DOC: reintroduce contextual pandas tokens

Author: LeviMatus

doc/source/development/contributing_docstring.rst

@@ -616,7 +616,7 @@ be added with blank lines before and after them.
 
 The way to present examples is as follows:
 
-1. Import required libraries (except ``numpy`` and pandas)
+1. Import required libraries (except ``numpy`` and ``pandas``)
 
 2. Create the data required for the example
 

doc/source/development/developer.rst

@@ -33,7 +33,7 @@ where ``KeyValue`` is
    }
 
 So that a ``pandas.DataFrame`` can be faithfully reconstructed, we store a
-pandas metadata key in the ``FileMetaData`` with the value stored as :
+``pandas`` metadata key in the ``FileMetaData`` with the value stored as :
 
 .. code-block:: text
 

doc/source/development/extending.rst

@@ -188,7 +188,7 @@ your ``MyExtensionArray`` class, as follows:
 
 .. note::
 
-   Since pandas automatically calls the underlying operator on each
+   Since ``pandas`` automatically calls the underlying operator on each
    element one-by-one, this might not be as performant as implementing your own
    version of the associated operators directly on the ``ExtensionArray``.
 
@@ -303,7 +303,7 @@ dtypes included in pandas, and ensure roundtrip to pyarrow and the Parquet file
 Subclassing pandas data structures
 ----------------------------------
 
-.. warning:: There are some easier alternatives before considering subclassing pandas data structures.
+.. warning:: There are some easier alternatives before considering subclassing ``pandas`` data structures.
 
   1. Extensible method chains with :ref:`pipe <basics.pipe>`
 
@@ -313,7 +313,7 @@ Subclassing pandas data structures
 
   4. Extending by :ref:`extension type <extending.extension-types>`
 
-This section describes how to subclass pandas data structures to meet more specific needs. There are two points that need attention:
+This section describes how to subclass ``pandas`` data structures to meet more specific needs. There are two points that need attention:
 
 1. Override constructor properties.
 2. Define original properties
@@ -327,15 +327,15 @@ Override constructor properties
 
 Each data structure has several *constructor properties* for returning a new
 data structure as the result of an operation. By overriding these properties,
-you can retain subclasses through pandas data manipulations.
+you can retain subclasses through ``pandas`` data manipulations.
 
 There are 3 constructor properties to be defined:
 
 * ``_constructor``: Used when a manipulation result has the same dimensions as the original.
 * ``_constructor_sliced``: Used when a manipulation result has one lower dimension(s) as the original, such as ``DataFrame`` single columns slicing.
 * ``_constructor_expanddim``: Used when a manipulation result has one higher dimension as the original, such as ``Series.to_frame()``.
 
-Following table shows how pandas data structures define constructor properties by default.
+Following table shows how ``pandas`` data structures define constructor properties by default.
 
 ===========================  ======================= =============
 Property Attributes          ``Series``              ``DataFrame``
@@ -411,7 +411,7 @@ Below example shows how to define ``SubclassedSeries`` and ``SubclassedDataFrame
 Define original properties
 ^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-To let original data structures have additional properties, you should let pandas know what properties are added. pandas maps unknown properties to data names overriding ``__getattribute__``. Defining original properties can be done in one of 2 ways:
+To let original data structures have additional properties, you should let ``pandas`` know what properties are added. ``pandas`` maps unknown properties to data names overriding ``__getattribute__``. Defining original properties can be done in one of 2 ways:
 
 1. Define ``_internal_names`` and ``_internal_names_set`` for temporary properties which WILL NOT be passed to manipulation results.
 2. Define ``_metadata`` for normal properties which will be passed to manipulation results.

doc/source/user_guide/io.rst

@@ -3365,7 +3365,7 @@ All pandas objects are equipped with ``to_pickle`` methods which use Python's
    df
    df.to_pickle("foo.pkl")
 
-The ``read_pickle`` function in the pandas namespace can be used to load
+The ``read_pickle`` function in the ``pandas`` namespace can be used to load
 any pickled pandas object (or any other pickled object) from file:
 
 

doc/source/user_guide/options.rst

@@ -22,7 +22,7 @@ You can get/set options directly as attributes of the top-level ``options`` attr
    pd.options.display.max_rows = 999
    pd.options.display.max_rows
 
-The API is composed of 5 relevant functions, available directly from the pandas
+The API is composed of 5 relevant functions, available directly from the ``pandas``
 namespace:
 
 * :func:`~pandas.get_option` / :func:`~pandas.set_option` - get/set the value of a single option.

doc/source/whatsnew/v0.12.0.rst

@@ -18,7 +18,7 @@ API changes
 ~~~~~~~~~~~
 
   - The I/O API is now much more consistent with a set of top level ``reader`` functions
-    accessed like ``pd.read_csv()`` that generally return a pandas object.
+    accessed like ``pd.read_csv()`` that generally return a ``pandas`` object.
 
     * ``read_csv``
     * ``read_excel``
@@ -179,7 +179,7 @@ API changes
     ``bs4`` + ``html5lib`` when lxml fails to parse. a list of parsers to try
     until success is also valid
 
-  - The internal pandas class hierarchy has changed (slightly). The
+  - The internal ``pandas`` class hierarchy has changed (slightly). The
     previous ``PandasObject`` now is called ``PandasContainer`` and a new
     ``PandasObject`` has become the base class for ``PandasContainer`` as well
     as ``Index``, ``Categorical``, ``GroupBy``, ``SparseList``, and

doc/source/whatsnew/v0.13.0.rst

@@ -57,7 +57,7 @@ API changes
   filter, map and zip, plus other necessary elements for Python 3
   compatibility. ``lmap``, ``lzip``, ``lrange`` and ``lfilter`` all produce
   lists instead of iterators, for compatibility with ``numpy``, subscripting
-  and pandas constructors.(:issue:`4384`, :issue:`4375`, :issue:`4372`)
+  and ``pandas`` constructors.(:issue:`4384`, :issue:`4375`, :issue:`4372`)
 - ``Series.get`` with negative indexers now returns the same as ``[]`` (:issue:`4390`)
 - Changes to how ``Index`` and ``MultiIndex`` handle metadata (``levels``,
   ``labels``, and ``names``) (:issue:`4039`):

doc/source/whatsnew/v0.18.1.rst

@@ -381,9 +381,9 @@ NumPy function compatibility
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 Compatibility between pandas array-like methods (e.g. ``sum`` and ``take``) and their ``numpy``
-counterparts has been greatly increased by augmenting the signatures of the pandas methods so
+counterparts has been greatly increased by augmenting the signatures of the ``pandas`` methods so
 as to accept arguments that can be passed in from ``numpy``, even if they are not necessarily
-used in the pandas implementation (:issue:`12644`, :issue:`12638`, :issue:`12687`)
+used in the ``pandas`` implementation (:issue:`12644`, :issue:`12638`, :issue:`12687`)
 
 - ``.searchsorted()`` for ``Index`` and ``TimedeltaIndex`` now accept a ``sorter`` argument to maintain compatibility with numpy's ``searchsorted`` function (:issue:`12238`)
 - Bug in numpy compatibility of ``np.round()`` on a ``Series`` (:issue:`12600`)

doc/source/whatsnew/v0.19.0.rst

@@ -404,7 +404,7 @@ Google BigQuery enhancements
 Fine-grained NumPy errstate
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Previous versions of pandas would permanently silence numpy's ufunc error handling when pandas was imported. pandas did this in order to silence the warnings that would arise from using numpy ufuncs on missing data, which are usually represented as ``NaN`` s. Unfortunately, this silenced legitimate warnings arising in non-pandas code in the application. Starting with 0.19.0, pandas will use the ``numpy.errstate`` context manager to silence these warnings in a more fine-grained manner, only around where these operations are actually used in the pandas code base. (:issue:`13109`, :issue:`13145`)
+Previous versions of pandas would permanently silence numpy's ufunc error handling when ``pandas`` was imported. pandas did this in order to silence the warnings that would arise from using numpy ufuncs on missing data, which are usually represented as ``NaN`` s. Unfortunately, this silenced legitimate warnings arising in non-pandas code in the application. Starting with 0.19.0, pandas will use the ``numpy.errstate`` context manager to silence these warnings in a more fine-grained manner, only around where these operations are actually used in the pandas code base. (:issue:`13109`, :issue:`13145`)
 
 After upgrading pandas, you may see *new* ``RuntimeWarnings`` being issued from your code. These are likely legitimate, and the underlying cause likely existed in the code when using previous versions of pandas that simply silenced the warning. Use `numpy.errstate <https://numpy.org/doc/stable/reference/generated/numpy.errstate.html>`__ around the source of the ``RuntimeWarning`` to control how these conditions are handled.
 

doc/source/whatsnew/v0.20.0.rst

@@ -1543,7 +1543,7 @@ Other deprecations
 - ``TimedeltaIndex.searchsorted()``, ``DatetimeIndex.searchsorted()``, and ``PeriodIndex.searchsorted()`` have deprecated the ``key`` parameter in favor of ``value`` (:issue:`12662`)
 - ``DataFrame.astype()`` has deprecated the ``raise_on_error`` parameter in favor of ``errors`` (:issue:`14878`)
 - ``Series.sortlevel`` and ``DataFrame.sortlevel`` have been deprecated in favor of ``Series.sort_index`` and ``DataFrame.sort_index`` (:issue:`15099`)
-- importing ``concat`` from ``pandas.tools.merge`` has been deprecated in favor of imports from the pandas namespace. This should only affect explicit imports (:issue:`15358`)
+- importing ``concat`` from ``pandas.tools.merge`` has been deprecated in favor of imports from the ``pandas`` namespace. This should only affect explicit imports (:issue:`15358`)
 - ``Series/DataFrame/Panel.consolidate()`` been deprecated as a public method. (:issue:`15483`)
 - The ``as_indexer`` keyword of ``Series.str.match()`` has been deprecated (ignored keyword) (:issue:`15257`).
 - The following top-level pandas functions have been deprecated and will be removed in a future version (:issue:`13790`, :issue:`15940`)