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* commit 'v0.19.0-174-g81a2f79': (156 commits)
BLD: escape GH_TOKEN in build_docs
TST: Correct results with np.size and crosstab (pandas-dev#4003) (pandas-dev#14755)
Frame benchmarking sum instead of mean (pandas-dev#14824)
CLN: lint of test_base.py
BUG: Allow TZ-aware DatetimeIndex in merge_asof() (pandas-dev#14844)
BUG: GH11847 Unstack with mixed dtypes coerces everything to object
TST: skip testing on windows for specific formatting which sometimes hangs (pandas-dev#14851)
BLD: try new gh token for pandas-docs
CLN/PERF: clean-up of the benchmarks (pandas-dev#14099)
ENH: add timedelta as valid type for interpolate with method='time' (pandas-dev#14799)
DOC: add section on groupby().rolling/expanding/resample (pandas-dev#14801)
TST: add test to confirm GH14606 (specify category dtype for empty) (pandas-dev#14752)
BLD: use org name in build-docs.sh
BF(TST): use = (native) instead of < (little endian) for target data types (pandas-dev#14832)
ENH: Introduce UnsortedIndexError GH11897 (pandas-dev#14762)
ENH: Add the ability to have a separate title for each subplot when plotting (pandas-dev#14753)
DOC: Fix grammar and formatting typos (pandas-dev#14803)
BLD: try new build credentials for pandas-docs
TST: Test pivot with categorical data
MAINT: Cleanup pandas/src/parser (pandas-dev#14740)
...
Copy file name to clipboardExpand all lines: .github/CONTRIBUTING.md
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All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome.
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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.
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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.
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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!
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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.
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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.
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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.
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Some great resources for learning Git:
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### Forking
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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:
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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:
This creates the directory pandas-yourname and connects your repository to the upstream (main project) *pandas* repository.
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pep8radius master --diff --in-place
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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).
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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).
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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.
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#### Writing tests
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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.
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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.
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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:
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You can run specific benchmarks using the `-r` flag, which takes a regular expression.
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See the [performance testing wiki](https://github.com/pydata/pandas/wiki/Performance-Testing) for information on how to write a benchmark.
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See the [performance testing wiki](https://github.com/pandas-dev/pandas/wiki/Performance-Testing) for information on how to write a benchmark.
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### Documenting your code
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.. versionadded:: 0.17.0
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```
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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)).
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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)).
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Contributing your changes to *pandas*
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-------------------------------------
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