ENH: HDFStore enhancements

RELEASE.rst

@@ -38,6 +38,12 @@ pandas 0.11.1
   - Fixed various issues with internal pprinting code, the repr() for various objects
     including TimeStamp and *Index now produces valid python code strings and
     can be used to recreate the object, (GH3038_), (GH3379_), (GH3251_)
+  - ``HDFStore``
+
+    - will retain index attributes (freq,tz,name) on recreation (GH3499_)
+    - will warn with a FrequencyWarning if you are attempting to append
+      an index with a different frequency than the existing
+    - support datelike columns with a timezone as data_columns (GH2852_)
 
 **API Changes**
 
@@ -87,6 +93,7 @@ pandas 0.11.1
 .. _GH3251: https://github.com/pydata/pandas/issues/3251
 .. _GH3379: https://github.com/pydata/pandas/issues/3379
 .. _GH3480: https://github.com/pydata/pandas/issues/3480
+.. _GH2852: https://github.com/pydata/pandas/issues/2852
 .. _GH3454: https://github.com/pydata/pandas/issues/3454
 .. _GH3457: https://github.com/pydata/pandas/issues/3457
 .. _GH3491: https://github.com/pydata/pandas/issues/3491
@@ -102,7 +109,7 @@ pandas 0.11.1
 .. _GH3461: https://github.com/pydata/pandas/issues/3461
 .. _GH3468: https://github.com/pydata/pandas/issues/3468
 .. _GH3448: https://github.com/pydata/pandas/issues/3448
-.. _GH3449: https://github.com/pydata/pandas/issues/3449
+.. _GH3499: https://github.com/pydata/pandas/issues/3499
 .. _GH3495: https://github.com/pydata/pandas/issues/3495
 .. _GH3492: https://github.com/pydata/pandas/issues/3492
 .. _GH3493: https://github.com/pydata/pandas/issues/3493

doc/source/v0.11.1.txt

@@ -1,6 +1,6 @@
-.. _whatsnew_0120:
+.. _whatsnew_0111:
 
-v0.12.0 (??)
+v0.11.1 (??)
 ------------------------
 
 This is a major release from 0.11.0 and includes many new features and
@@ -12,13 +12,21 @@ API changes
 
 Enhancements
 ~~~~~~~~~~~~
-  - pd.read_html() can now parse HTML string, files or urls and return dataframes
+  - ``pd.read_html()`` can now parse HTML string, files or urls and return dataframes
     courtesy of @cpcloud. (GH3477_)
+  - ``HDFStore``
+
+    - will retain index attributes (freq,tz,name) on recreation (GH3499_)
+    - will warn with a FrequencyWarning if you are attempting to append
+      an index with a different frequency than the existing
+    - support datelike columns with a timezone as data_columns (GH2852_)
 
 See the `full release notes
 <https://github.com/pydata/pandas/blob/master/RELEASE.rst>`__ or issue tracker
 on GitHub for a complete list.
 
 .. _GH2437: https://github.com/pydata/pandas/issues/2437
+.. _GH2852: https://github.com/pydata/pandas/issues/2852
 .. _GH3477: https://github.com/pydata/pandas/issues/3477
 .. _GH3492: https://github.com/pydata/pandas/issues/3492
+.. _GH3499: https://github.com/pydata/pandas/issues/3499

doc/source/whatsnew.rst

@@ -18,6 +18,8 @@ These are new features and improvements of note in each release.
 
 .. include:: v0.12.0.txt
 
+.. include:: v0.11.1.txt
+
 .. include:: v0.11.0.txt
 
 .. include:: v0.10.1.txt

pandas/core/index.py

@@ -83,12 +83,12 @@ class Index(np.ndarray):
 
     _engine_type = _index.ObjectEngine
 
-    def __new__(cls, data, dtype=None, copy=False, name=None):
+    def __new__(cls, data, dtype=None, copy=False, name=None, **kwargs):
         from pandas.tseries.period import PeriodIndex
         if isinstance(data, np.ndarray):
             if issubclass(data.dtype.type, np.datetime64):
                 from pandas.tseries.index import DatetimeIndex
-                result = DatetimeIndex(data, copy=copy, name=name)
+                result = DatetimeIndex(data, copy=copy, name=name, **kwargs)
                 if dtype is not None and _o_dtype == dtype:
                     return Index(result.to_pydatetime(), dtype=_o_dtype)
                 else:
@@ -102,7 +102,7 @@ def __new__(cls, data, dtype=None, copy=False, name=None):
                 except TypeError:
                     pass
             elif isinstance(data, PeriodIndex):
-                return PeriodIndex(data, copy=copy, name=name)
+                return PeriodIndex(data, copy=copy, name=name, **kwargs)
 
             if issubclass(data.dtype.type, np.integer):
                 return Int64Index(data, copy=copy, dtype=dtype, name=name)
@@ -123,10 +123,10 @@ def __new__(cls, data, dtype=None, copy=False, name=None):
                 if (inferred.startswith('datetime') or
                         tslib.is_timestamp_array(subarr)):
                     from pandas.tseries.index import DatetimeIndex
-                    return DatetimeIndex(subarr, copy=copy, name=name)
+                    return DatetimeIndex(subarr, copy=copy, name=name, **kwargs)
 
                 elif inferred == 'period':
-                    return PeriodIndex(subarr, name=name)
+                    return PeriodIndex(subarr, name=name, **kwargs)
 
         subarr = subarr.view(cls)
         subarr.name = name