Merge tag 'v0.19.2' into releases

Version 0.19.2

* tag 'v0.19.2': (78 commits)
  RLS: v0.19.2
  DOC: update release notes for 0.19.2
  TST: skip gbq upload test as flakey
  DOC: clean-up v0.19.2 whatsnew
  DOC: update Pandas Cheat Sheet (GH13202)
  DOC: Pandas Cheat Sheet
  TST: matplotlib 2.0 fix in log limits for barplot (GH14808) (pandas-dev#14957)
  flake8 fix import
  Remove test - from 0.20.0 PR slipped in
  PERF: fix getitem unique_check / initialization issue
  cache and remove boxing (pandas-dev#14931)
  CLN: Resubmit of GH14700.  Fixes GH14554.  Errors other than Indexing…
  Clean up construction of Series with dictionary and datetime index
  BUG: .fillna() for datetime64 with tz is passing thru floats
  BUG: Patch read_csv NA values behaviour
  ENH: merge_asof() has type specializations and can take multiple 'by' parameters (pandas-dev#13936)
  [Backport pandas-dev#14886] BUG: regression in DataFrame.combine_first with integer columns (GH14687) (pandas-dev#14886)
  Fixed KDE Plot to drop the missing values (pandas-dev#14820)
  ENH: merge_asof() has left_index/right_index and left_by/right_by (pandas-dev#14253) (pandas-dev#14531)
  TST: correct url for test file on s3 (xref pandas-dev#14587)
  ...

.github/CONTRIBUTING.md

@@ -6,7 +6,7 @@ Where to start?
 
 All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome.
 
-If you are simply looking to start working with the *pandas* codebase, navigate to the [GitHub "issues" tab](https://github.com/pandas-dev/pandas/issues) and start looking through interesting issues. There are a number of issues listed under [Docs](https://github.com/pandas-dev/pandas/issues?labels=Docs&sort=updated&state=open) and [Difficulty Novice](https://github.com/pandas-dev/pandas/issues?q=is%3Aopen+is%3Aissue+label%3A%22Difficulty+Novice%22) where you could start out.
+If you are simply looking to start working with the *pandas* codebase, navigate to the [GitHub "issues" tab](https://github.com/pydata/pandas/issues) and start looking through interesting issues. There are a number of issues listed under [Docs](https://github.com/pydata/pandas/issues?labels=Docs&sort=updated&state=open) and [Difficulty Novice](https://github.com/pydata/pandas/issues?q=is%3Aopen+is%3Aissue+label%3A%22Difficulty+Novice%22) where you could start out.
 
 Or maybe through using *pandas* you have an idea of you own or are looking for something in the documentation and thinking 'this can be improved'...you can do something about it!
 
@@ -49,7 +49,7 @@ Now that you have an issue you want to fix, enhancement to add, or documentation
 
 To the new user, working with Git is one of the more daunting aspects of contributing to *pandas*. It can very quickly become overwhelming, but sticking to the guidelines below will help keep the process straightforward and mostly trouble free. As always, if you are having difficulties please feel free to ask for help.
 
-The code is hosted on [GitHub](https://www.github.com/pandas-dev/pandas). To contribute you will need to sign up for a [free GitHub account](https://github.com/signup/free). We use [Git](http://git-scm.com/) for version control to allow many people to work together on the project.
+The code is hosted on [GitHub](https://www.github.com/pydata/pandas). To contribute you will need to sign up for a [free GitHub account](https://github.com/signup/free). We use [Git](http://git-scm.com/) for version control to allow many people to work together on the project.
 
 Some great resources for learning Git:
 
@@ -63,11 +63,11 @@ Some great resources for learning Git:
 
 ### Forking
 
-You will need your own fork to work on the code. Go to the [pandas project page](https://github.com/pandas-dev/pandas) and hit the `Fork` button. You will want to clone your fork to your machine:
+You will need your own fork to work on the code. Go to the [pandas project page](https://github.com/pydata/pandas) and hit the `Fork` button. You will want to clone your fork to your machine:
 
     git clone git@github.com:your-user-name/pandas.git pandas-yourname
     cd pandas-yourname
-    git remote add upstream git://github.com/pandas-dev/pandas.git
+    git remote add upstream git://github.com/pydata/pandas.git
 
 This creates the directory pandas-yourname and connects your repository to the upstream (main project) *pandas* repository.
 
@@ -268,7 +268,7 @@ and make these changes with:
 
     pep8radius master --diff --in-place
 
-Alternatively, use the [flake8](http://pypi.python.org/pypi/flake8) tool for checking the style of your code. Additional standards are outlined on the [code style wiki page](https://github.com/pandas-dev/pandas/wiki/Code-Style-and-Conventions).
+Alternatively, use the [flake8](http://pypi.python.org/pypi/flake8) tool for checking the style of your code. Additional standards are outlined on the [code style wiki page](https://github.com/pydata/pandas/wiki/Code-Style-and-Conventions).
 
 Please try to maintain backward compatibility. *pandas* has lots of users with lots of existing code, so don't break it if at all possible. If you think breakage is required, clearly state why as part of the pull request. Also, be careful when changing method signatures and add deprecation warnings where needed.
 
@@ -282,7 +282,7 @@ Like many packages, *pandas* uses the [Nose testing system](https://nose.readthe
 
 #### Writing tests
 
-All tests should go into the `tests` subdirectory of the specific package. This folder contains many current examples of tests, and we suggest looking to these for inspiration. If your test requires working with files or network connectivity, there is more information on the [testing page](https://github.com/pandas-dev/pandas/wiki/Testing) of the wiki.
+All tests should go into the `tests` subdirectory of the specific package. This folder contains many current examples of tests, and we suggest looking to these for inspiration. If your test requires working with files or network connectivity, there is more information on the [testing page](https://github.com/pydata/pandas/wiki/Testing) of the wiki.
 
 The `pandas.util.testing` module has many special `assert` functions that make it easier to make statements about whether Series or DataFrame objects are equivalent. The easiest way to verify that your code is correct is to explicitly construct the result you expect, then compare the actual result to the expected correct result:
 
@@ -378,7 +378,7 @@ This will check out the master revision and run the suite on both master and you
 
 You can run specific benchmarks using the `-r` flag, which takes a regular expression.
 
-See the [performance testing wiki](https://github.com/pandas-dev/pandas/wiki/Performance-Testing) for information on how to write a benchmark.
+See the [performance testing wiki](https://github.com/pydata/pandas/wiki/Performance-Testing) for information on how to write a benchmark.
 
 ### Documenting your code
 
@@ -390,7 +390,7 @@ If your code is an enhancement, it is most likely necessary to add usage example
 .. versionadded:: 0.17.0
 ```
 
-This will put the text *New in version 0.17.0* wherever you put the sphinx directive. This should also be put in the docstring when adding a new function or method ([example](https://github.com/pandas-dev/pandas/blob/v0.16.2/pandas/core/generic.py#L1959)) or a new keyword argument ([example](https://github.com/pandas-dev/pandas/blob/v0.16.2/pandas/core/frame.py#L1171)).
+This will put the text *New in version 0.17.0* wherever you put the sphinx directive. This should also be put in the docstring when adding a new function or method ([example](https://github.com/pydata/pandas/blob/v0.16.2/pandas/core/generic.py#L1959)) or a new keyword argument ([example](https://github.com/pydata/pandas/blob/v0.16.2/pandas/core/frame.py#L1171)).
 
 Contributing your changes to *pandas*
 -------------------------------------
@@ -466,8 +466,8 @@ If you added the upstream repository as described above you will see something l
 
     origin  git@github.com:yourname/pandas.git (fetch)
     origin  git@github.com:yourname/pandas.git (push)
-    upstream        git://github.com/pandas-dev/pandas.git (fetch)
-    upstream        git://github.com/pandas-dev/pandas.git (push)
+    upstream        git://github.com/pydata/pandas.git (fetch)
+    upstream        git://github.com/pydata/pandas.git (push)
 
 Now your code is on GitHub, but it is not yet a part of the *pandas* project. For that to happen, a pull request needs to be submitted on GitHub.
 

.github/ISSUE_TEMPLATE.md

@@ -1,18 +1,15 @@
-#### Code Sample, a copy-pastable example if possible
+#### A small, complete example of the issue
 
 ```python
 # Your code here
 
 ```
-#### Problem description
-
-[this should explain **why** the current behaviour is a problem and why the expected output is a better solution.]
 
 #### Expected Output
 
 #### Output of ``pd.show_versions()``
 
 <details>
-# Paste the output here pd.show_versions() here
+# Paste the output here
 
 </details>

.travis.yml

@@ -14,9 +14,13 @@ cache:
 
 env:
   global:
-
-  # pandas-docs-travis GH
-  - secure: Oz6cwVu3NetKZ5nKLJ4RQQBbRJE4KF3J5fkVwICJ2SQaE00ng8os4zJRGSkf0g+K1AVJpQ9A1XKG/IOKMBSkGiXBaVR/Qk/5b+QOTjEhgQBd7tdYjBrFfzpn0AIWn+70nAh24pvuGmq5MU9ILUXwNVVM87FF7cJ7efNseveh7Ss=
+  # scatterci API key
+  #- secure: "Bx5umgo6WjuGY+5XFa004xjCiX/vq0CyMZ/ETzcs7EIBI1BE/0fIDXOoWhoxbY9HPfdPGlDnDgB9nGqr5wArO2s+BavyKBWg6osZ3dmkfuJPMOWeyCa92EeP+sfKw8e5HSU5MizW9e319wHWOF/xkzdHR7T67Qd5erhv91x4DnQ="
+  # ironcache API key
+  #- secure: "e4eEFn9nDQc3Xa5BWYkzfX37jaWVq89XidVX+rcCNEr5OlOImvveeXnF1IzbRXznH4Sv0YsLwUd8RGUWOmyCvkONq/VJeqCHWtTMyfaCIdqSyhIP9Odz8r9ahch+Y0XFepBey92AJHmlnTh+2GjCDgIiqq4fzglojnp56Vg1ojA="
+  #- secure: "CjmYmY5qEu3KrvMtel6zWFEtMq8ORBeS1S1odJHnjQpbwT1KY2YFZRVlLphfyDQXSz6svKUdeRrCNp65baBzs3DQNA8lIuXGIBYFeJxqVGtYAZZs6+TzBPfJJK798sGOj5RshrOJkFG2rdlWNuTq/XphI0JOrN3nPUkRrdQRpAw="
+  # pandas-docs-bot GH
+  - secure: "PCzUFR8CHmw9lH84p4ygnojdF7Z8U5h7YfY0RyT+5K/aiQ1ZTU3ZkDTPI0/rR5FVMxsEEKEQKMcc5fvqW0PeD7Q2wRmluloKgT9w4EVEJ1ppKf7lITPcvZR2QgVOvjv4AfDtibLHFNiaSjzoqyJVjM4igjOu8WTlF3JfZcmOQjQ="
 
 git:
     # for cloning

README.md

@@ -1,5 +1,5 @@
 <div align="center">
-  <img src="https://github.com/pandas-dev/pandas/blob/master/doc/logo/pandas_logo.png"><br>
+  <img src="https://github.com/pydata/pandas/blob/master/doc/logo/pandas_logo.png"><br>
 </div>
 
 -----------------
@@ -25,8 +25,8 @@
 <tr>
   <td>Build Status</td>
   <td>
-    <a href="https://travis-ci.org/pandas-dev/pandas">
-    <img src="https://travis-ci.org/pandas-dev/pandas.svg?branch=master" alt="travis build status" />
+    <a href="https://travis-ci.org/pydata/pandas">
+    <img src="https://travis-ci.org/pydata/pandas.svg?branch=master" alt="travis build status" />
     </a>
   </td>
 </tr>
@@ -39,7 +39,7 @@
 </tr>
 <tr>
   <td>Coverage</td>
-  <td><img src="https://codecov.io/github/pandas-dev/pandas/coverage.svg?branch=master" alt="coverage" /></td>
+  <td><img src="https://codecov.io/github/pydata/pandas/coverage.svg?branch=master" alt="coverage" /></td>
 </tr>
 <tr>
   <td>Conda</td>
@@ -127,7 +127,7 @@ Here are just a few of the things that pandas does well:
 
 ## Where to get it
 The source code is currently hosted on GitHub at:
-http://github.com/pandas-dev/pandas
+http://github.com/pydata/pandas
 
 Binary installers for the latest released version are available at the [Python
 package index](http://pypi.python.org/pypi/pandas/) and on conda.

RELEASE.md

@@ -3,4 +3,4 @@ Release Notes
 
 The list of changes to pandas between each release can be found
 [here](http://pandas.pydata.org/pandas-docs/stable/whatsnew.html). For full
-details, see the commit logs at http://github.com/pandas-dev/pandas.
+details, see the commit logs at http://github.com/pydata/pandas.

asv_bench/asv.conf.json

@@ -21,7 +21,7 @@
     "environment_type": "conda",
 
     // the base URL to show a commit for the project.
-    "show_commit_url": "https://github.com/pandas-dev/pandas/commit/",
+    "show_commit_url": "https://github.com/pydata/pandas/commit/",
 
     // The Pythons you'd like to test against.  If not provided, defaults
     // to the current version of Python used to run `asv`.

asv_bench/benchmarks/algorithms.py

@@ -3,7 +3,7 @@
 from pandas.util import testing as tm
 
 
-class Algorithms(object):
+class algorithm(object):
     goal_time = 0.2
 
     def setup(self):
@@ -24,28 +24,21 @@ def setup(self):
         self.arrneg = np.arange(-1000000, 0)
         self.arrmixed = np.array([1, -1]).repeat(500000)
 
-        # match
-        self.uniques = tm.makeStringIndex(1000).values
-        self.all = self.uniques.repeat(10)
-
-    def time_factorize_int(self):
+    def time_int_factorize(self):
         self.int.factorize()
 
-    def time_factorize_float(self):
+    def time_float_factorize(self):
         self.int.factorize()
 
-    def time_duplicated_int_unique(self):
+    def time_int_unique_duplicated(self):
         self.int_unique.duplicated()
 
-    def time_duplicated_int(self):
+    def time_int_duplicated(self):
         self.int.duplicated()
 
-    def time_duplicated_float(self):
+    def time_float_duplicated(self):
         self.float.duplicated()
 
-    def time_match_strings(self):
-        pd.match(self.all, self.uniques)
-
     def time_add_overflow_pos_scalar(self):
         self.checked_add(self.arr, 1)
 
@@ -65,7 +58,7 @@ def time_add_overflow_mixed_arr(self):
         self.checked_add(self.arr, self.arrmixed)
 
 
-class Hashing(object):
+class hashing(object):
     goal_time = 0.2
 
     def setup(self):

asv_bench/benchmarks/attrs_caching.py

@@ -1,32 +1,23 @@
 from .pandas_vb_common import *
-from pandas.util.decorators import cache_readonly
 
 
-class DataFrameAttributes(object):
+class getattr_dataframe_index(object):
     goal_time = 0.2
 
     def setup(self):
         self.df = DataFrame(np.random.randn(10, 6))
         self.cur_index = self.df.index
 
-    def time_get_index(self):
+    def time_getattr_dataframe_index(self):
         self.foo = self.df.index
 
-    def time_set_index(self):
-        self.df.index = self.cur_index
-
 
-class CacheReadonly(object):
+class setattr_dataframe_index(object):
     goal_time = 0.2
 
     def setup(self):
+        self.df = DataFrame(np.random.randn(10, 6))
+        self.cur_index = self.df.index
 
-        class Foo:
-
-            @cache_readonly
-            def prop(self):
-                return 5
-        self.obj = Foo()
-
-    def time_cache_readonly(self):
-        self.obj.prop
+    def time_setattr_dataframe_index(self):
+        self.df.index = self.cur_index