additional common.is_*_dtype tests in core.common
make better use of dtype tests in nanops
Remove unused variable assignment
Add notes deprecating in_ipnb and in_qtconsole
Merge pull request #7499 from takluyver/ipy-no-detect-frontend

Deprecate detection of IPython frontends
DOC: Add cookbook recipe like R's `expand.grid()`

Add `expand_grid()` recipe to cookbook

Add note about cookbook recipe to release notes

Revert "Add note about cookbook recipe to release notes"

This reverts commit e431a024c2e688f9917cafb12235ee72ecc3e119.

Remove pandas import, print dataframe in cookbook
Merge pull request #7556 from onesandzeroes/expand-grid

DOC: Cookbook recipe for emulating R's expand.grid() (#7426)
BUG/PERF: perf issues in object groupby aggregations (GH7555)
Merge pull request #7568 from jreback/perf2

BUG/PERF: perf issues in object groupby aggregations (GH7555)
TST: Remove else after except in tests for io.data.Options.

Made the old tests consistent with the new tests, also passed the RemoteDataError on skip.

CLN:  Moved test for no tables to the get_option_tables method.
Merge pull request #7564 from dstephens99/master

TST: Remove else after except in tests for io.data.Options.
Merge pull request #7547 from toddrjen/nanopsclean

Minor cleanups for nanops
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