypes,
-                               coerce_to_dtypes,
-                               maybe_upcast_putmask,
-                               find_common_type)
-from pandas.types.common import (is_categorical_dtype,
-                                 is_object_dtype,
-                                 is_extension_type,
-                                 is_datetimetz,
-                                 is_datetime64_any_dtype,
-                                 is_datetime64tz_dtype,
-                                 is_bool_dtype,
-                                 is_integer_dtype,
-                                 is_float_dtype,
-                                 is_integer,
-                                 is_scalar,
-                                 is_dtype_equal,
-                                 needs_i8_conversion,
-                                 _get_dtype_from_object,
-                                 _ensure_float,
-                                 _ensure_float64,
-                                 _ensure_int64,
-                                 _ensure_platform_int,
-                                 is_list_like,
-                                 is_iterator,
-                                 is_sequence,
-                                 is_named_tuple)
-from pandas.types.missing import isnull, notnull
+from pandas.core.types.cast import (
+    maybe_upcast, infer_dtype_from_scalar,
+    maybe_cast_to_datetime,
+    maybe_infer_to_datetimelike,
+    maybe_convert_platform,
+    maybe_downcast_to_dtype,
+    invalidate_string_dtypes,
+    coerce_to_dtypes,
+    maybe_upcast_putmask,
+    find_common_type)
+from pandas.core.types.common import (
+    is_categorical_dtype,
+    is_object_dtype,
+    is_extension_type,
+    is_datetimetz,
+    is_datetime64_any_dtype,
+    is_datetime64tz_dtype,
+    is_bool_dtype,
+    is_integer_dtype,
+    is_float_dtype,
+    is_integer,
+    is_scalar,
+    is_dtype_equal,
+    needs_i8_conversion,
+    _get_dtype_from_object,
+    _ensure_float,
+    _ensure_float64,
+    _ensure_int64,
+    _ensure_platform_int,
+    is_list_like,
+    is_iterator,
+    is_sequence,
+    is_named_tuple)
+from pandas.core.types.missing import isnull, notnull
 
 from pandas.core.common import (_try_sort,
                                 _default_index,

pandas/core/generic.py

@@ -10,22 +10,23 @@
 import pandas as pd
 
 from pandas._libs import tslib, lib
-from pandas.types.common import (_coerce_to_dtype,
-                                 _ensure_int64,
-                                 needs_i8_conversion,
-                                 is_scalar,
-                                 is_integer, is_bool,
-                                 is_bool_dtype,
-                                 is_numeric_dtype,
-                                 is_datetime64_dtype,
-                                 is_timedelta64_dtype,
-                                 is_datetime64tz_dtype,
-                                 is_list_like,
-                                 is_dict_like,
-                                 is_re_compilable)
-from pandas.types.cast import maybe_promote, maybe_upcast_putmask
-from pandas.types.missing import isnull, notnull
-from pandas.types.generic import ABCSeries, ABCPanel
+from pandas.core.types.common import (
+    _coerce_to_dtype,
+    _ensure_int64,
+    needs_i8_conversion,
+    is_scalar,
+    is_integer, is_bool,
+    is_bool_dtype,
+    is_numeric_dtype,
+    is_datetime64_dtype,
+    is_timedelta64_dtype,
+    is_datetime64tz_dtype,
+    is_list_like,
+    is_dict_like,
+    is_re_compilable)
+from pandas.core.types.cast import maybe_promote, maybe_upcast_putmask
+from pandas.core.types.missing import isnull, notnull
+from pandas.core.types.generic import ABCSeries, ABCPanel
 
 from pandas.core.common import (_values_from_object,
                                 _maybe_box_datetimelike,

pandas/core/groupby.py

@@ -15,26 +15,27 @@
 from pandas.compat.numpy import function as nv, _np_version_under1p8
 from pandas.compat import set_function_name
 
-from pandas.types.common import (is_numeric_dtype,
-                                 is_timedelta64_dtype, is_datetime64_dtype,
-                                 is_categorical_dtype,
-                                 is_interval_dtype,
-                                 is_datetimelike,
-                                 is_datetime64_any_dtype,
-                                 is_bool, is_integer_dtype,
-                                 is_complex_dtype,
-                                 is_bool_dtype,
-                                 is_scalar,
-                                 is_list_like,
-                                 needs_i8_conversion,
-                                 _ensure_float64,
-                                 _ensure_platform_int,
-                                 _ensure_int64,
-                                 _ensure_object,
-                                 _ensure_categorical,
-                                 _ensure_float)
-from pandas.types.cast import maybe_downcast_to_dtype
-from pandas.types.missing import isnull, notnull, _maybe_fill
+from pandas.core.types.common import (
+    is_numeric_dtype,
+    is_timedelta64_dtype, is_datetime64_dtype,
+    is_categorical_dtype,
+    is_interval_dtype,
+    is_datetimelike,
+    is_datetime64_any_dtype,
+    is_bool, is_integer_dtype,
+    is_complex_dtype,
+    is_bool_dtype,
+    is_scalar,
+    is_list_like,
+    needs_i8_conversion,
+    _ensure_float64,
+    _ensure_platform_int,
+    _ensure_int64,
+    _ensure_object,
+    _ensure_categorical,
+    _ensure_float)
+from pandas.core.types.cast import maybe_downcast_to_dtype
+from pandas.core.types.missing import isnull, notnull, _maybe_fill
 
 from pandas.core.common import (_values_from_object, AbstractMethodError,
                                 _default_index)
@@ -4079,7 +4080,7 @@ def _apply_to_column_groupbys(self, func):
     def count(self):
         """ Compute count of group, excluding missing values """
         from functools import partial
-        from pandas.types.missing import _isnull_ndarraylike as isnull
+        from pandas.core.types.missing import _isnull_ndarraylike as isnull
 
         data, _ = self._get_data_to_aggregate()
         ids, _, ngroups = self.grouper.group_info