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CLN: Index imports and 0.23.1 whatsnew #21490

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Jun 15, 2018
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CLN: Index imports and 0.23.1 whatsnew #21490

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8 changes: 4 additions & 4 deletions doc/source/whatsnew/v0.23.1.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -97,8 +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 :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**
Expand All @@ -110,12 +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**

Expand Down
14 changes: 6 additions & 8 deletions pandas/core/indexes/base.py
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Expand Up @@ -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):
Expand All @@ -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)
Expand Down Expand Up @@ -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':
Expand Down Expand Up @@ -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,
Expand Down Expand Up @@ -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':
Expand Down