Metadata-Version: 2.4
Name: pandas-aipy
Version: 2.2.3
Summary: Powerful data structures for data analysis, time series, and statistics
Author-email: The QPYPI Team <qpypi@qpython.org>
License: MIT AND (Apache-2.0 OR BSD-2-Clause)
Project-URL: Homepage, https://qpypi.qpython.org/project/pandas-aipy/
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: End Users/Desktop
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: Android
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Software Development
Requires-Python: ==3.12.*
Description-Content-Type: text/markdown
Requires-Dist: numpy-aipy
Requires-Dist: python-dateutil
Requires-Dist: pytz

This project is a branch of <a target="_blank" rel="noopener" href="https://pypi.org/project/pandas/">pandas</a> on <a href="https://www.qpython.org">QPython</a>.

Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with structured (tabular, multidimensional, potentially heterogeneous) and time series data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. It is already well on its way toward this goal.


## Documentation
The official documentation is hosted on [PyData.org](https://pandas.pydata.org/pandas-docs/stable/).

## Background
Work on ``pandas`` started at [AQR](https://www.aqr.com/) (a quantitative hedge fund) in 2008 and
has been under active development since then.

## Getting Help

For usage questions, the best place to go to is [StackOverflow](https://stackoverflow.com/questions/tagged/pandas).
Further, general questions and discussions can also take place on the [pydata mailing list](https://groups.google.com/forum/?fromgroups#!forum/pydata).

## Discussion and Development
Most development discussions take place on GitHub in this repo, via the [GitHub issue tracker](https://github.com/pandas-dev/pandas/issues).

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 [Slack channel](https://pandas.pydata.org/docs/dev/development/community.html?highlight=slack#community-slack) is available for quick development related questions.

There are also frequent [community meetings](https://pandas.pydata.org/docs/dev/development/community.html#community-meeting) for project maintainers open to the community as well as monthly [new contributor meetings](https://pandas.pydata.org/docs/dev/development/community.html#new-contributor-meeting) to help support new contributors.

Additional information on the communication channels can be found on the [contributor community](https://pandas.pydata.org/docs/development/community.html) page.
