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v0.15.2.txt
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.. _whatsnew_0152:
v0.15.2 (December ??, 2014)
---------------------------
This is a minor release from 0.15.1 and includes a small number of API changes, several new features,
enhancements, and performance improvements along with a large number of bug fixes. We recommend that all
users upgrade to this version.
- Highlights include:
- :ref:`Enhancements <whatsnew_0152.enhancements>`
- :ref:`API Changes <whatsnew_0152.api>`
- :ref:`Performance Improvements <whatsnew_0152.performance>`
- :ref:`Experimental Changes <whatsnew_0152.experimental>`
- :ref:`Bug Fixes <whatsnew_0152.bug_fixes>`
.. _whatsnew_0152.api:
API changes
~~~~~~~~~~~
- Indexing in ``MultiIndex`` beyond lex-sort depth is now supported, though
a lexically sorted index will have a better performance. (:issue:`2646`)
.. ipython:: python
df = pd.DataFrame({'jim':[0, 0, 1, 1],
'joe':['x', 'x', 'z', 'y'],
'jolie':np.random.rand(4)}).set_index(['jim', 'joe'])
df
df.index.lexsort_depth
# in prior versions this would raise a KeyError
# will now show a PerformanceWarning
df.loc[(1, 'z')]
# lexically sorting
df2 = df.sortlevel()
df2
df2.index.lexsort_depth
df2.loc[(1,'z')]
- Bug in concat of Series with ``category`` dtype which were coercing to ``object``. (:issue:`8641`)
- Bug in unique of Series with ``category`` dtype, which returned all categories regardless
whether they were "used" or not (see :issue:`8559` for the discussion).
- ``Series.all`` and ``Series.any`` now support the ``level`` and ``skipna`` parameters. ``Series.all``, ``Series.any``, ``Index.all``, and ``Index.any`` no longer support the ``out`` and ``keepdims`` parameters, which existed for compatibility with ndarray. Various index types no longer support the ``all`` and ``any`` aggregation functions and will now raise ``TypeError``. (:issue:`8302`):
.. ipython:: python
s = pd.Series([False, True, False], index=[0, 0, 1])
s.any(level=0)
- ``Panel`` now supports the ``all`` and ``any`` aggregation functions. (:issue:`8302`):
.. ipython:: python
p = pd.Panel(np.random.rand(2, 5, 4) > 0.1)
p.all()
.. _whatsnew_0152.enhancements:
Enhancements
~~~~~~~~~~~~
- Added ability to export Categorical data to Stata (:issue:`8633`). See :ref:`here <io.stata-categorical>` for limitations of categorical variables exported to Stata data files.
- Added ability to export Categorical data to to/from HDF5 (:issue:`7621`). Queries work the same as if it was an object array. However, the ``category`` dtyped data is stored in a more efficient manner. See :ref:`here <io.hdf5-categorical>` for an example and caveats w.r.t. prior versions of pandas.
- Added support for ``utcfromtimestamp()``, ``fromtimestamp()``, and ``combine()`` on `Timestamp` class (:issue:`5351`).
- Added Google Analytics (`pandas.io.ga`) basic documentation (:issue:`8835`). See :ref:`here<remote_data.ga>`.
- Added flag ``order_categoricals`` to ``StataReader`` and ``read_stata`` to select whether to order imported categorical data (:issue:`8836`). See :ref:`here <io.stata-categorical>` for more information on importing categorical variables from Stata data files.
- ``Timedelta`` arithmetic returns ``NotImplemented`` in unknown cases, allowing extensions by custom classes (:issue:`8813`).
- ``Timedelta`` now supports arithemtic with ``numpy.ndarray`` objects of the appropriate dtype (numpy 1.8 or newer only) (:issue:`8884`).
- Added ``Timedelta.to_timedelta64`` method to the public API (:issue:`8884`).
.. _whatsnew_0152.performance:
Performance
~~~~~~~~~~~
.. _whatsnew_0152.experimental:
Experimental
~~~~~~~~~~~~
.. _whatsnew_0152.bug_fixes:
Bug Fixes
~~~~~~~~~
- Bug in packaging pandas with ``py2app/cx_Freeze`` (:issue:`8602`, :issue:`8831`)
- Bug in ``groupby`` signatures that didn't include \*args or \*\*kwargs (:issue:`8733`).
- ``io.data.Options`` now raises ``RemoteDataError`` when no expiry dates are available from Yahoo and when it receives no data from Yahoo (:issue:`8761`), (:issue:`8783`).
- Unclear error message in csv parsing when passing dtype and names and the parsed data is a different data type (:issue:`8833`)
- Bug in slicing a multi-index with an empty list and at least one boolean indexer (:issue:`8781`)
- ``io.data.Options`` now raises ``RemoteDataError`` when no expiry dates are available from Yahoo (:issue:`8761`).
- ``Timedelta`` kwargs may now be numpy ints and floats (:issue:`8757`).
- Fixed several outstanding bugs for ``Timedelta`` arithmetic and comparisons (:issue:`8813`, :issue:`5963`, :issue:`5436`).
- ``sql_schema`` now generates dialect appropriate ``CREATE TABLE`` statements (:issue:`8697`)
- ``slice`` string method now takes step into account (:issue:`8754`)
- Bug in ``BlockManager`` where setting values with different type would break block integrity (:issue:`8850`)
- Fix negative step support for label-based slices (:issue:`8753`)
Old behavior:
.. code-block:: python
In [1]: s = pd.Series(np.arange(3), ['a', 'b', 'c'])
Out[1]:
a 0
b 1
c 2
dtype: int64
In [2]: s.loc['c':'a':-1]
Out[2]:
c 2
dtype: int64
New behavior:
.. ipython:: python
s = pd.Series(np.arange(3), ['a', 'b', 'c'])
s.loc['c':'a':-1]
- Imported categorical variables from Stata files retain the ordinal information in the underlying data (:issue:`8836`).
- Defined ``.size`` attribute across ``NDFrame`` objects to provide compat with numpy >= 1.9.1; buggy with ``np.array_split`` (:issue:`8846`)
- Skip testing of histogram plots for matplotlib <= 1.2 (:issue:`8648`).
- Bug where ``get_data_google``returned object dtypes (:issue:`3995`)
- Bug in `pd.infer_freq`/`DataFrame.inferred_freq` that prevented proper sub-daily frequency inference
when the index contained DST days (:issue:`8772`).
- Bug where index name was still used when plotting a series with ``use_index=False`` (:issue:`8558`).
- Bugs when trying to stack multiple columns, when some (or all)
of the level names are numbers (:issue:`8584`).
- Bug in ``MultiIndex`` where ``__contains__`` returns wrong result if index is
not lexically sorted or unique (:issue:`7724`)