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v0.15.1.txt
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.. _whatsnew_0151:
v0.15.1 (November 8, 2014)
--------------------------
This is a minor bug-fix release from 0.15.0 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.
- :ref:`Enhancements <whatsnew_0151.enhancements>`
- :ref:`API Changes <whatsnew_0151.api>`
- :ref:`Performance Improvements <whatsnew_0151.performance>`
- :ref:`Experimental Changes <whatsnew_0151.experimental>`
- :ref:`Bug Fixes <whatsnew_0151.bug_fixes>`
.. _whatsnew_0151.api:
API changes
~~~~~~~~~~~
- Represent ``MultiIndex`` labels with a dtype that utilizes memory based on the level size. In prior versions, the memory usage was a constant 8 bytes per element in each level. In addition, in prior versions, the *reported* memory usage was incorrect as it didn't show the usage for the memory occupied by the underling data array. (:issue:`8456`)
.. ipython:: python
dfi = DataFrame(1,index=pd.MultiIndex.from_product([['a'],range(1000)]),columns=['A'])
previous behavior:
.. code-block:: python
# this was underreported in prior versions
In [1]: dfi.memory_usage(index=True)
Out[1]:
Index 8000 # took about 24008 bytes in < 0.15.1
A 8000
dtype: int64
current behavior:
.. ipython:: python
dfi.memory_usage(index=True)
- ``groupby`` with ``as_index=False`` will not add erroneous extra columns to
result (:issue:`8582`):
.. ipython:: python
np.random.seed(2718281)
df = pd.DataFrame(np.random.randint(0, 100, (10, 2)),
columns=['jim', 'joe'])
df.head()
ts = pd.Series(5 * np.random.randint(0, 3, 10))
previous behavior:
.. code-block:: python
In [4]: df.groupby(ts, as_index=False).max()
Out[4]:
NaN jim joe
0 0 72 83
1 5 77 84
2 10 96 65
current behavior:
.. ipython:: python
df.groupby(ts, as_index=False).max()
- ``groupby`` will not erroneously exclude columns if the column name conflics
with the grouper name (:issue:`8112`):
.. ipython:: python
df = pd.DataFrame({'jim': range(5), 'joe': range(5, 10)})
df
gr = df.groupby(df['jim'] < 2)
previous behavior (excludes 1st column from output):
.. code-block:: python
In [4]: gr.apply(sum)
Out[4]:
joe
jim
False 24
True 11
current behavior:
.. ipython:: python
gr.apply(sum)
- ``concat`` permits a wider variety of iterables of pandas objects to be
passed as the first parameter (:issue:`8645`):
.. ipython:: python
from collections import deque
df1 = pd.DataFrame([1, 2, 3])
df2 = pd.DataFrame([4, 5, 6])
previous behavior:
.. code-block:: python
In [7]: pd.concat(deque((df1, df2)))
TypeError: first argument must be a list-like of pandas objects, you passed an object of type "deque"
current behavior:
.. ipython:: python
pd.concat(deque((df1, df2)))
- ``s.dt.hour`` and other ``.dt`` accessors will now return ``np.nan`` for missing values (rather than previously -1), (:issue:`8689`)
.. ipython:: python
s = Series(date_range('20130101',periods=5,freq='D'))
s.iloc[2] = np.nan
s
previous behavior:
.. code-block:: python
In [6]: s.dt.hour
Out[6]:
0 0
1 0
2 -1
3 0
4 0
dtype: int64
current behavior:
.. ipython:: python
s.dt.hour
.. _whatsnew_0151.enhancements:
Enhancements
~~~~~~~~~~~~
- Added option to select columns when importing Stata files (:issue:`7935`)
- Qualify memory usage in ``DataFrame.info()`` by adding ``+`` if it is a lower bound (:issue:`8578`)
- Raise errors in certain aggregation cases where an argument such as ``numeric_only`` is not handled (:issue:`8592`).
- Added support for 3-character ISO and non-standard country codes in :func:``io.wb.download()`` (:issue:`8482`)
- :ref:`World Bank data requests <remote_data.wb>` now will warn/raise based on an ``errors`` argument, as well as a list of hard-coded country codes and the World Bank's JSON response. In prior versions, the error messages didn't look at the World Bank's JSON response. Problem-inducing input were simply dropped prior to the request. The issue was that many good countries were cropped in the hard-coded approach. All countries will work now, but some bad countries will raise exceptions because some edge cases break the entire response. (:issue:`8482`)
- Added option to ``Series.str.split()`` to return a ``DataFrame`` rather than a ``Series`` (:issue:`8428`)
.. _whatsnew_0151.performance:
Performance
~~~~~~~~~~~
.. _whatsnew_0151.experimental:
Experimental
~~~~~~~~~~~~
.. _whatsnew_0151.bug_fixes:
Bug Fixes
~~~~~~~~~
- Bug in unpickling of a ``CustomBusinessDay`` object (:issue:`8591`)
- Bug in coercing ``Categorical`` to a records array, e.g. ``df.to_records()`` (:issue:`8626`)
- Bug in ``Categorical`` not created properly with ``Series.to_frame()`` (:issue:`8626`)
- Bug in coercing in astype of a ``Categorical`` of a passed ``pd.Categorical`` (this now raises ``TypeError`` correctly), (:issue:`8626`)
- Bug in ``cut``/``qcut`` when using ``Series`` and ``retbins=True`` (:issue:`8589`)
- Bug in writing Categorical columns to an SQL database with ``to_sql`` (:issue:`8624`).
- Bug in comparing ``Categorical`` of datetime raising when being compared to a scalar datetime (:issue:`8687`)
- Bug in selecting from a ``Categorical`` with ``.iloc`` (:issue:`8623`)
- Bug in groupby-transform with a Categorical (:issue:`8623`)
- Bug in duplicated/drop_duplicates with a Categorical (:issue:`8623`)
- Bug in numeric index operations of add/sub with Float/Index Index with numpy arrays (:issue:`8608`)
- Bug in setitem with empty indexer and unwanted coercion of dtypes (:issue:`8669`)
- Bug in ix/loc block splitting on setitem (manifests with integer-like dtypes, e.g. datetime64) (:issue:`8607`)
- Fix ``shape`` attribute for ``MultiIndex`` (:issue:`8609`)
- Bug in ``GroupBy`` where a name conflict between the grouper and columns
would break ``groupby`` operations (:issue:`7115`, :issue:`8112`)
- Fixed a bug where plotting a column ``y`` and specifying a label would mutate the index name of the original DataFrame (:issue:`8494`)
- Bug in ``date_range`` where partially-specified dates would incorporate current date (:issue:`6961`)
- Fixed a bug that prevented setting values in a mixed-type Panel4D