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Copy file name to clipboardExpand all lines: .github/CONTRIBUTING.md
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Whether you are a novice or experienced software developer, all contributions and suggestions are welcome!
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Our main contributing guide can be found [in this repo](https://github.com/pandas-dev/pandas/blob/master/doc/source/development/contributing.rst) or [on the website](https://pandas-docs.github.io/pandas-docs-travis/development/contributing.html). If you do not want to read it in its entirety, we will summarize the main ways in which you can contribute and point to relevant sections of that document for further information.
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Our main contributing guide can be found [in this repo](https://github.com/pandas-dev/pandas/blob/master/doc/source/development/contributing.rst) or [on the website](https://pandas.pydata.org/docs/dev/development/contributing.html). If you do not want to read it in its entirety, we will summarize the main ways in which you can contribute and point to relevant sections of that document for further information.
about: Create a bug report to help us improve pandas
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title: "BUG:"
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labels: "Bug, Needs Triage"
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---
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-[ ] I have checked that this issue has not already been reported.
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-[ ] I have confirmed this bug exists on the latest version of pandas.
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-[ ] (optional) I have confirmed this bug exists on the master branch of pandas.
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---
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**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.
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#### Code Sample, a copy-pastable example
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```python
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# Your code here
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```
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#### Problem description
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[this should explain **why** the current behaviour is a problem and why the expected output is a better solution]
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#### Expected Output
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#### Output of ``pd.show_versions()``
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<details>
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[paste the output of ``pd.show_versions()`` here leaving a blank line after the details tag]
[this should provide the location of the documentation, e.g. "pandas.read_csv" or the URL of the documentation, e.g. "https://dev.pandas.io/docs/reference/api/pandas.read_csv.html"]
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**Note**: You can check the latest versions of the docs on `master`[here](https://pandas.pydata.org/docs/dev/).
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#### Documentation problem
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[this should provide a description of what documentation you believe needs to be fixed/improved]
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#### Suggested fix for documentation
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[this should explain the suggested fix and **why** it's better than the existing documentation]
#### Is your feature request related to a problem?
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[this should provide a description of what the problem is, e.g. "I wish I could use pandas to do [...]"]
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#### Describe the solution you'd like
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[this should provide a description of the feature request, e.g. "`DataFrame.foo` should get a new parameter `bar` that [...]", try to write a docstring for the desired feature]
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#### API breaking implications
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[this should provide a description of how this feature will affect the API]
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#### Describe alternatives you've considered
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[this should provide a description of any alternative solutions or features you've considered]
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#### Additional context
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[add any other context, code examples, or references to existing implementations about the feature request here]
-[ ] I have searched the [[pandas] tag](https://stackoverflow.com/questions/tagged/pandas) on StackOverflow for similar questions.
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-[ ] I have asked my usage related question on [StackOverflow](https://stackoverflow.com).
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---
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#### Question about pandas
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**Note**: If you'd still like to submit a question, please read [this guide](
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https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your question.
- JOB="3.9-dev" PATTERN="(not slow and not network and not clipboard)"
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- env:
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- JOB="3.8" ENV_FILE="ci/deps/travis-38.yaml" PATTERN="(not slow and not network and not clipboard)"
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- env:
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- JOB="3.7" ENV_FILE="ci/deps/travis-37.yaml" PATTERN="(not slow and not network and not clipboard)"
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- arch: arm64
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env:
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- JOB="3.7, arm64" PYTEST_WORKERS=8 ENV_FILE="ci/deps/travis-37-arm64.yaml" PATTERN="(not slow and not network and not clipboard)"
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- env:
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- JOB="3.6, locale" ENV_FILE="ci/deps/travis-36-locale.yaml" PATTERN="((not slow and not network and not clipboard) or (single and db))" LOCALE_OVERRIDE="zh_CN.UTF-8" SQL="1"
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- JOB="3.7, locale" ENV_FILE="ci/deps/travis-37-locale.yaml" PATTERN="((not slow and not network and not clipboard) or (single and db))" LOCALE_OVERRIDE="zh_CN.UTF-8" SQL="1"
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services:
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- mysql
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- postgresql
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# Enabling Deprecations when running tests
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# PANDAS_TESTING_MODE="deprecate" causes DeprecationWarning messages to be displayed in the logs
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# See pandas/_testing.py for more details.
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- JOB="3.6, coverage" ENV_FILE="ci/deps/travis-36-cov.yaml" PATTERN="((not slow and not network and not clipboard) or (single and db))" PANDAS_TESTING_MODE="deprecate" COVERAGE=true SQL="1"
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- JOB="3.7, coverage" ENV_FILE="ci/deps/travis-37-cov.yaml" PATTERN="((not slow and not network and not clipboard) or (single and db))" PANDAS_TESTING_MODE="deprecate" COVERAGE=true SQL="1"
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services:
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- mysql
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- postgresql
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allow_failures:
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- arch: arm64
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env:
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- JOB="3.7, arm64" PYTEST_WORKERS=8 ENV_FILE="ci/deps/travis-37-arm64.yaml" PATTERN="(not slow and not network and not clipboard)"
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- dist: bionic
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env:
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- JOB="3.9-dev" PATTERN="(not slow and not network and not clipboard)"
**pandas** is a Python package providing fast, flexible, and expressive data
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**pandas** is a Python package that provides fast, flexible, and expressive data
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structures designed to make working with "relational" or "labeled" data both
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easy and intuitive. It aims to be the fundamental high-level building block for
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doing practical, **real world** data analysis in Python. Additionally, it has
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Here are just a few of the things that pandas does well:
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- Easy handling of [**missing data**][missing-data] (represented as
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`NaN`) in floating point as well as non-floating point data
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`NaN`, `NA`, or `NaT`) in floating point as well as non-floating point data
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- Size mutability: columns can be [**inserted and
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deleted**][insertion-deletion] from DataFrame and higher dimensional
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objects
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Further, general questions and discussions can also take place on the [pydata mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata).
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## Discussion and Development
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Most development discussion is taking place on github in this repo. Further, the [pandas-dev mailing list](https://mail.python.org/mailman/listinfo/pandas-dev) can also be used for specialized discussions or design issues, and a [Gitter channel](https://gitter.im/pydata/pandas) is available for quick development related questions.
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Most development discussions take place on github in this repo. Further, the [pandas-dev mailing list](https://mail.python.org/mailman/listinfo/pandas-dev) can also be used for specialized discussions or design issues, and a [Gitter channel](https://gitter.im/pydata/pandas) is available for quick development related questions.
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## Contributing to pandas [](https://www.codetriage.com/pandas-dev/pandas)
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All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome.
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All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome.
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A detailed overview on how to contribute can be found in the **[contributing guide](https://dev.pandas.io/docs/contributing.html)**. There is also an [overview](.github/CONTRIBUTING.md) on GitHub.
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A detailed overview on how to contribute can be found in the **[contributing guide](https://pandas.pydata.org/docs/dev/development/contributing.html)**. There is also an [overview](.github/CONTRIBUTING.md) on GitHub.
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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 [good first issue](https://github.com/pandas-dev/pandas/issues?labels=good+first+issue&sort=updated&state=open) where you could start out.
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