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1 change: 0 additions & 1 deletion doc/source/getting_started/install.rst
Original file line number Diff line number Diff line change
Expand Up @@ -146,7 +146,6 @@ Installing using your Linux distribution's package manager.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

The commands in this table will install pandas for Python 3 from your distribution.
To install pandas for Python 2, you may need to use the ``python-pandas`` package.

.. csv-table::
:header: "Distribution", "Status", "Download / Repository Link", "Install method"
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5 changes: 0 additions & 5 deletions doc/source/user_guide/enhancingperf.rst
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Expand Up @@ -78,11 +78,6 @@ four calls) using the `prun ipython magic function <http://ipython.org/ipython-d
By far the majority of time is spend inside either ``integrate_f`` or ``f``,
hence we'll concentrate our efforts cythonizing these two functions.

.. note::

In Python 2 replacing the ``range`` with its generator counterpart (``xrange``)
would mean the ``range`` line would vanish. In Python 3 ``range`` is already a generator.

.. _enhancingperf.plain:

Plain Cython
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17 changes: 3 additions & 14 deletions doc/source/user_guide/io.rst
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Expand Up @@ -39,11 +39,6 @@ The pandas I/O API is a set of top level ``reader`` functions accessed like

:ref:`Here <io.perf>` is an informal performance comparison for some of these IO methods.

.. note::
For examples that use the ``StringIO`` class, make sure you import it
according to your Python version, i.e. ``from StringIO import StringIO`` for
Python 2 and ``from io import StringIO`` for Python 3.
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Maybe keep the note but just talk about the python 3 version? (we still use StringIO a lot throughout the file, and it's only imported once a bit further, so that is easily overlooked)

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Yes, indeed -- partially reverted.


.. _io.read_csv_table:

CSV & text files
Expand Down Expand Up @@ -915,9 +910,7 @@ data columns:
.. note::

When passing a dict as the `parse_dates` argument, the order of
the columns prepended is not guaranteed, because `dict` objects do not impose
an ordering on their keys. On Python 2.7+ you may use `collections.OrderedDict`
instead of a regular `dict` if this matters to you. Because of this, when using a
the columns prepended is not guaranteed. Because of this, when using a
dict for 'parse_dates' in conjunction with the `index_col` argument, it's best to
specify `index_col` as a column label rather then as an index on the resulting frame.

Expand Down Expand Up @@ -2453,7 +2446,7 @@ Specify a number of rows to skip:

dfs = pd.read_html(url, skiprows=0)

Specify a number of rows to skip using a list (``xrange`` (Python 2 only) works
Specify a number of rows to skip using a list (``range`` works
as well):

.. code-block:: python
Expand Down Expand Up @@ -3124,11 +3117,7 @@ Pandas supports writing Excel files to buffer-like objects such as ``StringIO``

.. code-block:: python

# Safe import for either Python 2.x or 3.x
try:
from io import BytesIO
except ImportError:
from cStringIO import StringIO as BytesIO
from io import BytesIO

bio = BytesIO()

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