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MultiIndex Doc #18169

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16 changes: 8 additions & 8 deletions doc/source/advanced.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -174,14 +174,14 @@ on a deeper level.
Defined Levels
~~~~~~~~~~~~~~

The repr of a ``MultiIndex`` shows ALL the defined levels of an index, even
The repr of a ``MultiIndex`` shows all the defined levels of an index, even
if the they are not actually used. When slicing an index, you may notice this.
For example:

.. ipython:: python

# original multi-index
df.columns
  # original MultiIndex
  df.columns

# sliced
df[['foo','qux']].columns
Expand Down Expand Up @@ -264,7 +264,7 @@ Passing a list of labels or tuples works similar to reindexing:
Using slicers
~~~~~~~~~~~~~

You can slice a multi-index by providing multiple indexers.
You can slice a ``MultiIndex`` by providing multiple indexers.

You can provide any of the selectors as if you are indexing by label, see :ref:`Selection by Label <indexing.label>`,
including slices, lists of labels, labels, and boolean indexers.
Expand All @@ -278,16 +278,16 @@ As usual, **both sides** of the slicers are included as this is label indexing.

You should specify all axes in the ``.loc`` specifier, meaning the indexer for the **index** and
for the **columns**. There are some ambiguous cases where the passed indexer could be mis-interpreted
as indexing *both* axes, rather than into say the MuliIndex for the rows.
  as indexing *both* axes, rather than into say the ``MultiIndex`` for the rows.

You should do this:

.. code-block:: python

df.loc[(slice('A1','A3'),.....), :]

rather than this:

  rather than this:
 
.. code-block:: python

df.loc[(slice('A1','A3'),.....)]
Expand Down Expand Up @@ -494,7 +494,7 @@ are named.
s.sort_index(level='L2')

On higher dimensional objects, you can sort any of the other axes by level if
they have a MultiIndex:
they have a ``MultiIndex``:

.. ipython:: python

Expand Down