Merge branch 'master' into dep_keyword

Author: EricChea

.travis.yml

@@ -50,9 +50,6 @@ matrix:
           packages:
           - python-gtk2
     # In allow_failures
-    - dist: trusty
-      env:
-        - JOB="3.5" TEST_ARGS="--skip-slow --skip-network"
     - dist: trusty
       env:
         - JOB="3.6" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate" CONDA_FORGE=true COVERAGE=true
@@ -63,36 +60,26 @@ matrix:
     # In allow_failures
     - dist: trusty
       env:
-        - JOB="3.6_PIP_BUILD_TEST" TEST_ARGS="--skip-slow" PIP_BUILD_TEST=true
+        - JOB="3.6_NUMPY_DEV" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate"
       addons:
         apt:
           packages:
           - xsel
     # In allow_failures
-    - dist: trusty
-      env:
-        - JOB="3.6_NUMPY_DEV" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate"
-    # In allow_failures
     - dist: trusty
       env:
         - JOB="3.6_DOC" DOC=true
     allow_failures:
-      - dist: trusty
-        env:
-          - JOB="3.5" TEST_ARGS="--skip-slow --skip-network"
       - dist: trusty
         env:
           - JOB="2.7_SLOW" SLOW=true
       - dist: trusty
         env:
-          - JOB="3.6_PIP_BUILD_TEST" TEST_ARGS="--skip-slow" PIP_BUILD_TEST=true
+          - JOB="3.6_NUMPY_DEV" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate"
         addons:
           apt:
             packages:
             - xsel
-      - dist: trusty
-        env:
-          - JOB="3.6_NUMPY_DEV" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate"
       - dist: trusty
         env:
           - JOB="3.6_DOC" DOC=true

ci/install_travis.sh

@@ -115,15 +115,6 @@ if [ "$COVERAGE" ]; then
     pip install coverage pytest-cov
 fi
 
-echo
-if [ -z "$PIP_BUILD_TEST" ] ; then
-
-    # build but don't install
-    echo "[build em]"
-    time python setup.py build_ext --inplace || exit 1
-
-fi
-
 # we may have run installations
 echo
 echo "[conda installs]"
@@ -161,23 +152,8 @@ conda list pandas
 pip list --format columns |grep pandas
 
 # build and install
-echo
-
-if [ "$PIP_BUILD_TEST" ]; then
-
-    # build & install testing
-    echo "[building release]"
-    time bash scripts/build_dist_for_release.sh || exit 1
-    conda uninstall -y cython
-    time pip install dist/*tar.gz || exit 1
-
-else
-
-    # install our pandas
-    echo "[running setup.py develop]"
-    python setup.py develop  || exit 1
-
-fi
+echo "[running setup.py develop]"
+python setup.py develop  || exit 1
 
 echo
 echo "[show pandas]"

ci/requirements-3.6_PIP_BUILD_TEST.build

@@ -7,4 +7,4 @@ pytest>=3.1
 python-dateutil>=2.5.0
 pytz
 setuptools>=3.3
-sphinx
+sphinx=1.5*

ci/requirements-3.6_PIP_BUILD_TEST.pip

@@ -12,29 +12,18 @@ if [ -n "$LOCALE_OVERRIDE" ]; then
     python -c "$pycmd"
 fi
 
+# Enforce absent network during testing by faking a proxy
+if echo "$TEST_ARGS" | grep -e --skip-network -q; then
+    export http_proxy=http://1.2.3.4 https_proxy=http://1.2.3.4;
+fi
+
 # Workaround for pytest-xdist flaky collection order
 # https://github.com/pytest-dev/pytest/issues/920
 # https://github.com/pytest-dev/pytest/issues/1075
 export PYTHONHASHSEED=$(python -c 'import random; print(random.randint(1, 4294967295))')
 echo PYTHONHASHSEED=$PYTHONHASHSEED
 
-if [ "$PIP_BUILD_TEST" ] ; then
-    echo "[build-test]"
-
-    echo "[env]"
-    pip list --format columns |grep pandas
-
-    echo "[running]"
-    cd /tmp
-    unset PYTHONPATH
-
-    echo "[build-test: single]"
-    python -c 'import pandas; pandas.test(["--skip-slow", "--skip-network", "-r xX", "-m single"])'
-
-    echo "[build-test: not single]"
-    python -c 'import pandas; pandas.test(["-n 2", "--skip-slow", "--skip-network", "-r xX", "-m not single"])'
-
-elif [ "$DOC" ]; then
+if [ "$DOC" ]; then
     echo "We are not running pytest as this is a doc-build"
 
 elif [ "$COVERAGE" ]; then

ci/requirements-3.6_PIP_BUILD_TEST.sh

@@ -16,10 +16,12 @@ if [ "$SLOW" ]; then
     TEST_ARGS="--only-slow --skip-network"
 fi
 
-if [ "$PIP_BUILD_TEST" ]; then
-    echo "We are not running pytest as this is a build test."
+# Enforce absent network during testing by faking a proxy
+if echo "$TEST_ARGS" | grep -e --skip-network -q; then
+    export http_proxy=http://1.2.3.4 https_proxy=http://1.2.3.4;
+fi
 
-elif [ "$DOC" ]; then
+if [ "$DOC" ]; then
     echo "We are not running pytest as this is a doc-build"
 
 elif [ "$COVERAGE" ]; then

ci/requirements_dev.txt

@@ -274,7 +274,7 @@ Passing a list of labels or tuples works similar to reindexing:
 
    df.loc[[('bar', 'two'), ('qux', 'one')]]
 
-.. info::
+.. note::
 
    It is important to note that tuples and lists are not treated identically
    in pandas when it comes to indexing. Whereas a tuple is interpreted as one

ci/script_multi.sh

@@ -1682,6 +1682,16 @@ MultiIndex Components
    MultiIndex.reorder_levels
    MultiIndex.remove_unused_levels
 
+MultiIndex Selecting
+~~~~~~~~~~~~~~~~~~~~
+
+.. autosummary::
+   :toctree: generated/
+
+   MultiIndex.get_loc
+   MultiIndex.get_indexer
+   MultiIndex.get_level_values
+
 .. _api.datetimeindex:
 
 DatetimeIndex

ci/script_single.sh

@@ -506,7 +506,7 @@ to be inserted (for example, a ``Series`` or NumPy array), or a function
 of one argument to be called on the ``DataFrame``. A *copy* of the original
 DataFrame is returned, with the new values inserted.
 
-.. versionmodified:: 0.23.0
+.. versionchanged:: 0.23.0
 
 Starting with Python 3.6 the order of ``**kwargs`` is preserved. This allows
 for *dependent* assignment, where an expression later in ``**kwargs`` can refer

doc/source/advanced.rst

@@ -2262,6 +2262,7 @@ is not round-trippable, nor are any names beginning with 'level_' within a
 indicate missing values and the subsequent read cannot distinguish the intent.
 
 .. ipython:: python
+   :okwarning:
 
    df.index.name = 'index'
    df.to_json('test.json', orient='table')

doc/source/api.rst

@@ -283,6 +283,20 @@ Rounded division (floor-division) of a ``timedelta64[ns]`` Series by a scalar
    td // pd.Timedelta(days=3, hours=4)
    pd.Timedelta(days=3, hours=4) // td
 
+.. _timedeltas.mod_divmod:
+
+The mod (%) and divmod operations are defined for ``Timedelta`` when operating with another timedelta-like or with a numeric argument.
+
+.. ipython:: python
+
+   pd.Timedelta(hours=37) % datetime.timedelta(hours=2)
+
+   # divmod against a timedelta-like returns a pair (int, Timedelta)
+   divmod(datetime.timedelta(hours=2), pd.Timedelta(minutes=11))
+
+   # divmod against a numeric returns a pair (Timedelta, Timedelta)
+   divmod(pd.Timedelta(hours=25), 86400000000000)
+
 Attributes
 ----------
 

doc/source/dsintro.rst

@@ -411,15 +411,23 @@ N Dimensional Panels (Experimental)
 Adding experimental support for Panel4D and factory functions to create n-dimensional named panels.
 :ref:`Docs <dsintro.panel4d>` for NDim. Here is a taste of what to expect.
 
-     .. ipython:: python
-        :okwarning:
-
-        p4d = Panel4D(randn(2, 2, 5, 4),
-              labels=['Label1','Label2'],
-              items=['Item1', 'Item2'],
-              major_axis=date_range('1/1/2000', periods=5),
-              minor_axis=['A', 'B', 'C', 'D'])
-        p4d
+.. code-block:: ipython
+
+  In [58]: p4d = Panel4D(randn(2, 2, 5, 4),
+    ....:       labels=['Label1','Label2'],
+    ....:       items=['Item1', 'Item2'],
+    ....:       major_axis=date_range('1/1/2000', periods=5),
+    ....:       minor_axis=['A', 'B', 'C', 'D'])
+    ....:
+
+  In [59]: p4d
+  Out[59]:
+  <class 'pandas.core.panelnd.Panel4D'>
+  Dimensions: 2 (labels) x 2 (items) x 5 (major_axis) x 4 (minor_axis)
+  Labels axis: Label1 to Label2
+  Items axis: Item1 to Item2
+  Major_axis axis: 2000-01-01 00:00:00 to 2000-01-05 00:00:00
+  Minor_axis axis: A to D
 
 
 

doc/source/io.rst

@@ -140,25 +140,44 @@ API changes
   applied would be called with an empty ``Series`` to guess whether a
   ``Series`` or ``DataFrame`` should be returned:
 
-  .. ipython:: python
+  .. code-block:: ipython
+
+    In [32]: def applied_func(col):
+      ....:    print("Apply function being called with: ", col)
+      ....:    return col.sum()
+      ....:
 
-     def applied_func(col):
-        print("Apply function being called with: ", col)
-        return col.sum()
+    In [33]: empty = DataFrame(columns=['a', 'b'])
 
-     empty = DataFrame(columns=['a', 'b'])
-     empty.apply(applied_func)
+    In [34]: empty.apply(applied_func)
+    Apply function being called with:  Series([], Length: 0, dtype: float64)
+    Out[34]:
+    a   NaN
+    b   NaN
+    Length: 2, dtype: float64
 
   Now, when ``apply`` is called on an empty ``DataFrame``: if the ``reduce``
   argument is ``True`` a ``Series`` will returned, if it is ``False`` a
   ``DataFrame`` will be returned, and if it is ``None`` (the default) the
   function being applied will be called with an empty series to try and guess
   the return type.
 
-  .. ipython:: python
+  .. code-block:: ipython
+
+    In [35]: empty.apply(applied_func, reduce=True)
+    Out[35]:
+    a   NaN
+    b   NaN
+    Length: 2, dtype: float64
+
+    In [36]: empty.apply(applied_func, reduce=False)
+    Out[36]:
+    Empty DataFrame
+    Columns: [a, b]
+    Index: []
+
+    [0 rows x 2 columns]
 
-     empty.apply(applied_func, reduce=True)
-     empty.apply(applied_func, reduce=False)
 
 Prior Version Deprecations/Changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

doc/source/timedeltas.rst

@@ -1044,7 +1044,7 @@ Other:
 
       idx = MultiIndex.from_product([['a'], range(3), list("pqr")], names=['foo', 'bar', 'baz'])
       idx.set_names('qux', level=0)
-      idx.set_names(['qux','baz'], level=[0,1])
+      idx.set_names(['qux','corge'], level=[0,1])
       idx.set_levels(['a','b','c'], level='bar')
       idx.set_levels([['a','b','c'],[1,2,3]], level=[1,2])
 

doc/source/whatsnew/v0.10.0.txt

@@ -894,17 +894,14 @@ imported. Matplotlib plot methods (``plt.plot``, ``ax.plot``, ...), will not
 nicely format the x-axis for ``DatetimeIndex`` or ``PeriodIndex`` values. You
 must explicitly register these methods:
 
-.. ipython:: python
-
-   from pandas.tseries import converter
-   converter.register()
-
-   fig, ax = plt.subplots()
-   plt.plot(pd.date_range('2017', periods=6), range(6))
-
 Pandas built-in ``Series.plot`` and ``DataFrame.plot`` *will* register these
 converters on first-use (:issue:17710).
 
+.. note::
+
+  This change has been temporarily reverted in pandas 0.21.1,
+  for more details see :ref:`here <whatsnew_0211.converters>`.
+
 .. _whatsnew_0210.api:
 
 Other API Changes