CLN: Index imports and 0.23.1 whatsnew (pandas-dev#21490)

Author: mroeschke

doc/source/whatsnew/v0.23.1.txt

@@ -97,9 +97,8 @@ Bug Fixes
 
 **Data-type specific**
 
-- Bug in :meth:`Series.str.replace()` where the method throws `TypeError` on Python 3.5.2 (:issue: `21078`)
-- Bug in :class:`Timedelta`: where passing a float with a unit would prematurely round the float precision (:issue: `14156`)
-- Bug in :class:`Timedelta`: where passing a string of a pure number would not take unit into account. Also raises for ambiguous/duplicate unit specification (:issue: `12136`)
+- Bug in :meth:`Series.str.replace()` where the method throws `TypeError` on Python 3.5.2 (:issue:`21078`)
+- Bug in :class:`Timedelta` where passing a float with a unit would prematurely round the float precision (:issue:`14156`)
 - Bug in :func:`pandas.testing.assert_index_equal` which raised ``AssertionError`` incorrectly, when comparing two :class:`CategoricalIndex` objects with param ``check_categorical=False`` (:issue:`19776`)
 
 **Sparse**
@@ -111,12 +110,12 @@ Bug Fixes
 - Bug in :meth:`Series.reset_index` where appropriate error was not raised with an invalid level name (:issue:`20925`)
 - Bug in :func:`interval_range` when ``start``/``periods`` or ``end``/``periods`` are specified with float ``start`` or ``end`` (:issue:`21161`)
 - Bug in :meth:`MultiIndex.set_names` where error raised for a ``MultiIndex`` with ``nlevels == 1`` (:issue:`21149`)
-- Bug in :class:`IntervalIndex` constructors where creating an ``IntervalIndex`` from categorical data was not fully supported (:issue:`21243`, issue:`21253`)
+- Bug in :class:`IntervalIndex` constructors where creating an ``IntervalIndex`` from categorical data was not fully supported (:issue:`21243`, :issue:`21253`)
 - Bug in :meth:`MultiIndex.sort_index` which was not guaranteed to sort correctly with ``level=1``; this was also causing data misalignment in particular :meth:`DataFrame.stack` operations (:issue:`20994`, :issue:`20945`, :issue:`21052`)
 
 **Plotting**
 
-- New keywords (sharex, sharey) to turn on/off sharing of x/y-axis by subplots generated with pandas.DataFrame().groupby().boxplot() (:issue: `20968`)
+- New keywords (sharex, sharey) to turn on/off sharing of x/y-axis by subplots generated with pandas.DataFrame().groupby().boxplot() (:issue:`20968`)
 
 **I/O**
 

pandas/core/indexes/base.py

@@ -283,7 +283,7 @@ def __new__(cls, data=None, dtype=None, copy=False, name=None,
             if (is_datetime64_any_dtype(data) or
                 (dtype is not None and is_datetime64_any_dtype(dtype)) or
                     'tz' in kwargs):
-                from pandas.core.indexes.datetimes import DatetimeIndex
+                from pandas import DatetimeIndex
                 result = DatetimeIndex(data, copy=copy, name=name,
                                        dtype=dtype, **kwargs)
                 if dtype is not None and is_dtype_equal(_o_dtype, dtype):
@@ -293,7 +293,7 @@ def __new__(cls, data=None, dtype=None, copy=False, name=None,
 
             elif (is_timedelta64_dtype(data) or
                   (dtype is not None and is_timedelta64_dtype(dtype))):
-                from pandas.core.indexes.timedeltas import TimedeltaIndex
+                from pandas import TimedeltaIndex
                 result = TimedeltaIndex(data, copy=copy, name=name, **kwargs)
                 if dtype is not None and _o_dtype == dtype:
                     return Index(result.to_pytimedelta(), dtype=_o_dtype)
@@ -404,17 +404,15 @@ def __new__(cls, data=None, dtype=None, copy=False, name=None,
                         if (lib.is_datetime_with_singletz_array(subarr) or
                                 'tz' in kwargs):
                             # only when subarr has the same tz
-                            from pandas.core.indexes.datetimes import (
-                                DatetimeIndex)
+                            from pandas import DatetimeIndex
                             try:
                                 return DatetimeIndex(subarr, copy=copy,
                                                      name=name, **kwargs)
                             except libts.OutOfBoundsDatetime:
                                 pass
 
                     elif inferred.startswith('timedelta'):
-                        from pandas.core.indexes.timedeltas import (
-                            TimedeltaIndex)
+                        from pandas import TimedeltaIndex
                         return TimedeltaIndex(subarr, copy=copy, name=name,
                                               **kwargs)
                     elif inferred == 'period':
@@ -1177,7 +1175,7 @@ def astype(self, dtype, copy=True):
                                     copy=copy)
         try:
             if is_datetime64tz_dtype(dtype):
-                from pandas.core.indexes.datetimes import DatetimeIndex
+                from pandas import DatetimeIndex
                 return DatetimeIndex(self.values, name=self.name, dtype=dtype,
                                      copy=copy)
             return Index(self.values.astype(dtype, copy=copy), name=self.name,
@@ -3333,7 +3331,7 @@ def get_indexer_for(self, target, **kwargs):
 
     def _maybe_promote(self, other):
         # A hack, but it works
-        from pandas.core.indexes.datetimes import DatetimeIndex
+        from pandas import DatetimeIndex
         if self.inferred_type == 'date' and isinstance(other, DatetimeIndex):
             return DatetimeIndex(self), other
         elif self.inferred_type == 'boolean':