CLN: Fix typo
BUG: {expanding,rolling}_{cov,corr} don't handle arguments with different index sets properly
ENH: change BlockManager pickle format to work with dup items
Merge pull request #7370 from immerrr/blockmanager-new-pickle-format

ENH: change BlockManager pickle format to work with dup items
Merge pull request #7604 from seth-p/moments_diff_index_sets

BUG: {expanding,rolling}_{cov,corr} don't handle arguments with different index sets properly
Merge pull request #7624 from bwignall/quickfix_depr

CLN: Fix typo
PERF: optimize MultiIndex.from_product for large iterables
Merge pull request #7627 from immerrr/perf-multiindex-fromproduct

PERF: optimize MultiIndex.from_product
WIP: categoricals as an internal CategoricalBlock GH5313

Categorical: add new constructor mode

Catgoricals: implement min/max/sort

CLN: integrate JanSchulz changes
     change _value_pointer back to labels

BUG: fix up PeriodIndex formatting/printing
API: Categorical sort api backwarks - now conform to Series interface (order returns a copy, sort is inplace)

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

more min/max tests for categorical as a pd.Series

Add Categorical Properties to Series

's.levels' and 's.ordered' are passed through to the underlying
Categorical instance.

Default to 'ordered' Categoricals if values are orderd

R defaults to ordered factors if the input values are ordered. Do
the same. Change the unittests accordingly.

Also reordere some unittests: catgoricals tested as is and tested as
Series/Dataframes belong to different classes.

Test that Series.ordered/.levels only works on Categorical types

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

Add the possibility to change the levels (including longer and shorter levels).

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.

Do some refactorings and use a faster version in case values + levels are
passed in at creation time.

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: Rename fast_path to fastpath

Categorical: Use fastpath in some cases

Categorical: Add mode testcases for Categorical

Categorical: implement remove_unused_levels()

Both implemented in Categorical and Series

Categorical: implement value_count() for categorical series

Categorical: new examples in Categorical docstring

Categorical: Use fastpath in internal code

Categorical: check that categoricals in dataframes are also not compressed in groupby

Categorical: add `Categorical(cat)` constructor codepath and tests

Categorical: First version to fix groupby with categoricals

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

Categorical: Add failing testcase due to sideeffects

Categorical: NaNs handling in init

Categorical: new doc versions

remove Series accessors in favor of using .cat
added some FIXME sections to some failing tests

TST: infer correctly a multi-level index of pd.NaT and Timestamp

PERF: perf issue with indexing

Categorical: add better check for categorical in Series.cat

Categorical: doc changes

Categorical: New (failing!) unittests for slicing

API: removed need for ndim changing in Categoricals

TST: fime tests in Categorical slicing/indexing

Categorical: additional (failing) slicing testcases

Categorical: testcase: groupby based on categorical should result in categorical index

Categorical: first version of assigning testcases (failing)

BUG: fix slicing issues

ENH: add setitem to Categorical

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

BUG: side effects now tested / work correcty

BUG: require identical level set when setting

BUG: fixup groupby tests for size/count

CLN: CategoricalDtype was returning itself in dtype, causing recursing loops
BUG: side effects test should use is and not hash comparison

TST: fix groupby_sort tests

Categorical: More assigning unittests

ERR: improved error messages for Series numeric ops with Categoricals

API: disallow numpy ufuncs with categoricals

Categorical: Categorical assignment to int/obj column

Categorical: more failing tests and some tests

Categorical: new version of the docs

.gitignore: include temp file from docbuilding (win specific)
API: changed newstyle -> compat in constructor

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

Categorical: add docstrings to Categorical methods

Categorical: Add more (failing) unittests

Categorical: document API methods in api doc

Categorical: New doc version

Categorical: doc updates (mostly numpydoc changes)

Categorical: new (failing) tests for sorting a categorical in a dataframe

Categorical: document apply behaviour

Categorical: Implement 'numeric_only' for min/max

Categorical: Add (failing) tests for df.append(..)

Categorical: (failing) tests for to_csv and to_hdf

Categorical: clearer example of apply problem

Categorical: add some io tests and documentation

Categorical: add public accessor for the level codes

Categorical: rename ._level_code to ._code

fixup from rebase

BUG: reordering levels that are not in the original set now raises ValueError

BUG: fix dataframe sorting by categoricals

TST: append was working ok

ENH/BUG: fix describe to work correctly (and return all levels)

BUG: update MultiIndex.from_product for Categorical change

Categorical: Fixup some missing merge leftovers