Updates

.gitignore

@@ -88,8 +88,9 @@ scikits
 *.c
 *.cpp
 
-# Performance Testing #
-#######################
+# Unit / Performance Testing #
+##############################
+.pytest_cache/
 asv_bench/env/
 asv_bench/html/
 asv_bench/results/

ci/environment-dev.yaml

@@ -5,6 +5,7 @@ channels:
 dependencies:
   - Cython
   - NumPy
+  - flake8
   - moto
   - pytest>=3.1
   - python-dateutil>=2.5.0

ci/requirements-3.6_DOC.run

@@ -5,7 +5,7 @@ sphinx
 nbconvert
 nbformat
 notebook
-matplotlib
+matplotlib=2.1*
 seaborn
 scipy
 lxml

ci/requirements_dev.txt

@@ -2,9 +2,10 @@
 # Do not modify directly
 Cython
 NumPy
+flake8
 moto
 pytest>=3.1
 python-dateutil>=2.5.0
 pytz
 setuptools>=3.3
-sphinx
+sphinx

doc/make.py

@@ -11,6 +11,7 @@
     $ python make.py html
     $ python make.py latex
 """
+import importlib
 import sys
 import os
 import shutil
@@ -20,8 +21,6 @@
 import webbrowser
 import jinja2
 
-import pandas
-
 
 DOC_PATH = os.path.dirname(os.path.abspath(__file__))
 SOURCE_PATH = os.path.join(DOC_PATH, 'source')
@@ -134,7 +133,7 @@ def _process_single_doc(self, single_doc):
             self.single_doc = single_doc
         elif single_doc is not None:
             try:
-                obj = pandas
+                obj = pandas  # noqa: F821
                 for name in single_doc.split('.'):
                     obj = getattr(obj, name)
             except AttributeError:
@@ -332,7 +331,7 @@ def main():
                                  'compile, e.g. "indexing", "DataFrame.join"'))
     argparser.add_argument('--python-path',
                            type=str,
-                           default=os.path.join(DOC_PATH, '..'),
+                           default=os.path.dirname(DOC_PATH),
                            help='path')
     argparser.add_argument('-v', action='count', dest='verbosity', default=0,
                            help=('increase verbosity (can be repeated), '
@@ -343,7 +342,13 @@ def main():
         raise ValueError('Unknown command {}. Available options: {}'.format(
             args.command, ', '.join(cmds)))
 
+    # Below we update both os.environ and sys.path. The former is used by
+    # external libraries (namely Sphinx) to compile this module and resolve
+    # the import of `python_path` correctly. The latter is used to resolve
+    # the import within the module, injecting it into the global namespace
     os.environ['PYTHONPATH'] = args.python_path
+    sys.path.append(args.python_path)
+    globals()['pandas'] = importlib.import_module('pandas')
 
     builder = DocBuilder(args.num_jobs, not args.no_api, args.single,
                          args.verbosity)

doc/source/api.rst

@@ -551,7 +551,6 @@ These can be accessed like ``Series.dt.<property>``.
    Series.dt.weekofyear
    Series.dt.dayofweek
    Series.dt.weekday
-   Series.dt.weekday_name
    Series.dt.dayofyear
    Series.dt.quarter
    Series.dt.is_month_start
@@ -581,6 +580,8 @@ These can be accessed like ``Series.dt.<property>``.
    Series.dt.round
    Series.dt.floor
    Series.dt.ceil
+   Series.dt.month_name
+   Series.dt.day_name
 
 **Timedelta Properties**
 
@@ -1723,7 +1724,6 @@ Time/Date Components
    DatetimeIndex.week
    DatetimeIndex.dayofweek
    DatetimeIndex.weekday
-   DatetimeIndex.weekday_name
    DatetimeIndex.quarter
    DatetimeIndex.tz
    DatetimeIndex.freq
@@ -1759,6 +1759,8 @@ Time-specific operations
    DatetimeIndex.round
    DatetimeIndex.floor
    DatetimeIndex.ceil
+   DatetimeIndex.month_name
+   DatetimeIndex.day_name
 
 Conversion
 ~~~~~~~~~~
@@ -1940,7 +1942,6 @@ Properties
     Timestamp.tzinfo
     Timestamp.value
     Timestamp.week
-    Timestamp.weekday_name
     Timestamp.weekofyear
     Timestamp.year
 
@@ -1954,6 +1955,7 @@ Methods
     Timestamp.combine
     Timestamp.ctime
     Timestamp.date
+    Timestamp.day_name
     Timestamp.dst
     Timestamp.floor
     Timestamp.freq
@@ -1963,6 +1965,7 @@ Methods
     Timestamp.isocalendar
     Timestamp.isoformat
     Timestamp.isoweekday
+    Timestamp.month_name
     Timestamp.normalize
     Timestamp.now
     Timestamp.replace

doc/source/categorical.rst

@@ -177,7 +177,7 @@ are consistent among all columns.
 .. note::
 
     To perform table-wise conversion, where all labels in the entire ``DataFrame`` are used as
-    categories for each column, the ``categories`` parameter can be determined programatically by
+    categories for each column, the ``categories`` parameter can be determined programmatically by
     ``categories = pd.unique(df.values.ravel())``.
 
 If you already have ``codes`` and ``categories``, you can use the 

doc/source/conf.py

@@ -63,6 +63,7 @@
               'ipython_sphinxext.ipython_console_highlighting',
               # lowercase didn't work
               'IPython.sphinxext.ipython_console_highlighting',
+              'matplotlib.sphinxext.plot_directive',
               'sphinx.ext.intersphinx',
               'sphinx.ext.coverage',
               'sphinx.ext.mathjax',
@@ -85,6 +86,14 @@
 if any(re.match("\s*api\s*", l) for l in index_rst_lines):
     autosummary_generate = True
 
+# matplotlib plot directive
+plot_include_source = True
+plot_formats = [("png", 90)]
+plot_html_show_formats = False
+plot_html_show_source_link = False
+plot_pre_code = """import numpy as np
+import pandas as pd"""
+
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['../_templates']
 

doc/source/contributing.rst

@@ -351,8 +351,10 @@ Some other important things to know about the docs:
 
       pandoc doc/source/contributing.rst -t markdown_github > CONTRIBUTING.md
 
-The utility script ``scripts/api_rst_coverage.py`` can be used to compare
-the list of methods documented in ``doc/source/api.rst`` (which is used to generate
+The utility script ``scripts/validate_docstrings.py`` can be used to get a csv
+summary of the API documentation. And also validate common errors in the docstring
+of a specific class, function or method. The summary also compares the list of
+methods documented in ``doc/source/api.rst`` (which is used to generate
 the `API Reference <http://pandas.pydata.org/pandas-docs/stable/api.html>`_ page)
 and the actual public methods.
 This will identify methods documented in ``doc/source/api.rst`` that are not actually

doc/source/developer.rst

@@ -140,46 +140,3 @@ As an example of fully-formed metadata:
          'metadata': None}
     ],
     'pandas_version': '0.20.0'}
-
-.. _developer.register-accessors:
-
-Registering Custom Accessors
-----------------------------
-
-Libraries can use the decorators
-:func:`pandas.api.extensions.register_dataframe_accessor`,
-:func:`pandas.api.extensions.register_series_accessor`, and
-:func:`pandas.api.extensions.register_index_accessor`, to add additional "namespaces" to
-pandas objects. All of these follow a similar convention: you decorate a class, providing the name of attribute to add. The
-class's `__init__` method gets the object being decorated. For example:
-
-.. code-block:: python
-
-   @pd.api.extensions.register_dataframe_accessor("geo")
-   class GeoAccessor(object):
-       def __init__(self, pandas_obj):
-           self._obj = pandas_obj
-
-       @property
-       def center(self):
-           # return the geographic center point of this DataFarme
-           lon = self._obj.latitude
-           lat = self._obj.longitude
-           return (float(lon.mean()), float(lat.mean()))
-
-       def plot(self):
-           # plot this array's data on a map, e.g., using Cartopy
-           pass
-
-Now users can access your methods using the `geo` namespace:
-
-      >>> ds = pd.DataFrame({'longitude': np.linspace(0, 10),
-      ...                    'latitude': np.linspace(0, 20)})
-      >>> ds.geo.center
-      (5.0, 10.0)
-      >>> ds.geo.plot()
-      # plots data on a map
-
-This can be a convenient way to extend pandas objects without subclassing them.
-If you write a custom accessor, make a pull request adding it to our
-:ref:`ecosystem` page.

doc/source/ecosystem.rst

@@ -262,3 +262,38 @@ Data validation
 
 Engarde is a lightweight library used to explicitly state your assumptions abour your datasets
 and check that they're *actually* true.
+
+.. _ecosystem.extensions:
+
+Extension Data Types
+--------------------
+
+Pandas provides an interface for defining
+:ref:`extension types <extending.extension-types>` to extend NumPy's type
+system. The following libraries implement that interface to provide types not
+found in NumPy or pandas, which work well with pandas' data containers.
+
+`cyberpandas`_
+~~~~~~~~~~~~~~
+
+Cyberpandas provides an extension type for storing arrays of IP Addresses. These
+arrays can be stored inside pandas' Series and DataFrame.
+
+.. _ecosystem.accessors:
+
+Accessors
+---------
+
+A directory of projects providing
+:ref:`extension accessors <extending.register-accessors>`. This is for users to
+discover new accessors and for library authors to coordinate on the namespace.
+
+============== ========== =========================
+Library        Accessor   Classes
+============== ========== =========================
+`cyberpandas`_ ``ip``     ``Series``
+`pdvega`_      ``vgplot`` ``Series``, ``DataFrame``
+============== ========== =========================
+
+.. _cyberpandas: https://cyberpandas.readthedocs.io/en/latest
+.. _pdvega: https://jakevdp.github.io/pdvega/