SQL: don't reflect full database GH7396
FIX: don't create 32 bit int type for int64 column (GH7433)
API: disallow inplace setting with where and a non-np.nan value (GH7656)
Merge pull request #7657 from jreback/where

API: disallow inplace setting with where and a non-np.nan value (GH7656)
BUG: DatetimeIndex.delete with tz raises ValueError
Merge pull request #7608 from sinhrks/delete2

BUG: DatetimeIndex.delete with tz raises ValueError
BUG: Bug in multi-index slice setting, related GH3738
Merge pull request #7667 from jreback/mi_slicing

BUG: Bug in multi-index slice setting, related GH3738
BUG: windows failure on GH7667
Merge pull request #7668 from pydata/mi_slicing2

BUG: windows failure on GH7667
BUG: area plot raises ValueError with tz-aware data
Merge pull request #7515 from sinhrks/areabug

BUG: area plot raises ValueError with tz-aware data
Update docs to use display.width instead of deprecated line_width.
Merge pull request #7669 from lexual/docs_use_display_width

Update docs to use display.width instead of deprecated line_width.
CLN: Simplify Period construction / Resolution
Merge pull request #7634 from jorisvandenbossche/sql-int64

FIX: don't create 32 bit int type for int64 column (GH7433)
Merge pull request #7581 from jorisvandenbossche/sql-reflect-database

SQL: don't reflect full database GH7396
CI: update sqlalchemy to 0.9.6 in 3.4 build
Merge pull request #7607 from sinhrks/millireso

CLN: Simplify Period Construction / Resolution
ENH: upgrade categoricals to a first class pandas type
     GH3943, GH5313, GH5314, GH7444

ENH: delegate _reduction and ops from Series to the categorical
     to support min/max and raise TypeError on other ops (numerical) and reduction

Add Categorical Properties to Series

Default to 'ordered' Categoricals if values are ordered

Categorical: add level assignments and reordering + changed default for ordered

Add a `Categorical.reorder_levels()` method. Change some naming in `Series`,
so that the methods do not clash with established standards and rename the
other categorical methods accordingly.

Also change the default for `ordered` to True if values + levels are passed
in at creation time.

Initial doc version for working with Categorical data

Categorical: add Categorical.mode() and use that in Series.mode()

Categorical: implement remove_unused_levels()

Categorical: implement value_count() for categorical series

Categorical: make Series.astype("category") work

ENH: add setitem to Categorical

BUG: assigning to levels not in level set now raises ValueError

API: disallow numpy ufuncs with categoricals

Categorical: Categorical assignment to int/obj column

ENH: add support for fillna to Categoricals

API: deprecate old style categorical constructor usage and change default

Before it was possible to pass in precomputed labels/pointer and the
corresponding levels (e.g.: `Categorical([0,1,2], levels=["a","b","c"])`).

This could lead to subtle errors in case of integer categoricals: the
following could be both interpreted as "precomputed pointers and
levels" or "values and levels", but converting it back to a integer
array would result in different arrays:

`np.array(Categorical([1,2], levels=[1,2,3]))`
interpreted as pointers: `[2,3]`
interpreted as values: `[1,2]`

Up to now we would favour old style "pointer and levels" if these
values could be interpreted as such (see code for details...). With
this commit we favour new style "values and levels" and only attempt
to interprete them as "pointers and levels" if "compat=True" is passed
to the constructor.

BREAKS: This will break code which uses Categoricals with "pointer and
levels". A short google search and a search on stackoverflow revealed
no such useage.

Categorical: document constructor changes and small fixes

Categorical: document that inappropriate numpy functions won't work anymore

ENH: concat support