changes to HDFStore:

      1. added __str__ (to do __repr__)
      2. added __delitem__ to support store deletion syntatic sugar
      3. row removal in tables is much faster if rows are consecutive
      4. added Term class, refactored Selection (this is backwards compatible)
         Term is a concise way of specifying conditions for queries, e.g.

            Term(dict(field = 'index', op = '>', value = '20121114'))
            Term('index', '20121114')
            Term('index', '>', '20121114')
            Term('index', ['20121114','20121114'])
            Term('index', datetime(2012,11,14))
            Term('index>20121114')

            added alias to the Term class; you can specify the nomial indexers (e.g. index in DataFrame, major_axis/minor_axis or alias in Panel)

	 this should close GH #1996

      5. added Col class to manage the column conversions
      6. added min_itemsize parameter and checks in pytables to allow setting of indexer columns minimum size
      7. added indexing support via method create_table_index (requires 2.3 in PyTables)
      	 btw now works quite well as Int64 indicies are used as opposed to the Time64Col which has a bug); includes a check on the pytables version requirement

	 this should close GH #698

      8. signficantlly updated docs for pytables to reflect all changes; added docs for Table sections
      9. BUG: a store would fail if appending but the a put had not been done before (see test_append)
         this the result of incompatibility testing on the index_kind
     10. BUG: minor change to select and remove: require a table ONLY if where is also provided (and not None)

      all tests pass; tests added for new features
testing for PyTables 2.3 was incorrect (for allowing indexing support); added test to catch
Refactor of PyTables support to allow multiple table types.

  This commit allows for support of multiple table types in a pytables hdf file,
  supporting the existing infrastructure in a backwards compatible manner (LegacyTable)
  while extending to a slightly modified format to support AppendableTables and future support of WORMTables

  AppendableTables are implementations of the current table format with two enhancements:
     1) mixed dtype support
     2) writing routines in cython for enhanced performance

  WORMTables (not implemented - but pretty straightforward)
    these tables can support a fixed 'table' (meaning not-appendable), that is searchable via queries
    this would have greatly enhanced write performance compared with AppendableTables, and a similar read performance profile

  In addition, the tables allow for arbitrary axes to be indexed (e.g. you could save a panel that allows indexing on major_axis,minor_axis AND items),
    so all dimensions are queryable (currently only major/minor axes allow this query)

  all tests pass (with 1 exception)
    a frame table round-trip - we fail on a comparison of a sorted index of the frame vs the index of the table (which is as written), not sure why this should be the case?
minor doc changes to reflect v4
Merge branch 'master' of https://github.com/jreback/pandas into pytablesv4
Merge branch 'master' of git://github.com/pydata/pandas into pytablesv4
update v0.10.0 whatsnew docs for PyTables Table features
added additional test cases for Terms in test_pytables.py
subtle change to parsing order in Terms (e.g. '<=' would only cause '<' to be picked up)
updated whatsnew with list of bugs/enhancements for pytablesv4
BUG: fix time zone handling in union between non-overlapping DatetimeIndex. close #2367
BUG: raise OverflowError on integer values exceeding int64 precision in parsers. close #2247
TST: make sort default to False in merge
BLD: add travis 3.3 environment, allow fail for now
VB: add tool to measure per benchmark memory consumption (experimental)
BLD: add vbench based util for benchmarking the current head into a gist
BLD: add a 2.7 vbench build to the travis build matrix

a seperate job is spawned, which is allowed to fail without
failing the entire build.
the results are posted to a public gist as a json file.

helper functions in vb_suite/perf_HEAD.py accept a travis
build number, locate the VBENCH job, fetch the log through
the Travis API, extract the gist raw_url, fetch the results
and decode the json into a dict and then a pandas dataframe.
FTW.

It remains to be seen whether the results are consistent
enough between builds over time to make this useful.
ENH: configurability of boolean value indicators. true_values/false_values arguments to read_csv/table. close #2360
BUG: fix python 3.2 bytes issue
update RELEAST.rst for v0.10.0 for HDFStore changes
BLD: fix travis.yml, print is a function in 3.x
Merge pull request #2375 from y-p/fix1

BLD: fix travis.yml, print is a function in 3.x