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DOC: whatsnew changes
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@jreback
jreback committed Jul 17, 2015
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141 changes: 71 additions & 70 deletions doc/source/whatsnew/v0.17.0.txt
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Expand Up @@ -34,6 +34,7 @@ New features

Other enhancements
^^^^^^^^^^^^^^^^^^

- Enable `read_hdf` to be used without specifying a key when the HDF file contains a single dataset (:issue:`10443`)

- ``DatetimeIndex`` can be instantiated using strings contains ``NaT`` (:issue:`7599`)
Expand Down Expand Up @@ -91,7 +92,7 @@ Backwards incompatible API changes
Changes to convert_objects
^^^^^^^^^^^^^^^^^^^^^^^^^^

- ``DataFrame.convert_objects`` keyword arguments have been shortened. (:issue:`10265`)
``DataFrame.convert_objects`` keyword arguments have been shortened. (:issue:`10265`)

===================== =============
Old New
Expand All @@ -101,70 +102,65 @@ Changes to convert_objects
``convert_timedelta`` ``timedelta``
===================== =============

- Coercing types with ``DataFrame.convert_objects`` is now implemented using the
keyword argument ``coerce=True``. Previously types were coerced by setting a
keyword argument to ``'coerce'`` instead of ``True``, as in ``convert_dates='coerce'``.

.. ipython:: python
Coercing types with ``DataFrame.convert_objects`` is now implemented using the
keyword argument ``coerce=True``. Previously types were coerced by setting a
keyword argument to ``'coerce'`` instead of ``True``, as in ``convert_dates='coerce'``.

df = pd.DataFrame({'i': ['1','2'],
'f': ['apple', '4.2'],
's': ['apple','banana']})
df
.. ipython:: python

The old usage of ``DataFrame.convert_objects`` used `'coerce'` along with the
type.
df = pd.DataFrame({'i': ['1','2'],
'f': ['apple', '4.2'],
's': ['apple','banana']})
df

.. code-block:: python
The old usage of ``DataFrame.convert_objects`` used `'coerce'` along with the
type.

In [2]: df.convert_objects(convert_numeric='coerce')

Now the ``coerce`` keyword must be explicitly used.

.. ipython:: python
.. code-block:: python

df.convert_objects(numeric=True, coerce=True)
In [2]: df.convert_objects(convert_numeric='coerce')

- In earlier versions of pandas, ``DataFrame.convert_objects`` would not coerce
numeric types when there were no values convertible to a numeric type. For example,
Now the ``coerce`` keyword must be explicitly used.

.. code-block:: python
.. ipython:: python

In [1]: df = pd.DataFrame({'s': ['a','b']})
In [2]: df.convert_objects(convert_numeric='coerce')
Out[2]:
s
0 a
1 b
df.convert_objects(numeric=True, coerce=True)

returns the original DataFrame with no conversion. This change alters
this behavior so that
In earlier versions of pandas, ``DataFrame.convert_objects`` would not coerce
numeric types when there were no values convertible to a numeric type. This returns
the original DataFrame with no conversion. This change alters
this behavior so that converts all non-number-like strings to ``NaN``.

.. ipython:: python
.. code-block:: python

pd.DataFrame({'s': ['a','b']})
df.convert_objects(numeric=True, coerce=True)
In [1]: df = pd.DataFrame({'s': ['a','b']})
In [2]: df.convert_objects(convert_numeric='coerce')
Out[2]:
s
0 a
1 b

converts all non-number-like strings to ``NaN``.
.. ipython:: python

- In earlier versions of pandas, the default behavior was to try and convert
datetimes and timestamps. The new default is for ``DataFrame.convert_objects``
to do nothing, and so it is necessary to pass at least one conversion target
in the method call.
pd.DataFrame({'s': ['a','b']})
df.convert_objects(numeric=True, coerce=True)

.. _whatsnew_0170.api_breaking.other:
In earlier versions of pandas, the default behavior was to try and convert
datetimes and timestamps. The new default is for ``DataFrame.convert_objects``
to do nothing, and so it is necessary to pass at least one conversion target
in the method call.

Other API Changes
^^^^^^^^^^^^^^^^^
Changes to Index Comparisons
^^^^^^^^^^^^^^^^^^^^^^^^^^^^

- Operator equal on Index should behavior similarly to Series (:issue:`9947`)
Operator equal on Index should behavior similarly to Series (:issue:`9947`)

Starting in v0.17.0, comparing ``Index`` objects of different lengths will raise
a ``ValueError``. This is to be consistent with the behavior of ``Series``.
Starting in v0.17.0, comparing ``Index`` objects of different lengths will raise
a ``ValueError``. This is to be consistent with the behavior of ``Series``.

Previous behavior:
Previous behavior:

.. code-block:: python
.. code-block:: python

In [2]: pd.Index([1, 2, 3]) == pd.Index([1, 4, 5])
Out[2]: array([ True, False, False], dtype=bool)
Expand All @@ -188,9 +184,9 @@ Other API Changes
In [7]: pd.Series([1, 2, 3]) == pd.Series([1, 2])
ValueError: Series lengths must match to compare

New behavior:
New behavior:

.. code-block:: python
.. code-block:: python

In [8]: pd.Index([1, 2, 3]) == pd.Index([1, 4, 5])
Out[8]: array([ True, False, False], dtype=bool)
Expand All @@ -214,24 +210,27 @@ Other API Changes
In [13]: pd.Series([1, 2, 3]) == pd.Series([1, 2])
ValueError: Series lengths must match to compare

Note that this is different from the ``numpy`` behavior where a comparison can
be broadcast:
Note that this is different from the ``numpy`` behavior where a comparison can
be broadcast:

.. ipython:: python
.. ipython:: python

np.array([1, 2, 3]) == np.array([1])

or it can return False if broadcasting can not be done:
or it can return False if broadcasting can not be done:

.. ipython:: python
.. ipython:: python

np.array([1, 2, 3]) == np.array([1, 2])

Other API Changes
^^^^^^^^^^^^^^^^^

- Enable writing Excel files in :ref:`memory <_io.excel_writing_buffer>` using StringIO/BytesIO (:issue:`7074`)
- Enable serialization of lists and dicts to strings in ExcelWriter (:issue:`8188`)
- Allow passing `kwargs` to the interpolation methods (:issue:`10378`).
- Serialize metadata properties of subclasses of pandas objects (:issue:`10553`).
- Boolean comparisons of a ``Series`` vs None will now be equivalent to comparing with np.nan, rather than raise ``TypeError``, xref (:issue:`1079`).
- Boolean comparisons of a ``Series`` vs ``None`` will now be equivalent to comparing with ``np.nan``, rather than raise ``TypeError``, xref (:issue:`1079`).
- Remove use of some deprecated numpy comparisons (:issue:`10569`)

.. _whatsnew_0170.deprecations:
Expand Down Expand Up @@ -288,46 +287,48 @@ Bug Fixes

- Bug in ``DataFrame.apply`` when function returns categorical series. (:issue:`9573`)
- Bug in ``to_datetime`` with invalid dates and formats supplied (:issue:`10154`)

- Bug in ``Index.drop_duplicates`` dropping name(s) (:issue:`10115`)


- Bug in ``pd.Series`` when setting a value on an empty ``Series`` whose index has a frequency. (:issue:`10193`)

- Bug in ``DataFrame.plot`` raises ``ValueError`` when color name is specified by multiple characters (:issue:`10387`)
- Bug in ``DataFrame.reset_index`` when index contains `NaT`. (:issue:`10388`)
- Bug in ``ExcelReader`` when worksheet is empty (:issue:`6403`)
- Bug in ``Table.select_column`` where name is not preserved (:issue:`10392`)
- Bug in ``offsets.generate_range`` where ``start`` and ``end`` have finer precision than ``offset`` (:issue:`9907`)


- Bug in ``ExcelReader`` when worksheet is empty (:issue:`6403`)


- Bug in ``Table.select_column`` where name is not preserved (:issue:`10392`)
- Bug in ``offsets.generate_range`` where ``start`` and ``end`` have finer precision than ``offset`` (:issue:`9907`)


- Bug in ``DataFrame.interpolate`` with ``axis=1`` and ``inplace=True`` (:issue:`10395`)

- Bug in ``io.sql.get_schema`` when specifying multiple columns as primary
key (:issue:`10385`).


- Bug in ``test_categorical`` on big-endian builds (:issue:`10425`)
- Bug in ``Series.map`` using categorical ``Series`` raises ``AttributeError`` (:issue:`10324`)
- Bug in ``MultiIndex.get_level_values`` including ``Categorical`` raises ``AttributeError`` (:issue:`10460`)







- Bug that caused segfault when resampling an empty Series (:issue:`10228`)
- Bug in ``DatetimeIndex`` and ``PeriodIndex.value_counts`` resets name from its result, but retains in result's ``Index``. (:issue:`10150`)

- Bug in `pandas.concat` with ``axis=0`` when column is of dtype ``category`` (:issue:`10177`)

- Bug in ``read_msgpack`` where input type is not always checked (:issue:`10369`)

- Bug in `pandas.read_csv` with ``index_col=False`` or with ``index_col=['a', 'b']`` (:issue:`10413`, :issue:`10467`)

- Bug in `Series.from_csv` with ``header`` kwarg not setting the ``Series.name`` or the ``Series.index.name`` (:issue:`10483`)

- Bug in `groupby.var` which caused variance to be inaccurate for small float values (:issue:`10448`)

- Bug in ``Series.plot(kind='hist')`` Y Label not informative (:issue:`10485`)










- Bug in operator equal on Index not being consistent with Series (:issue:`9947`)

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