Merge branch 'master' into PR_TOOL_MERGE_PR_17453

doc/source/whatsnew/v0.22.0.txt

@@ -3,143 +3,9 @@
 v0.22.0 (December 29, 2017)
 ---------------------------
 
-This is a major release from 0.21.1 and includes a number of API changes,
-deprecations, new features, enhancements, and performance improvements along
-with a large number of bug fixes. We recommend that all users upgrade to this
-version.
-
-.. _whatsnew_0220.enhancements:
-
-New features
-~~~~~~~~~~~~
-
--
--
--
-
-
-.. _whatsnew_0210.enhancements.get_dummies_dtype:
-
-``get_dummies`` now supports ``dtype`` argument
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-The :func:`get_dummies` now accepts a ``dtype`` argument, which specifies a dtype for the new columns. The default remains uint8. (:issue:`18330`)
-
-.. ipython:: python
-
- df = pd.DataFrame({'a': [1, 2], 'b': [3, 4], 'c': [5, 6]})
- pd.get_dummies(df, columns=['c']).dtypes
- pd.get_dummies(df, columns=['c'], dtype=bool).dtypes
-
-
-.. _whatsnew_0220.enhancements.merge_on_columns_and_levels:
-
-Merging on a combination of columns and index levels
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-Strings passed to :meth:`DataFrame.merge` as the ``on``, ``left_on``, and ``right_on``
-parameters may now refer to either column names or index level names.
-This enables merging ``DataFrame`` instances on a combination of index levels
-and columns without resetting indexes. See the :ref:`Merge on columns and
-levels <merging.merge_on_columns_and_levels>` documentation section.
-(:issue:`14355`)
-
-.. ipython:: python
-
- left_index = pd.Index(['K0', 'K0', 'K1', 'K2'], name='key1')
-
- left = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
- 'B': ['B0', 'B1', 'B2', 'B3'],
- 'key2': ['K0', 'K1', 'K0', 'K1']},
- index=left_index)
-
- right_index = pd.Index(['K0', 'K1', 'K2', 'K2'], name='key1')
-
- right = pd.DataFrame({'C': ['C0', 'C1', 'C2', 'C3'],
- 'D': ['D0', 'D1', 'D2', 'D3'],
- 'key2': ['K0', 'K0', 'K0', 'K1']},
- index=right_index)
-
- left.merge(right, on=['key1', 'key2'])
-
-
-.. _whatsnew_0220.enhancements.ran_inf:
-
-``.rank()`` handles ``inf`` values when ``NaN`` are present
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-
-In previous versions, ``.rank()`` would assign ``inf`` elements ``NaN`` as their ranks. Now ranks are calculated properly. (:issue:`6945`)
-
-.. ipython:: python
-
- s = pd.Series([-np.inf, 0, 1, np.nan, np.inf])
- s
-
-Previous Behavior:
-
-.. code-block:: ipython
-
- In [11]: s.rank()
- Out[11]:
- 0 1.0
- 1 2.0
- 2 3.0
- 3 NaN
- 4 NaN
- dtype: float64
-
-Current Behavior
-
-.. ipython:: python
-
- s.rank()
-
-Furthermore, previously if you rank ``inf`` or ``-inf`` values together with ``NaN`` values, the calculation won't distinguish ``NaN`` from infinity when using 'top' or 'bottom' argument.
-
-.. ipython:: python
-
- s = pd.Series([np.nan, np.nan, -np.inf, -np.inf])
- s
-
-Previous Behavior:
-
-.. code-block:: ipython
-
- In [15]: s.rank(na_option='top')
- Out[15]:
- 0 2.5
- 1 2.5
- 2 2.5
- 3 2.5
- dtype: float64
-
-Current Behavior
-
-.. ipython:: python
-
- s.rank(na_option='top')
-
-.. _whatsnew_0220.enhancements.other:
-
-Other Enhancements
-^^^^^^^^^^^^^^^^^^
-
-- Better support for :func:`Dataframe.style.to_excel` output with the ``xlsxwriter`` engine. (:issue:`16149`)
-- :func:`pandas.tseries.frequencies.to_offset` now accepts leading '+' signs e.g. '+1h'. (:issue:`18171`)
-- :func:`MultiIndex.unique` now supports the ``level=`` argument, to get unique values from a specific index level (:issue:`17896`)
-- :class:`pandas.io.formats.style.Styler` now has method ``hide_index()`` to determine whether the index will be rendered in ouptut (:issue:`14194`)
-- :class:`pandas.io.formats.style.Styler` now has method ``hide_columns()`` to determine whether columns will be hidden in output (:issue:`14194`)
-- Improved wording of ``ValueError`` raised in :func:`to_datetime` when ``unit=`` is passed with a non-convertible value (:issue:`14350`)
-- :func:`Series.fillna` now accepts a Series or a dict as a ``value`` for a categorical dtype (:issue:`17033`)
-- :func:`pandas.read_clipboard` updated to use qtpy, falling back to PyQt5 and then PyQt4, adding compatibility with Python3 and multiple python-qt bindings (:issue:`17722`)
-- Improved wording of ``ValueError`` raised in :func:`read_csv` when the ``usecols`` argument cannot match all columns. (:issue:`17301`)
-- :func:`DataFrame.corrwith` now silently drops non-numeric columns when passed a Series. Before, an exception was raised (:issue:`18570`).
-- :class:`IntervalIndex` now supports time zone aware ``Interval`` objects (:issue:`18537`, :issue:`18538`)
-- :func:`Series` / :func:`DataFrame` tab completion also returns identifiers in the first level of a :func:`MultiIndex`. (:issue:`16326`)
-- :func:`read_excel()` has gained the ``nrows`` parameter (:issue:`16645`)
-- :func:``DataFrame.to_json`` and ``Series.to_json`` now accept an ``index`` argument which allows the user to exclude the index from the JSON output (:issue:`17394`)
-- ``IntervalIndex.to_tuples()`` has gained the ``na_tuple`` parameter to control whether NA is returned as a tuple of NA, or NA itself (:issue:`18756`)
-- :func: groupby.is_monotonic_increasing and :func: .is_monotonic_decreasing extend :func: Series.is_monotonic_increasing to groups, returning whether each group is monotonically increasing or decreasing, respectively. (:issue:`17015`)
+This is a major release from 0.21.1 and includes a single, API-breaking change.
+We recommend that all users upgrade to this version after carefully reading the
+release note (singular!).
 
 .. _whatsnew_0220.api_breaking:
 
@@ -313,8 +179,34 @@ entirely valid.
 
 .. ipython:: python
 
+<<<<<<< HEAD
+ s.rank(na_option='top')
+
+.. _whatsnew_0220.enhancements.other:
+
+Other Enhancements
+^^^^^^^^^^^^^^^^^^
+
+- Better support for :func:`Dataframe.style.to_excel` output with the ``xlsxwriter`` engine. (:issue:`16149`)
+- :func:`pandas.tseries.frequencies.to_offset` now accepts leading '+' signs e.g. '+1h'. (:issue:`18171`)
+- :func:`MultiIndex.unique` now supports the ``level=`` argument, to get unique values from a specific index level (:issue:`17896`)
+- :class:`pandas.io.formats.style.Styler` now has method ``hide_index()`` to determine whether the index will be rendered in ouptut (:issue:`14194`)
+- :class:`pandas.io.formats.style.Styler` now has method ``hide_columns()`` to determine whether columns will be hidden in output (:issue:`14194`)
+- Improved wording of ``ValueError`` raised in :func:`to_datetime` when ``unit=`` is passed with a non-convertible value (:issue:`14350`)
+- :func:`Series.fillna` now accepts a Series or a dict as a ``value`` for a categorical dtype (:issue:`17033`)
+- :func:`pandas.read_clipboard` updated to use qtpy, falling back to PyQt5 and then PyQt4, adding compatibility with Python3 and multiple python-qt bindings (:issue:`17722`)
+- Improved wording of ``ValueError`` raised in :func:`read_csv` when the ``usecols`` argument cannot match all columns. (:issue:`17301`)
+- :func:`DataFrame.corrwith` now silently drops non-numeric columns when passed a Series. Before, an exception was raised (:issue:`18570`).
+- :class:`IntervalIndex` now supports time zone aware ``Interval`` objects (:issue:`18537`, :issue:`18538`)
+- :func:`Series` / :func:`DataFrame` tab completion also returns identifiers in the first level of a :func:`MultiIndex`. (:issue:`16326`)
+- :func:`read_excel()` has gained the ``nrows`` parameter (:issue:`16645`)
+- :func:``DataFrame.to_json`` and ``Series.to_json`` now accept an ``index`` argument which allows the user to exclude the index from the JSON output (:issue:`17394`)
+- ``IntervalIndex.to_tuples()`` has gained the ``na_tuple`` parameter to control whether NA is returned as a tuple of NA, or NA itself (:issue:`18756`)
+- :func: groupby.is_monotonic_increasing and :func: .is_monotonic_decreasing extend :func: Series.is_monotonic_increasing to groups, returning whether each group is monotonically increasing or decreasing, respectively. (:issue:`17015`)
+=======
  idx = pd.DatetimeIndex(['2017-01-01', '2017-01-02'])
  pd.Series([1, 2], index=idx).resample("12H").sum()
+>>>>>>> master
 
 Once again, the ``min_count`` keyword is available to restore the 0.21 behavior.