Merge commit 'v0.16.1-97-gbc7d48f' into debian

* commit 'v0.16.1-97-gbc7d48f': (56 commits)
  disable some deps on 3.2 build
  Fix meantim typo
  DOC: use current ipython in doc build
  PERF: write basic datetimes faster pandas-dev#10271
  TST: fix for bottleneck >= 1.0 nansum behavior, xref pandas-dev#9422
  add numba example to enhancingperf.rst
  BUG: SparseSeries constructor ignores input data name
  BUG: Raise TypeError only if key DataFrame is not empty pandas-dev#10126
  ENH: groupby.apply for Categorical should preserve categories (closes pandas-dev#10138)
  DOC: add in whatsnew/0.17.0.txt
  DOC: move whatsnew from 0.17.0 -> 0.16.2
  BUG:  Holiday(..) with both offset and observance raises NotImplementedError pandas-dev#10217
  BUG: Index.union cannot handle array-likes
  BUG: SparseSeries.abs() resets name
  BUG: Series arithmetic methods incorrectly hold name
  ENH: Don't infer WOM-5MON if we don't support it (pandas-dev#9425)
  BUG: Series.align resets name when fill_value is specified
  BUG: GroupBy.get_group raises ValueError when group key contains NaT
  Close mysql connection in TestXMySQL to prevent tests freezing
  BUG: plot doesnt default to matplotlib axes.grid setting (pandas-dev#9792)
  ...

README.md

@@ -123,7 +123,7 @@ conda install pandas
      - xlrd >= 0.9.0
   - [XlsxWriter](https://pypi.python.org/pypi/XlsxWriter)
      - Alternative Excel writer.
-- [Google bq Command Line Tool](https://developers.google.com/bigquery/bq-command-line-tool/)
+- [Google bq Command Line Tool](https://cloud.google.com/bigquery/bq-command-line-tool)
   - Needed for `pandas.io.gbq`
 - [boto](https://pypi.python.org/pypi/boto): necessary for Amazon S3 access.
 - One of the following combinations of libraries is needed to use the

ci/build_docs.sh

@@ -13,9 +13,10 @@ fi
 
 
 if [ x"$DOC_BUILD" != x"" ]; then
-    # we're running network tests, let's build the docs in the meantim
+
+    # we're running network tests, let's build the docs in the meantime
     echo "Will build docs"
-    pip install sphinx==1.1.3 ipython==1.1.0
+    conda install sphinx==1.1.3 ipython
 
     mv "$TRAVIS_BUILD_DIR"/doc /tmp
     cd /tmp/doc

ci/requirements-3.2.txt

@@ -1,15 +1,4 @@
 python-dateutil==2.1
 pytz==2013b
-xlsxwriter==0.4.6
-xlrd==0.9.2
 numpy==1.7.1
 cython==0.19.1
-numexpr==2.1
-tables==3.0.0
-matplotlib==1.2.1
-patsy==0.1.0
-lxml==3.2.1
-html5lib
-scipy==0.12.0
-beautifulsoup4==4.2.1
-statsmodels==0.5.0

doc/_templates/autosummary/accessor.rst

@@ -0,0 +1,6 @@
+{{ fullname }}
+{{ underline }}
+
+.. currentmodule:: {{ module.split('.')[0] }}
+
+.. automethod:: {{ [module.split('.')[1], objname]|join('.') }}

doc/_templates/autosummary/class_without_autosummary.rst

@@ -0,0 +1,6 @@
+{{ fullname }}
+{{ underline }}
+
+.. currentmodule:: {{ module }}
+
+.. autoclass:: {{ objname }}

doc/source/10min.rst

@@ -6,18 +6,16 @@
    :suppress:
 
    import numpy as np
-   import random
+   import pandas as pd
    import os
    np.random.seed(123456)
-   from pandas import options
-   import pandas as pd
    np.set_printoptions(precision=4, suppress=True)
    import matplotlib
    try:
       matplotlib.style.use('ggplot')
    except AttributeError:
-      options.display.mpl_style = 'default'
-   options.display.max_rows=15
+      pd.options.display.mpl_style = 'default'
+   pd.options.display.max_rows = 15
 
    #### portions of this were borrowed from the
    #### Pandas cheatsheet
@@ -298,7 +296,7 @@ Using the :func:`~Series.isin` method for filtering:
 .. ipython:: python
 
    df2 = df.copy()
-   df2['E']=['one', 'one','two','three','four','three']
+   df2['E'] = ['one', 'one','two','three','four','three']
    df2
    df2[df2['E'].isin(['two','four'])]
 
@@ -310,7 +308,7 @@ by the indexes
 
 .. ipython:: python
 
-   s1 = pd.Series([1,2,3,4,5,6],index=pd.date_range('20130102',periods=6))
+   s1 = pd.Series([1,2,3,4,5,6], index=pd.date_range('20130102', periods=6))
    s1
    df['F'] = s1
 
@@ -359,7 +357,7 @@ returns a copy of the data.
 
 .. ipython:: python
 
-   df1 = df.reindex(index=dates[0:4],columns=list(df.columns) + ['E'])
+   df1 = df.reindex(index=dates[0:4], columns=list(df.columns) + ['E'])
    df1.loc[dates[0]:dates[1],'E'] = 1
    df1
 
@@ -409,9 +407,9 @@ In addition, pandas automatically broadcasts along the specified dimension.
 
 .. ipython:: python
 
-   s = pd.Series([1,3,5,np.nan,6,8],index=dates).shift(2)
+   s = pd.Series([1,3,5,np.nan,6,8], index=dates).shift(2)
    s
-   df.sub(s,axis='index')
+   df.sub(s, axis='index')
 
 
 Apply
@@ -431,7 +429,7 @@ See more at :ref:`Histogramming and Discretization <basics.discretization>`
 
 .. ipython:: python
 
-   s = pd.Series(np.random.randint(0,7,size=10))
+   s = pd.Series(np.random.randint(0, 7, size=10))
    s
    s.value_counts()
 
@@ -516,9 +514,9 @@ See the :ref:`Grouping section <groupby>`
 .. ipython:: python
 
    df = pd.DataFrame({'A' : ['foo', 'bar', 'foo', 'bar',
-                            'foo', 'bar', 'foo', 'foo'],
+                             'foo', 'bar', 'foo', 'foo'],
                       'B' : ['one', 'one', 'two', 'three',
-                            'two', 'two', 'one', 'three'],
+                             'two', 'two', 'one', 'three'],
                       'C' : np.random.randn(8),
                       'D' : np.random.randn(8)})
    df