Merge commit 'v0.14.0-213-g741b2fa' into debian

* commit 'v0.14.0-213-g741b2fa': (112 commits)
  BUG: Bug in .loc performing fallback integer indexing with object dtype indices (GH7496)
  BUG: Bug in DataFrame.where with a symmetric shaped frame and a passed other of a DataFrame (GH7506)
  BUG: Bug in timeops with non-aligned Series (GH7500)
  DOC: Fix index error for remote data docs.
  [doc fix] minor update to fix latex usepackage syntax
  Switch if to elif in test_frame.test_to_csv_moar._do_test
  DOC: Clean up docs for io.data.Options.
  CI: 3.4 updates
  ENH: Added method to pandas.data.Options to download all option data for a ticker.
  Fix indentation: switch to four spaces. (GH6643)
  BUG: copy certain interpolate arguments to ensure we can write to them; closes pandas-dev#7295.
  Fix cache key collision and add test for cache key distinctness.
  DOC: v0.14.1.txt fixes
  BUG: Bug in Panel.apply with a multi-index as an axis (GH7469)
  ENH: Cast ndarray-like datetime64 arrays to Index properly
  DOC: Add missing column header in 'baseball.csv'.
  CLN: Simplify boxplot and modify its test
  BUG: astype(float) in Index does the wrong thing
  FIX: Stata writer no longer ignores encoding when writing strings
  FIX: Enable fixed width strings to be read from Stata 13 (117) files
  ...

Author: yarikoptic

.travis.yml

@@ -34,12 +34,6 @@ matrix:
       - CLIPBOARD_GUI=gtk2
       - JOB_NAME: "27_nslow"
       - DOC_BUILD=true # if rst files were changed, build docs in parallel with tests
-    - python: 3.2
-      env:
-      - NOSE_ARGS="not slow and not disabled"
-      - FULL_DEPS=true
-      - CLIPBOARD_GUI=qt4
-      - JOB_NAME: "32_nslow"
     - python: 3.3
       env:
       - NOSE_ARGS="not slow and not disabled"
@@ -48,11 +42,16 @@ matrix:
       - JOB_NAME: "33_nslow"
     - python: 3.4
       env:
-      - EXPERIMENTAL=true
       - NOSE_ARGS="not slow and not disabled"
       - FULL_DEPS=true
       - CLIPBOARD=xsel
       - JOB_NAME: "34_nslow"
+    - python: 3.2
+      env:
+      - NOSE_ARGS="not slow and not disabled"
+      - FULL_DEPS=true
+      - CLIPBOARD_GUI=qt4
+      - JOB_NAME: "32_nslow"
     - python: 2.7
       env:
       - EXPERIMENTAL=true
@@ -62,13 +61,12 @@ matrix:
       - NUMPY_BUILD=master
       - PANDAS_TESTING_MODE="deprecate"
     allow_failures:
-      - python: 3.4
+      - python: 3.2
         env:
-        - EXPERIMENTAL=true
         - NOSE_ARGS="not slow and not disabled"
         - FULL_DEPS=true
-        - CLIPBOARD=xsel
-        - JOB_NAME: "34_nslow"
+        - CLIPBOARD_GUI=qt4
+        - JOB_NAME: "32_nslow"
       - python: 2.7
         env:
         - EXPERIMENTAL=true

ci/install.sh

@@ -38,32 +38,12 @@ echo "home_dir: [$home_dir]"
 # pip==1.5.1
 # setuptools==2.2
 # wheel==0.22
-# nose==1.3.0 (1.3.1 broken for PY3)
+# nose==1.3.3
 
 pip install -I -U pip
 pip install -I -U setuptools
 pip install wheel==0.22
-
-# install nose
-pip uninstall nose -y
-
-if [ -n "$EXPERIMENTAL" ]; then
-
-    # install from master
-    rm -Rf /tmp/nose
-    cd /tmp
-    git clone --branch master https://github.com/nose-devs/nose.git nose
-    cd nose
-    python setup.py install
-    cd $home_dir
-
-else
-
-    # known good version
-    pip install nose==1.3.0
-
-fi
-
+pip install nose==1.3.3
 
 # comment this line to disable the fetching of wheel files
 base_url=http://pandas.pydata.org/pandas-build/dev/wheels

ci/requirements-2.6.txt

@@ -6,10 +6,12 @@ http://www.crummy.com/software/BeautifulSoup/bs4/download/4.2/beautifulsoup4-4.2
 html5lib==1.0b2
 bigquery==2.0.17
 numexpr==1.4.2
-sqlalchemy==0.8.1
+sqlalchemy==0.7.1
+pymysql==0.6.0
+psycopg2==2.5
 scipy==0.11.0
 statsmodels==0.4.3
 xlwt==0.7.5
-openpyxl==1.6.2
+openpyxl==2.0.3
 xlsxwriter==0.4.6
 xlrd==0.9.2

ci/requirements-2.7.txt

@@ -20,3 +20,4 @@ scipy==0.13.3
 beautifulsoup4==4.2.1
 statsmodels==0.5.0
 bigquery==2.0.17
+boto==2.26.1

ci/requirements-3.2.txt

@@ -1,6 +1,5 @@
 python-dateutil==2.1
 pytz==2013b
-openpyxl==1.6.2
 xlsxwriter==0.4.6
 xlrd==0.9.2
 numpy==1.7.1

ci/requirements-3.4.txt

@@ -3,17 +3,17 @@ pytz
 openpyxl
 xlsxwriter
 xlrd
-html5lib==1.0b2
+html5lib
 numpy==1.8.0
 cython==0.20.0
 scipy==0.13.3
-numexpr==2.3
+numexpr==2.4
 tables==3.1.0
 bottleneck==0.8.0
 matplotlib==1.3.1
 patsy
-lxml==3.2.1
+lxml==3.3.5
 sqlalchemy==0.9.3
 pymysql==0.6.1
 psycopg2==2.5.2
-beautifulsoup4==4.2.1
+beautifulsoup4

doc/data/baseball.csv

@@ -1,4 +1,4 @@
-id,year,stint,team,lg,g,ab,r,h,X2b,X3b,hr,rbi,sb,cs,bb,so,ibb,hbp,sh,sf,gidp
+id,player,year,stint,team,lg,g,ab,r,h,X2b,X3b,hr,rbi,sb,cs,bb,so,ibb,hbp,sh,sf,gidp
 88641,womacto01,2006,2,CHN,NL,19,50,6,14,1,0,1,2.0,1.0,1.0,4,4.0,0.0,0.0,3.0,0.0,0.0
 88643,schilcu01,2006,1,BOS,AL,31,2,0,1,0,0,0,0.0,0.0,0.0,0,1.0,0.0,0.0,0.0,0.0,0.0
 88645,myersmi01,2006,1,NYA,AL,62,0,0,0,0,0,0,0.0,0.0,0.0,0,0.0,0.0,0.0,0.0,0.0,0.0

doc/make.py

@@ -77,10 +77,10 @@ def upload_prev(ver, doc_root='./'):
         raise SystemExit('Upload PDF to %s from %s failed' % (ver, doc_root))
 
 def build_pandas():
-        os.chdir('..')
-        os.system('python setup.py clean')
-        os.system('python setup.py build_ext --inplace')
-        os.chdir('doc')
+    os.chdir('..')
+    os.system('python setup.py clean')
+    os.system('python setup.py build_ext --inplace')
+    os.chdir('doc')
 
 def build_prev(ver):
     if os.system('git checkout v%s' % ver) != 1:
@@ -300,7 +300,7 @@ def _get_config():
 
 import argparse
 argparser = argparse.ArgumentParser(description="""
-Pandas documentation builder
+pandas documentation builder
 """.strip())
 
 # argparser.add_argument('-arg_name', '--arg_name',
@@ -325,7 +325,7 @@ def generate_index(api=True, single=False, **kwds):
         f.write(t.render(api=api,single=single,**kwds))
 
 import argparse
-argparser = argparse.ArgumentParser(description="Pandas documentation builder",
+argparser = argparse.ArgumentParser(description="pandas documentation builder",
                                     epilog="Targets : %s" % funcd.keys())
 
 argparser.add_argument('--no-api',

doc/source/10min.rst

@@ -22,7 +22,7 @@
 
 
 ********************
-10 Minutes to Pandas
+10 Minutes to pandas
 ********************
 
 This is a short introduction to pandas, geared mainly for new users.
@@ -344,7 +344,7 @@ A ``where`` operation with setting.
 Missing Data
 ------------
 
-Pandas primarily uses the value ``np.nan`` to represent missing data. It is by
+pandas primarily uses the value ``np.nan`` to represent missing data. It is by
 default not included in computations. See the :ref:`Missing Data section
 <missing_data>`
 
@@ -445,7 +445,7 @@ Merge
 Concat
 ~~~~~~
 
-Pandas provides various facilities for easily combining together Series,
+pandas provides various facilities for easily combining together Series,
 DataFrame, and Panel objects with various kinds of set logic for the indexes
 and relational algebra functionality in the case of join / merge-type
 operations.
@@ -585,7 +585,7 @@ We can produce pivot tables from this data very easily:
 Time Series
 -----------
 
-Pandas has simple, powerful, and efficient functionality for performing
+pandas has simple, powerful, and efficient functionality for performing
 resampling operations during frequency conversion (e.g., converting secondly
 data into 5-minutely data). This is extremely common in, but not limited to,
 financial applications. See the :ref:`Time Series section <timeseries>`

doc/source/api.rst

@@ -350,6 +350,7 @@ Computations / Descriptive Stats
    Series.prod
    Series.quantile
    Series.rank
+   Series.sem
    Series.skew
    Series.std
    Series.sum
@@ -642,6 +643,7 @@ Computations / Descriptive Stats
    DataFrame.prod
    DataFrame.quantile
    DataFrame.rank
+   DataFrame.sem
    DataFrame.skew
    DataFrame.sum
    DataFrame.std
@@ -895,6 +897,7 @@ Computations / Descriptive Stats
    Panel.min
    Panel.pct_change
    Panel.prod
+   Panel.sem
    Panel.skew
    Panel.sum
    Panel.std
@@ -1222,6 +1225,7 @@ Computations / Descriptive Stats
 
    GroupBy.mean
    GroupBy.median
+   GroupBy.sem
    GroupBy.std
    GroupBy.var
    GroupBy.ohlc

doc/source/basics.rst

@@ -93,7 +93,7 @@ unlike the axis labels, cannot be assigned to.
 Accelerated operations
 ----------------------
 
-Pandas has support for accelerating certain types of binary numerical and boolean operations using
+pandas has support for accelerating certain types of binary numerical and boolean operations using
 the ``numexpr`` library (starting in 0.11.0) and the ``bottleneck`` libraries.
 
 These libraries are especially useful when dealing with large data sets, and provide large
@@ -428,6 +428,7 @@ optional ``level`` parameter which applies only if the object has a
     ``prod``, Product of values
     ``std``, Unbiased standard deviation
     ``var``, Unbiased variance
+    ``sem``, Unbiased standard error of the mean
     ``skew``, Unbiased skewness (3rd moment)
     ``kurt``, Unbiased kurtosis (4th moment)
     ``quantile``, Sample quantile (value at %)
@@ -1165,6 +1166,9 @@ Thus, a Series of messy strings can be "converted" into a
 like-indexed Series or DataFrame of cleaned-up or more useful strings,
 without necessitating ``get()`` to access tuples or ``re.match`` objects.
 
+The results dtype always is object, even if no match is found and the result
+only contains ``NaN``.
+
 Named groups like
 
 .. ipython:: python
@@ -1556,7 +1560,7 @@ Working with package options
 .. _basics.working_with_options:
 .. versionadded:: 0.10.1
 
-Pandas has an options system that let's you customize some aspects of it's behaviour,
+pandas has an options system that let's you customize some aspects of it's behaviour,
 display-related options being those the user is must likely to adjust.
 
 Options have a full "dotted-style", case-insensitive name (e.g. ``display.max_rows``),