Data Science Tool
Project description
Dataphile
=========
Dataphile is a high-level python package for both data analysis and data processing. It started as
a central repository of common tasks and capabilities used by the author, but has now evolved into
something others might find useful. See [components](#Components) below.
[![GitHub License](http://img.shields.io/badge/license-GPLv3-blue.svg?style=flat)](http://www.gnu.org/copyleft/gpl.html)
[![PyPI Version](https://img.shields.io/pypi/v/dataphile.svg)](https://pypi.org/project/dataphile/)
[![Docs
Latest](https://readthedocs.com/projects/dataphile-dataphile/badge/?version=latest)](https://readthedocs.com/dataphile)
---
<!-- Animated GIF of AutoGUI -->
<img src="https://lentner.io/images/auto_gui_interactive.gif" width="80%"
style="display:block;margin: 0 auto;">
<p style="text-align:center;">
**Figure**: Demonstration of Dataphile's `AutoGUI` feature.
</p>
Componenents
------------
Installation
------------
Install Dataphile using _pip_.
```
pip install git+https://github.com/glentner/dataphile
```
If you are using Anaconda, install using the above call to pip _from inside your environment_.
Documentation
-------------
Authors
-------
Contributions
-------------
Road Map
--------
TODO: README, PyPI, Docs
=========
Dataphile is a high-level python package for both data analysis and data processing. It started as
a central repository of common tasks and capabilities used by the author, but has now evolved into
something others might find useful. See [components](#Components) below.
[![GitHub License](http://img.shields.io/badge/license-GPLv3-blue.svg?style=flat)](http://www.gnu.org/copyleft/gpl.html)
[![PyPI Version](https://img.shields.io/pypi/v/dataphile.svg)](https://pypi.org/project/dataphile/)
[![Docs
Latest](https://readthedocs.com/projects/dataphile-dataphile/badge/?version=latest)](https://readthedocs.com/dataphile)
---
<!-- Animated GIF of AutoGUI -->
<img src="https://lentner.io/images/auto_gui_interactive.gif" width="80%"
style="display:block;margin: 0 auto;">
<p style="text-align:center;">
**Figure**: Demonstration of Dataphile's `AutoGUI` feature.
</p>
Componenents
------------
Installation
------------
Install Dataphile using _pip_.
```
pip install git+https://github.com/glentner/dataphile
```
If you are using Anaconda, install using the above call to pip _from inside your environment_.
Documentation
-------------
Authors
-------
Contributions
-------------
Road Map
--------
TODO: README, PyPI, Docs
Project details
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