DOC: doc typos, xref pandas-dev#15838

Author: jreback

ci/requirements-3.6_DOC.run

@@ -12,6 +12,7 @@ lxml
 beautifulsoup4
 html5lib
 pytables
+python-snappy
 openpyxl
 xlrd
 xlwt

doc/source/install.rst

@@ -237,7 +237,7 @@ Optional Dependencies
 * `xarray <http://xarray.pydata.org>`__: pandas like handling for > 2 dims, needed for converting Panels to xarray objects. Version 0.7.0 or higher is recommended.
 * `PyTables <http://www.pytables.org>`__: necessary for HDF5-based storage. Version 3.0.0 or higher required, Version 3.2.1 or higher highly recommended.
 * `Feather Format <https://github.com/wesm/feather>`__: necessary for feather-based storage, version 0.3.1 or higher.
-* ``Apache Parquet Format``, either `pyarrow <http://arrow.apache.org/docs/python/>`__ (>= 0.4.1) or `fastparquet <https://fastparquet.readthedocs.io/en/latest/necessary>`__ (>= 0.0.6) for parquet-based storage. The `snappy <https://pypi.python.org/pypi/python-snappy>`__ and `brotli <https://pypi.python.org/pypi/brotlipy>`__ are available for compression support.
+* `Apache Parquet <https://parquet.apache.org/>`__, either `pyarrow <http://arrow.apache.org/docs/python/>`__ (>= 0.4.1) or `fastparquet <https://fastparquet.readthedocs.io/en/latest/necessary>`__ (>= 0.0.6) for parquet-based storage. The `snappy <https://pypi.python.org/pypi/python-snappy>`__ and `brotli <https://pypi.python.org/pypi/brotlipy>`__ are available for compression support.
 * `SQLAlchemy <http://www.sqlalchemy.org>`__: for SQL database support. Version 0.8.1 or higher recommended. Besides SQLAlchemy, you also need a database specific driver. You can find an overview of supported drivers for each SQL dialect in the `SQLAlchemy docs <http://docs.sqlalchemy.org/en/latest/dialects/index.html>`__. Some common drivers are:
 
   * `psycopg2 <http://initd.org/psycopg/>`__: for PostgreSQL

doc/source/io.rst

@@ -4554,7 +4554,7 @@ Parquet
 
 .. versionadded:: 0.21.0
 
-`Parquet <https://parquet.apache.org/`__ provides a partitioned binary columnar serialization for data frames. It is designed to
+`Apache Parquet <https://parquet.apache.org/>`__ provides a partitioned binary columnar serialization for data frames. It is designed to
 make reading and writing data frames efficient, and to make sharing data across data analysis
 languages easy. Parquet can use a variety of compression techniques to shrink the file size as much as possible
 while still maintaining good read performance.
@@ -4575,7 +4575,7 @@ You can specifiy an ``engine`` to direct the serialization. This can be one of `
 If the engine is NOT specified, then the ``pd.options.io.parquet.engine`` option is checked; if this is also ``auto``, then
 then ``pyarrow`` is tried, and falling back to ``fastparquet``.
 
-See the documentation for `pyarrow <http://arrow.apache.org/docs/python/`__ and `fastparquet <https://fastparquet.readthedocs.io/en/latest/>`__
+See the documentation for `pyarrow <http://arrow.apache.org/docs/python/>`__ and `fastparquet <https://fastparquet.readthedocs.io/en/latest/>`__
 
 .. note::
 

doc/source/whatsnew/v0.21.0.txt

@@ -9,6 +9,8 @@ users upgrade to this version.
 
 Highlights include:
 
+- Integration with `Apache Parquet <https://parquet.apache.org/>`__, including a new top-level :func:`pd.read_parquet` and :func:`DataFrame.to_parquet` method, see :ref:`here <io.parquet>`.
+
 Check the :ref:`API Changes <whatsnew_0210.api_breaking>` and :ref:`deprecations <whatsnew_0210.deprecations>` before updating.
 
 .. contents:: What's new in v0.21.0
@@ -79,7 +81,7 @@ Other Enhancements
 - :func:`date_range` now accepts 'YS' in addition to 'AS' as an alias for start of year (:issue:`9313`)
 - :func:`date_range` now accepts 'Y' in addition to 'A' as an alias for end of year (:issue:`9313`)
 - :func:`read_html` handles colspan and rowspan arguments and attempts to infer a header if the header is not explicitly specified (:issue:`17054`)
-- Integration with Apache Parquet, including a new top-level ``pd.read_parquet()`` and ``DataFrame.to_parquet()`` method, see :ref:`here <io.parquet>`.
+- Integration with `Apache Parquet <https://parquet.apache.org/>`__, including a new top-level :func:`pd.read_parquet` and :func:`DataFrame.to_parquet` method, see :ref:`here <io.parquet>`.
 
 .. _whatsnew_0210.api_breaking: