Skip to content

DOC: Fix flake8 issues with whatsnew v0.18.* #24303

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 6 commits into from
Dec 18, 2018
Merged

DOC: Fix flake8 issues with whatsnew v0.18.* #24303

Show file tree
Hide file tree
Changes from 5 commits
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
67ff7ae
DOC: Fix flake8 issues with whatsnew v0.18.*
JimJeon Dec 16, 2018
7e4bc37
DOC: Fixes import of StringIO
JimJeon Dec 16, 2018
f898da7
DOC: Fix reviewed issues
JimJeon Dec 17, 2018
2d7d5e5
DOC: Remove pandas import from v0.18.1
JimJeon Dec 17, 2018
c3fd30f
DOC: Rearrange the import block
JimJeon Dec 17, 2018
a17fa1b
DOC: Add a blank line
JimJeon Dec 18, 2018
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
42 changes: 19 additions & 23 deletions doc/source/whatsnew/v0.18.0.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,11 +5,6 @@ v0.18.0 (March 13, 2016)

{{ header }}

.. ipython:: python
:suppress:

from pandas import * # noqa F401, F403


This is a major release from 0.17.1 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
Expand Down Expand Up @@ -64,14 +59,14 @@ Window functions have been refactored to be methods on ``Series/DataFrame`` obje
.. ipython:: python

np.random.seed(1234)
df = pd.DataFrame({'A' : range(10), 'B' : np.random.randn(10)})
df = pd.DataFrame({'A': range(10), 'B': np.random.randn(10)})
df

Previous Behavior:

.. code-block:: ipython

In [8]: pd.rolling_mean(df,window=3)
In [8]: pd.rolling_mean(df, window=3)
FutureWarning: pd.rolling_mean is deprecated for DataFrame and will be removed in a future version, replace with
DataFrame.rolling(window=3,center=False).mean()
Out[8]:
Expand Down Expand Up @@ -102,7 +97,7 @@ with tab-completion of available methods and properties.

.. code-block:: ipython

In [9]: r.
In [9]: r.<TAB> # noqa E225, E999
r.A r.agg r.apply r.count r.exclusions r.max r.median r.name r.skew r.sum
r.B r.aggregate r.corr r.cov r.kurt r.mean r.min r.quantile r.std r.var

Expand All @@ -122,8 +117,8 @@ And multiple aggregations

.. ipython:: python

r.agg({'A' : ['mean','std'],
'B' : ['mean','std']})
r.agg({'A': ['mean', 'std'],
'B': ['mean', 'std']})

.. _whatsnew_0180.enhancements.rename:

Expand Down Expand Up @@ -201,7 +196,7 @@ Currently the default is ``expand=None`` which gives a ``FutureWarning`` and use

.. code-block:: ipython

In [1]: pd.Series(['a1', 'b2', 'c3']).str.extract('[ab](\d)', expand=None)
In [1]: pd.Series(['a1', 'b2', 'c3']).str.extract(r'[ab](\d)', expand=None)
FutureWarning: currently extract(expand=None) means expand=False (return Index/Series/DataFrame)
but in a future version of pandas this will be changed to expand=True (return DataFrame)

Expand All @@ -216,13 +211,13 @@ Extracting a regular expression with one group returns a Series if

.. ipython:: python

pd.Series(['a1', 'b2', 'c3']).str.extract('[ab](\d)', expand=False)
pd.Series(['a1', 'b2', 'c3']).str.extract(r'[ab](\d)', expand=False)

It returns a ``DataFrame`` with one column if ``expand=True``.

.. ipython:: python

pd.Series(['a1', 'b2', 'c3']).str.extract('[ab](\d)', expand=True)
pd.Series(['a1', 'b2', 'c3']).str.extract(r'[ab](\d)', expand=True)

Calling on an ``Index`` with a regex with exactly one capture group
returns an ``Index`` if ``expand=False``.
Expand Down Expand Up @@ -270,13 +265,13 @@ match.

s = pd.Series(["a1a2", "b1", "c1"], ["A", "B", "C"])
s
s.str.extract("(?P<letter>[ab])(?P<digit>\d)", expand=False)
s.str.extract(r"(?P<letter>[ab])(?P<digit>\d)", expand=False)

The ``extractall`` method returns all matches.

.. ipython:: python

s.str.extractall("(?P<letter>[ab])(?P<digit>\d)")
s.str.extractall(r"(?P<letter>[ab])(?P<digit>\d)")

.. _whatsnew_0180.enhancements.strcat:

Expand All @@ -289,12 +284,12 @@ A new, friendlier ``ValueError`` is added to protect against the mistake of supp

.. ipython:: python

pd.Series(['a','b',np.nan,'c']).str.cat(sep=' ')
pd.Series(['a','b',np.nan,'c']).str.cat(sep=' ', na_rep='?')
pd.Series(['a', 'b', np.nan, 'c']).str.cat(sep=' ')
pd.Series(['a', 'b', np.nan, 'c']).str.cat(sep=' ', na_rep='?')

.. code-block:: ipython

In [2]: pd.Series(['a','b',np.nan,'c']).str.cat(' ')
In [2]: pd.Series(['a', 'b', np.nan, 'c']).str.cat(' ')
ValueError: Did you mean to supply a `sep` keyword?


Expand Down Expand Up @@ -329,7 +324,7 @@ Timedeltas

.. ipython:: python

t = timedelta_range('1 days 2 hr 13 min 45 us',periods=3,freq='d')
t = timedelta_range('1 days 2 hr 13 min 45 us', periods=3, freq='d')
t
t.round('10min')

Expand All @@ -356,7 +351,7 @@ Previous Behavior:

.. code-block:: ipython

In [2]: s = pd.Series([1,2,3], index=np.arange(3.))
In [2]: s = pd.Series([1, 2, 3], index=np.arange(3.))

In [3]: s
Out[3]:
Expand All @@ -378,7 +373,7 @@ New Behavior:

.. ipython:: python

s = pd.Series([1,2,3], index=np.arange(3.))
s = pd.Series([1, 2, 3], index=np.arange(3.))
s
s.index
print(s.to_csv(path_or_buf=None, header=False))
Expand Down Expand Up @@ -727,7 +722,8 @@ Like the change in the window functions API :ref:`above <whatsnew_0180.enhanceme
np.random.seed(1234)
df = pd.DataFrame(np.random.rand(10,4),
columns=list('ABCD'),
index=pd.date_range('2010-01-01 09:00:00', periods=10, freq='s'))
index=pd.date_range('2010-01-01 09:00:00',
periods=10, freq='s'))
df


Expand Down Expand Up @@ -1137,7 +1133,7 @@ and setting

Positional setting with ``.ix`` and a float indexer will ADD this value to the index, rather than previously setting the value by position.

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

In [3]: s2.ix[1.0] = 10
In [4]: s2
Expand Down
52 changes: 27 additions & 25 deletions doc/source/whatsnew/v0.18.1.rst
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -5,11 +5,6 @@ v0.18.1 (May 3, 2016)

{{ header }}

.. ipython:: python
:suppress:

from pandas import * # noqa F401, F403


This is a minor bug-fix release from 0.18.0 and includes a large number of
bug fixes along with several new features, enhancements, and performance improvements.
Expand Down Expand Up @@ -53,7 +48,8 @@ Friday before MLK Day

.. ipython:: python

dt = datetime(2014, 1, 17, 15)
import datetime
dt = datetime.datetime(2014, 1, 17, 15)

dt + bhour_us

Expand Down Expand Up @@ -171,8 +167,7 @@ without using temporary variable.
bb = pd.read_csv('data/baseball.csv', index_col='id')
(bb.groupby(['year', 'team'])
.sum()
.loc[lambda df: df.r > 100]
)
.loc[lambda df: df.r > 100])

.. _whatsnew_0181.partial_string_indexing:

Expand All @@ -183,12 +178,13 @@ Partial string indexing now matches on ``DateTimeIndex`` when part of a ``MultiI

.. ipython:: python

dft2 = pd.DataFrame(np.random.randn(20, 1),
columns=['A'],
index=pd.MultiIndex.from_product([pd.date_range('20130101',
periods=10,
freq='12H'),
['a', 'b']]))
dft2 = pd.DataFrame(
np.random.randn(20, 1),
columns=['A'],
index=pd.MultiIndex.from_product([pd.date_range('20130101',
periods=10,
freq='12H'),
['a', 'b']]))
dft2
dft2.loc['2013-01-05']

Expand Down Expand Up @@ -317,8 +313,8 @@ The index in ``.groupby(..).nth()`` output is now more consistent when the ``as_

.. ipython:: python

df = DataFrame({'A' : ['a', 'b', 'a'],
'B' : [1, 2, 3]})
df = pd.DataFrame({'A': ['a', 'b', 'a'],
'B': [1, 2, 3]})
df

Previous Behavior:
Expand Down Expand Up @@ -433,13 +429,15 @@ Previous behavior:

.. code-block:: ipython

In [1]: df.groupby(pd.TimeGrouper(key='date', freq='M')).apply(lambda x: x.value.sum())
In [1]: df.groupby(pd.TimeGrouper(key='date',
...: freq='M')).apply(lambda x: x.value.sum())
Out[1]:
...
TypeError: cannot concatenate a non-NDFrame object

# Output is a Series
In [2]: df.groupby(pd.TimeGrouper(key='date', freq='M')).apply(lambda x: x[['value']].sum())
In [2]: df.groupby(pd.TimeGrouper(key='date',
...: freq='M')).apply(lambda x: x[['value']].sum())
Out[2]:
date
2000-10-31 value 10
Expand All @@ -448,18 +446,20 @@ Previous behavior:

New Behavior:

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

# Output is a Series
In [55]: df.groupby(pd.TimeGrouper(key='date', freq='M')).apply(lambda x: x.value.sum())
In [55]: df.groupby(pd.TimeGrouper(key='date',
...: freq='M')).apply(lambda x: x.value.sum())
Out[55]:
date
2000-10-31 10
2000-11-30 13
Freq: M, dtype: int64

# Output is a DataFrame
In [56]: df.groupby(pd.TimeGrouper(key='date', freq='M')).apply(lambda x: x[['value']].sum())
In [56]: df.groupby(pd.TimeGrouper(key='date',
...: freq='M')).apply(lambda x: x[['value']].sum())
Out[56]:
value
date
Expand All @@ -471,30 +471,32 @@ New Behavior:
Changes in ``read_csv`` exceptions
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^


In order to standardize the ``read_csv`` API for both the ``c`` and ``python`` engines, both will now raise an
``EmptyDataError``, a subclass of ``ValueError``, in response to empty columns or header (:issue:`12493`, :issue:`12506`)

Previous behaviour:

.. code-block:: ipython
In [1]: import io
Copy link
Contributor

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

I think you need a blank line here

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Thanks.


In [1]: df = pd.read_csv(StringIO(''), engine='c')
In [2]: df = pd.read_csv(io.StringIO(''), engine='c')
...
ValueError: No columns to parse from file

In [2]: df = pd.read_csv(StringIO(''), engine='python')
In [3]: df = pd.read_csv(io.StringIO(''), engine='python')
...
StopIteration

New behaviour:

.. code-block:: ipython

In [1]: df = pd.read_csv(StringIO(''), engine='c')
In [1]: df = pd.read_csv(io.StringIO(''), engine='c')
...
pandas.io.common.EmptyDataError: No columns to parse from file

In [2]: df = pd.read_csv(StringIO(''), engine='python')
In [2]: df = pd.read_csv(io.StringIO(''), engine='python')
...
pandas.io.common.EmptyDataError: No columns to parse from file

Expand Down
2 changes: 0 additions & 2 deletions setup.cfg
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -56,8 +56,6 @@ exclude =
doc/source/whatsnew/v0.16.2.rst
doc/source/whatsnew/v0.17.0.rst
doc/source/whatsnew/v0.17.1.rst
doc/source/whatsnew/v0.18.0.rst
doc/source/whatsnew/v0.18.1.rst
doc/source/basics.rst
doc/source/contributing_docstring.rst
doc/source/enhancingperf.rst
Expand Down