Fixed whatsnew entry

.github/CONTRIBUTING.md

@@ -8,16 +8,16 @@ Our main contributing guide can be found [in this repo](https://github.com/panda
 
 If you are looking to contribute to the *pandas* codebase, the best place to start is the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues). This is also a great place for filing bug reports and making suggestions for ways in which we can improve the code and documentation.
 
-If you have additional questions, feel free to ask them on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Gitter](https://gitter.im/pydata/pandas). Further information can also be found in the "[Where to start?](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#where-to-start)" section.
+If you have additional questions, feel free to ask them on the [mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata) or on [Gitter](https://gitter.im/pydata/pandas). Further information can also be found in the "[Where to start?](https://github.com/pandas-dev/pandas/blob/master/doc/source/development/contributing.rst#where-to-start)" section.
 
 ## Filing Issues
 
-If you notice a bug in the code or documentation, or have suggestions for how we can improve either, feel free to create an issue on the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) using [GitHub's "issue" form](https://github.com/pandas-dev/pandas/issues/new). The form contains some questions that will help us best address your issue. For more information regarding how to file issues against *pandas*, please refer to the "[Bug reports and enhancement requests](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#bug-reports-and-enhancement-requests)" section.
+If you notice a bug in the code or documentation, or have suggestions for how we can improve either, feel free to create an issue on the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) using [GitHub's "issue" form](https://github.com/pandas-dev/pandas/issues/new). The form contains some questions that will help us best address your issue. For more information regarding how to file issues against *pandas*, please refer to the "[Bug reports and enhancement requests](https://github.com/pandas-dev/pandas/blob/master/doc/source/development/contributing.rst#bug-reports-and-enhancement-requests)" section.
 
 ## Contributing to the Codebase
 
-The code is hosted on [GitHub](https://www.github.com/pandas-dev/pandas), so you will need to use [Git](http://git-scm.com/) to clone the project and make changes to the codebase. Once you have obtained a copy of the code, you should create a development environment that is separate from your existing Python environment so that you can make and test changes without compromising your own work environment. For more information, please refer to the "[Working with the code](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#working-with-the-code)" section.
+The code is hosted on [GitHub](https://www.github.com/pandas-dev/pandas), so you will need to use [Git](http://git-scm.com/) to clone the project and make changes to the codebase. Once you have obtained a copy of the code, you should create a development environment that is separate from your existing Python environment so that you can make and test changes without compromising your own work environment. For more information, please refer to the "[Working with the code](https://github.com/pandas-dev/pandas/blob/master/doc/source/development/contributing.rst#working-with-the-code)" section.
 
-Before submitting your changes for review, make sure to check that your changes do not break any tests. You can find more information about our test suites in the "[Test-driven development/code writing](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#test-driven-development-code-writing)" section. We also have guidelines regarding coding style that will be enforced during testing, which can be found in the "[Code standards](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#code-standards)" section.
+Before submitting your changes for review, make sure to check that your changes do not break any tests. You can find more information about our test suites in the "[Test-driven development/code writing](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#test-driven-development-code-writing)" section. We also have guidelines regarding coding style that will be enforced during testing, which can be found in the "[Code standards](https://github.com/pandas-dev/pandas/blob/master/doc/source/development/contributing.rst#code-standards)" section.
 
-Once your changes are ready to be submitted, make sure to push your changes to GitHub before creating a pull request. Details about how to do that can be found in the "[Contributing your changes to pandas](https://github.com/pandas-dev/pandas/blob/master/doc/source/contributing.rst#contributing-your-changes-to-pandas)" section. We will review your changes, and you will most likely be asked to make additional changes before it is finally ready to merge. However, once it's ready, we will merge it, and you will have successfully contributed to the codebase!
+Once your changes are ready to be submitted, make sure to push your changes to GitHub before creating a pull request. Details about how to do that can be found in the "[Contributing your changes to pandas](https://github.com/pandas-dev/pandas/blob/master/doc/source/development/contributing.rst#contributing-your-changes-to-pandas)" section. We will review your changes, and you will most likely be asked to make additional changes before it is finally ready to merge. However, once it's ready, we will merge it, and you will have successfully contributed to the codebase!

Makefile

@@ -23,4 +23,3 @@ doc:
 	cd doc; \
 	python make.py clean; \
 	python make.py html
-	python make.py spellcheck

asv_bench/benchmarks/__init__.py

@@ -0,0 +1 @@
+"""Pandas benchmarks."""

asv_bench/benchmarks/algorithms.py

@@ -5,7 +5,6 @@
 import pandas as pd
 from pandas.util import testing as tm
 
-
 for imp in ['pandas.util', 'pandas.tools.hashing']:
     try:
         hashing = import_module(imp)
@@ -142,4 +141,4 @@ def time_quantile(self, quantile, interpolation, dtype):
         self.idx.quantile(quantile, interpolation=interpolation)
 
 
-from .pandas_vb_common import setup  # noqa: F401
+from .pandas_vb_common import setup  # noqa: F401 isort:skip

asv_bench/benchmarks/io/hdf.py

@@ -1,7 +1,5 @@
-import warnings
-
 import numpy as np
-from pandas import DataFrame, Panel, date_range, HDFStore, read_hdf
+from pandas import DataFrame, date_range, HDFStore, read_hdf
 import pandas.util.testing as tm
 
 from ..pandas_vb_common import BaseIO
@@ -99,31 +97,6 @@ def time_store_info(self):
         self.store.info()
 
 
-class HDFStorePanel(BaseIO):
-
-    def setup(self):
-        self.fname = '__test__.h5'
-        with warnings.catch_warnings(record=True):
-            self.p = Panel(np.random.randn(20, 1000, 25),
-                           items=['Item%03d' % i for i in range(20)],
-                           major_axis=date_range('1/1/2000', periods=1000),
-                           minor_axis=['E%03d' % i for i in range(25)])
-            self.store = HDFStore(self.fname)
-            self.store.append('p1', self.p)
-
-    def teardown(self):
-        self.store.close()
-        self.remove(self.fname)
-
-    def time_read_store_table_panel(self):
-        with warnings.catch_warnings(record=True):
-            self.store.select('p1')
-
-    def time_write_store_table_panel(self):
-        with warnings.catch_warnings(record=True):
-            self.store.append('p2', self.p)
-
-
 class HDF(BaseIO):
 
     params = ['table', 'fixed']

asv_bench/benchmarks/strings.py

@@ -102,10 +102,10 @@ def setup(self, repeats):
         N = 10**5
         self.s = Series(tm.makeStringIndex(N))
         repeat = {'int': 1, 'array': np.random.randint(1, 3, N)}
-        self.repeat = repeat[repeats]
+        self.values = repeat[repeats]
 
     def time_repeat(self, repeats):
-        self.s.str.repeat(self.repeat)
+        self.s.str.repeat(self.values)
 
 
 class Cat(object):

ci/code_checks.sh

@@ -93,7 +93,7 @@ if [[ -z "$CHECK" || "$CHECK" == "lint" ]]; then
     # this particular codebase (e.g. src/headers, src/klib, src/msgpack). However,
     # we can lint all header files since they aren't "generated" like C files are.
     MSG='Linting .c and .h' ; echo $MSG
-    cpplint --quiet --extensions=c,h --headers=h --recursive --filter=-readability/casting,-runtime/int,-build/include_subdir pandas/_libs/src/*.h pandas/_libs/src/parser pandas/_libs/ujson pandas/_libs/tslibs/src/datetime
+    cpplint --quiet --extensions=c,h --headers=h --recursive --filter=-readability/casting,-runtime/int,-build/include_subdir pandas/_libs/src/*.h pandas/_libs/src/parser pandas/_libs/ujson pandas/_libs/tslibs/src/datetime pandas/io/msgpack pandas/_libs/*.cpp pandas/util
     RET=$(($RET + $?)) ; echo $MSG "DONE"
 
     echo "isort --version-number"
@@ -174,9 +174,10 @@ if [[ -z "$CHECK" || "$CHECK" == "patterns" ]]; then
     MSG='Check that no file in the repo contains tailing whitespaces' ; echo $MSG
     set -o pipefail
     if [[ "$AZURE" == "true" ]]; then
-        ! grep -n --exclude="*.svg" -RI "\s$" * | awk -F ":" '{print "##vso[task.logissue type=error;sourcepath=" $1 ";linenumber=" $2 ";] Tailing whitespaces found: " $3}'
+        # we exclude all c/cpp files as the c/cpp files of pandas code base are tested when Linting .c and .h files
+        ! grep -n '--exclude=*.'{svg,c,cpp,html} -RI "\s$" * | awk -F ":" '{print "##vso[task.logissue type=error;sourcepath=" $1 ";linenumber=" $2 ";] Tailing whitespaces found: " $3}'
     else
-        ! grep -n --exclude="*.svg" -RI "\s$" * | awk -F ":" '{print $1 ":" $2 ":Tailing whitespaces found: " $3}'
+        ! grep -n '--exclude=*.'{svg,c,cpp,html}  -RI "\s$" * | awk -F ":" '{print $1 ":" $2 ":Tailing whitespaces found: " $3}'
     fi
     RET=$(($RET + $?)) ; echo $MSG "DONE"
 fi
@@ -206,7 +207,7 @@ if [[ -z "$CHECK" || "$CHECK" == "doctests" ]]; then
 
     MSG='Doctests frame.py' ; echo $MSG
     pytest -q --doctest-modules pandas/core/frame.py \
-        -k"-axes -combine -itertuples -join -pivot_table -query -reindex -reindex_axis -round"
+        -k" -itertuples -join -reindex -reindex_axis -round"
     RET=$(($RET + $?)) ; echo $MSG "DONE"
 
     MSG='Doctests series.py' ; echo $MSG
@@ -240,8 +241,8 @@ fi
 ### DOCSTRINGS ###
 if [[ -z "$CHECK" || "$CHECK" == "docstrings" ]]; then
 
-    MSG='Validate docstrings (GL06, GL07, GL09, SS04, PR03, PR05, EX04)' ; echo $MSG
-    $BASE_DIR/scripts/validate_docstrings.py --format=azure --errors=GL06,GL07,GL09,SS04,PR03,PR05,EX04
+    MSG='Validate docstrings (GL06, GL07, GL09, SS04, PR03, PR05, PR10, EX04, RT04, RT05, SS05, SA05)' ; echo $MSG
+    $BASE_DIR/scripts/validate_docstrings.py --format=azure --errors=GL06,GL07,GL09,SS04,PR03,PR04,PR05,EX04,RT04,RT05,SS05,SA05
     RET=$(($RET + $?)) ; echo $MSG "DONE"
 
 fi

doc/source/user_guide/groupby.rst

@@ -15,7 +15,7 @@ steps:
 
 Out of these, the split step is the most straightforward. In fact, in many
 situations we may wish to split the data set into groups and do something with
-those groups. In the apply step, we might wish to one of the
+those groups. In the apply step, we might wish to do one of the
 following:
 
 * **Aggregation**: compute a summary statistic (or statistics) for each
@@ -1317,7 +1317,7 @@ arbitrary function, for example:
    df.groupby(['Store', 'Product']).pipe(mean)
 
 where ``mean`` takes a GroupBy object and finds the mean of the Revenue and Quantity
-columns repectively for each Store-Product combination. The ``mean`` function can
+columns respectively for each Store-Product combination. The ``mean`` function can
 be any function that takes in a GroupBy object; the ``.pipe`` will pass the GroupBy
 object as a parameter into the function you specify.
 

doc/source/user_guide/io.rst

@@ -989,6 +989,36 @@ a single date rather than the entire array.
 
    os.remove('tmp.csv')
 
+
+.. _io.csv.mixed_timezones:
+
+Parsing a CSV with mixed Timezones
+++++++++++++++++++++++++++++++++++
+
+Pandas cannot natively represent a column or index with mixed timezones. If your CSV
+file contains columns with a mixture of timezones, the default result will be
+an object-dtype column with strings, even with ``parse_dates``.
+
+
+.. ipython:: python
+
+   content = """\
+   a
+   2000-01-01T00:00:00+05:00
+   2000-01-01T00:00:00+06:00"""
+   df = pd.read_csv(StringIO(content), parse_dates=['a'])
+   df['a']
+
+To parse the mixed-timezone values as a datetime column, pass a partially-applied
+:func:`to_datetime` with ``utc=True`` as the ``date_parser``.
+
+.. ipython:: python
+
+   df = pd.read_csv(StringIO(content), parse_dates=['a'],
+                    date_parser=lambda col: pd.to_datetime(col, utc=True))
+   df['a']
+
+
 .. _io.dayfirst: