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DOC: Polishing typos out of doc/source/user_guide/indexing.rst #25528

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Mar 4, 2019
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DOC: Polishing typos out of doc/source/user_guide/indexing.rst #25528

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DOC: typo - matching singular verb to singular subject
leerssej Mar 3, 2019
1787470
DOC: typo fix - 'and' removed since 'that' is already serving as conj…
leerssej Mar 3, 2019
4a05ae9
DOC: typo fix - indefinite article added before the single noun: 'var…
leerssej Mar 3, 2019
fe822e4
DOC: typo fix - definite article added before the single noun: 'method'
leerssej Mar 3, 2019
8fe53ec
DOC: typo fix - added backtick to fix rst formatting
leerssej Mar 3, 2019
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10 changes: 5 additions & 5 deletions doc/source/user_guide/indexing.rst
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Expand Up @@ -435,7 +435,7 @@ Selection By Position
This is sometimes called ``chained assignment`` and should be avoided.
See :ref:`Returning a View versus Copy <indexing.view_versus_copy>`.

Pandas provides a suite of methods in order to get **purely integer based indexing**. The semantics follow closely Python and NumPy slicing. These are ``0-based`` indexing. When slicing, the start bounds is *included*, while the upper bound is *excluded*. Trying to use a non-integer, even a **valid** label will raise an ``IndexError``.
Pandas provides a suite of methods in order to get **purely integer based indexing**. The semantics follow closely Python and NumPy slicing. These are ``0-based`` indexing. When slicing, the start bound is *included*, while the upper bound is *excluded*. Trying to use a non-integer, even a **valid** label will raise an ``IndexError``.

The ``.iloc`` attribute is the primary access method. The following are valid inputs:

Expand Down Expand Up @@ -545,7 +545,7 @@ Selection By Callable
.. versionadded:: 0.18.1

``.loc``, ``.iloc``, and also ``[]`` indexing can accept a ``callable`` as indexer.
The ``callable`` must be a function with one argument (the calling Series, DataFrame or Panel) and that returns valid output for indexing.
The ``callable`` must be a function with one argument (the calling Series, DataFrame or Panel) that returns valid output for indexing.

.. ipython:: python

Expand All @@ -569,7 +569,7 @@ You can use callable indexing in ``Series``.
df1.A.loc[lambda s: s > 0]

Using these methods / indexers, you can chain data selection operations
without using temporary variable.
without using a temporary variable.

.. ipython:: python

Expand Down Expand Up @@ -907,7 +907,7 @@ of the DataFrame):

df[df['A'] > 0]

List comprehensions and ``map`` method of Series can also be used to produce
List comprehensions and the ``map`` method of Series can also be used to produce
more complex criteria:

.. ipython:: python
Expand Down Expand Up @@ -1556,7 +1556,7 @@ See :ref:`Advanced Indexing <advanced>` for usage of MultiIndexes.
ind

``set_names``, ``set_levels``, and ``set_codes`` also take an optional
`level`` argument
``level`` argument

.. ipython:: python

Expand Down