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DOC: fix code-block in the reshaping docs #28838

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Merged
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Oct 16, 2019
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DOC: fix code-block in the reshaping docs #28838

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d9d089c
fix code-block in the reshaping docs
oktaysabak Oct 8, 2019
0b09517
code-block selected to python
oktaysabak Oct 8, 2019
07971bd
Update reshaping.rst
jorisvandenbossche Oct 8, 2019
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Update reshaping.rst
oktaysabak Oct 8, 2019
7a8d0ba
Update reshaping.rst
oktaysabak Oct 8, 2019
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Update reshaping.rst
oktaysabak Oct 8, 2019
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oktaysabak Oct 8, 2019
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oktaysabak Oct 8, 2019
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oktaysabak Oct 14, 2019
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.. code-block:: changed to .. code-block:: text
oktaysabak Oct 15, 2019
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16 changes: 8 additions & 8 deletions doc/source/user_guide/reshaping.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -728,14 +728,14 @@ Suppose we wanted to pivot ``df`` such that the ``col`` values are columns,
``row`` values are the index, and the mean of ``val0`` are the values? In
particular, the resulting DataFrame should look like:

.. note::

col col0 col1 col2 col3 col4
row
row0 0.77 0.605 NaN 0.860 0.65
row2 0.13 NaN 0.395 0.500 0.25
row3 NaN 0.310 NaN 0.545 NaN
row4 NaN 0.100 0.395 0.760 0.24
.. code-block:: text
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I still dont' think this will format corectly; rather than trying to fix it this way, simply create a DataFrame and show it.

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I initially thought of doing so. but requested only 'change note to the code-block'. If you want I can change it to the DataFrame then call it on .. code-block:: ipython

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well, does this actually render the same as a dataframe?

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I created a example_dataframe variable. Result after rendering looks like this: link
If you OK, I can commit my changes

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I created a example_dataframe variable. Result after rendering looks like this: link
If you OK, I can commit my changes

*i will write DataFrame values on original 'reshaping.rst' file, this values only for show render results.

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@jreback the point of this block in the docs is to show a possible result, and not an actual dataframe. The full section could maybe be rewritten, but that is outside of scope for this PR.


col col0 col1 col2 col3 col4
row
row0 0.77 0.605 NaN 0.860 0.65
row2 0.13 NaN 0.395 0.500 0.25
row3 NaN 0.310 NaN 0.545 NaN
row4 NaN 0.100 0.395 0.760 0.24

This solution uses :func:`~pandas.pivot_table`. Also note that
``aggfunc='mean'`` is the default. It is included here to be explicit.
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