@@ -41,8 +41,7 @@ The pandas I/O API is a set of top level ``reader`` functions accessed like
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.. note ::
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For examples that use the ``StringIO `` class, make sure you import it
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- according to your Python version, i.e. ``from StringIO import StringIO `` for
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- Python 2 and ``from io import StringIO `` for Python 3.
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+ with ``from io import StringIO `` for Python 3.
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.. _io.read_csv_table :
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@@ -912,16 +911,6 @@ data columns:
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significantly faster, ~20x has been observed.
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- .. note ::
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-
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- When passing a dict as the `parse_dates ` argument, the order of
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- the columns prepended is not guaranteed, because `dict ` objects do not impose
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- an ordering on their keys. On Python 2.7+ you may use `collections.OrderedDict `
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- instead of a regular `dict ` if this matters to you. Because of this, when using a
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- dict for 'parse_dates' in conjunction with the `index_col ` argument, it's best to
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- specify `index_col ` as a column label rather then as an index on the resulting frame.
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-
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-
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Date parsing functions
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++++++++++++++++++++++
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@@ -2453,7 +2442,7 @@ Specify a number of rows to skip:
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dfs = pd.read_html(url, skiprows = 0 )
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- Specify a number of rows to skip using a list (``xrange `` (Python 2 only) works
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+ Specify a number of rows to skip using a list (``range `` works
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as well):
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.. code-block :: python
@@ -3124,11 +3113,7 @@ Pandas supports writing Excel files to buffer-like objects such as ``StringIO``
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.. code-block :: python
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- # Safe import for either Python 2.x or 3.x
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- try :
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- from io import BytesIO
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- except ImportError :
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- from cStringIO import StringIO as BytesIO
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+ from io import BytesIO
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bio = BytesIO()
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