8000 ERR: Boolean comparisons of a Series vs None will now be equivalent to null comparisons by jreback · Pull Request #10569 · pandas-dev/pandas · GitHub
[go: up one dir, main page]
Skip to content

ERR: Boolean comparisons of a Series vs None will now be equivalent to null comparisons #10569

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 8 commits into from
Jul 17, 2015
Merged

ERR: Boolean comparisons of a Series vs None will now be equivalent to null comparisons #10569

Changes from 1 commit
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
4fe7c68
ERR: Boolean comparisons of a Series vs None will now be equivalent o…
jreback Jul 11, 2015
dccf5eb
DEPR: remove numpy deprecation warnings for i8 vs integer comparisions
jreback Jul 16, 2015
8016a7f
DEPR: remove visible deprecation warning for slicing in test_internals
jreback Jul 16, 2015
b381327
DEPR: remove unordered types depreceation usage in core/index.py
jreback Jul 17, 2015
26ee43e
Align options in chunk and full file read
kshedden Jul 17, 2015
4def8e4
TST: fixes stata datetimelike comparisons for #10606
jreback Jul 17, 2015
0bd25ab
DOC: whatsnew changes
jreback Jul 17, 2015
effb676
misc import cleanups
jreback Jul 17, 2015
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
Next Next commit
DOC: whatsnew changes
  • Loading branch information
@jreback
jreback committed Jul 17, 2015
commit 0bd25ab0c44e5e0a82c1abcca57d517a5fcc7659
141 changes: 71 additions & 70 deletions doc/source/whatsnew/v0.17.0.txt
View file
Open in desktop 10000
B285
Original file line number Diff line number Diff line change
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`)
0