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Jan 2, 2019
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DOC: fix some doc build warnings/errors #24552

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50264f3
DOC: fix some doc build warnings/errors
jorisvandenbossche Jan 2, 2019
86a1b92
fix linting
jorisvandenbossche Jan 2, 2019
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2 changes: 1 addition & 1 deletion doc/source/cookbook.rst
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Expand Up @@ -1236,7 +1236,7 @@ the following Python code will read the binary file ``'binary.dat'`` into a
pandas ``DataFrame``, where each element of the struct corresponds to a column
in the frame:

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

names = 'count', 'avg', 'scale'

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2 changes: 1 addition & 1 deletion doc/source/integer_na.rst
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Expand Up @@ -2,7 +2,7 @@

{{ header }}

.. _integer_na:
.. _integer_na:

**************************
Nullable Integer Data Type
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2 changes: 1 addition & 1 deletion doc/source/io.rst
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Expand Up @@ -4880,7 +4880,7 @@ below and the SQLAlchemy `documentation <https://docs.sqlalchemy.org/en/latest/c

If you want to manage your own connections you can pass one of those instead:

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

with engine.connect() as conn, conn.begin():
data = pd.read_sql_table('data', conn)
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9 changes: 2 additions & 7 deletions doc/source/missing_data.rst
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Expand Up @@ -759,12 +759,7 @@ the ``dtype="Int64"``.

.. ipython:: python

s = pd.Series(np.random.randn(5), index=[0, 2, 4, 6, 7],
dtype="Int64")
s > 0
(s > 0).dtype
crit = (s > 0).reindex(list(range(8)))
crit
crit.dtype
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@TomAugspurger was there something specific you wanted to show with the above code? It seems you copied this from above about booleans becoming object, but which doesn't seem relevant for integer NA

(the actual fix here is the first line, you can't convert floats from random.randn to Integers)

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I don't recall anything specific goal behind that example.

s = pd.Series([0, 1, np.nan, 3, 4], dtype="Int64")
s

See :ref:`integer_na` for more.
6 changes: 3 additions & 3 deletions doc/source/timeseries.rst
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Expand Up @@ -1874,16 +1874,16 @@ has multiplied span.

.. ipython:: python

pd.PeriodIndex(start='2014-01', freq='3M', periods=4)
pd.period_range(start='2014-01', freq='3M', periods=4)

If ``start`` or ``end`` are ``Period`` objects, they will be used as anchor
endpoints for a ``PeriodIndex`` with frequency matching that of the
``PeriodIndex`` constructor.

.. ipython:: python

pd.PeriodIndex(start=pd.Period('2017Q1', freq='Q'),
end=pd.Period('2017Q2', freq='Q'), freq='M')
pd.period_range(start=pd.Period('2017Q1', freq='Q'),
end=pd.Period('2017Q2', freq='Q'), freq='M')

Just like ``DatetimeIndex``, a ``PeriodIndex`` can also be used to index pandas
objects:
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2 changes: 1 addition & 1 deletion doc/source/tutorials.rst
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Expand Up @@ -33,7 +33,7 @@ repository <http://github.com/jvns/pandas-cookbook>`_.
Learn Pandas by Hernan Rojas
----------------------------

A set of lesson for new pandas users: `Learn pandas <https://bitbucket.org/hrojas/learn-pandas>`__.
A set of lesson for new pandas users: https://bitbucket.org/hrojas/learn-pandas

Practical data analysis with Python
-----------------------------------
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7 changes: 4 additions & 3 deletions doc/source/whatsnew/v0.20.0.rst
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Expand Up @@ -189,14 +189,15 @@ URLs and paths are now inferred using their file extensions. Additionally,
support for bz2 compression in the python 2 C-engine improved (:issue:`14874`).

.. ipython:: python
:okwarning:

url = ('https://github.com/{repo}/raw/{branch}/{path}'
.format(repo='pandas-dev/pandas',
branch='master',
path='pandas/tests/io/parser/data/salaries.csv.bz2'))
df = pd.read_table(url, compression='infer') # default, infer compression
df = pd.read_table(url, compression='bz2') # explicitly specify compression
# default, infer compression
df = pd.read_csv(url, sep='\t', compression='infer')
# explicitly specify compression
df = pd.read_csv(url, sep='\t', compression='bz2')
df.head(2)

.. _whatsnew_0200.enhancements.pickle_compression:
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