Rohan Singh 1f027344f1 [Dataframes] Implemented .describe() (#1696)
* added describe methods

* mean updates and added truediv func

* updates

* updated truediv test

* porting stocks to ubuntu

* hacky solution for describe, mean, median, quantile by transposing df

* removed data file

* removed faulty truediv implementation

* flake8 and documentation updates

* updated mean, median, var, std to handle mixed values

* added describe methods

* mean updates and added truediv func

* updates

* updated truediv test

* porting stocks to ubuntu

* hacky solution for describe, mean, median, quantile by transposing df

* removed data file

* removed faulty truediv implementation

* flake8 and documentation updates

* fixed quantile to drop object typed columns

* syntax improvements"

* fixed flatten issue

* fixing flatten issue

* minor updates

* added describe methods

* mean updates and added truediv func

* updates

* updated truediv test

* porting stocks to ubuntu

* hacky solution for describe, mean, median, quantile by transposing df

* removed data file

* removed faulty truediv implementation

* flake8 and documentation updates

* updated mean, median, var, std to handle mixed values

* added describe methods

* mean updates and added truediv func

* updates

* updated truediv test

* porting stocks to ubuntu

* hacky solution for describe, mean, median, quantile by transposing df

* removed data file

* removed faulty truediv implementation

* flake8 and documentation updates

* fixed quantile to drop object typed columns

* syntax improvements"

* fixed flatten issue

* fixing flatten issue

* improved describe syntax
2018-03-15 21:16:59 -07:00
2016-11-22 17:04:24 -08:00
2016-07-08 12:39:11 -07:00
2016-11-22 17:04:24 -08:00

Ray
===

.. image:: https://travis-ci.org/ray-project/ray.svg?branch=master
    :target: https://travis-ci.org/ray-project/ray

.. image:: https://readthedocs.org/projects/ray/badge/?version=latest
    :target: http://ray.readthedocs.io/en/latest/?badge=latest

|

Ray is a flexible, high-performance distributed execution framework.


Ray is easy to install: ``pip install ray``

Example Use
-----------

+------------------------------------------------+----------------------------------------------------+
| **Basic Python**                               | **Distributed with Ray**                           |
+------------------------------------------------+----------------------------------------------------+
|.. code-block:: python                          |.. code-block:: python                              |
|                                                |                                                    |
|  # Execute f serially.                         |  # Execute f in parallel.                          |
|                                                |                                                    |
|                                                |  @ray.remote                                       |
|  def f():                                      |  def f():                                          |
|      time.sleep(1)                             |      time.sleep(1)                                 |
|      return 1                                  |      return 1                                      |
|                                                |                                                    |
|                                                |                                                    |
|                                                |  ray.init()                                        |
|  results = [f() for i in range(4)]             |  results = ray.get([f.remote() for i in range(4)]) |
+------------------------------------------------+----------------------------------------------------+


Ray comes with libraries that accelerate deep learning and reinforcement learning development:

- `Ray Tune`_: Hyperparameter Optimization Framework
- `Ray RLlib`_: Scalable Reinforcement Learning

.. _`Ray Tune`: http://ray.readthedocs.io/en/latest/tune.html
.. _`Ray RLlib`: http://ray.readthedocs.io/en/latest/rllib.html

Installation
------------

Ray can be installed on Linux and Mac with ``pip install ray``.

To build Ray from source or to install the nightly versions, see the `installation documentation`_.

.. _`installation documentation`: http://ray.readthedocs.io/en/latest/installation.html

More Information
----------------

- `Documentation`_
- `Tutorial`_
- `Blog`_
- `Ray paper`_
- `Ray HotOS paper`_

.. _`Documentation`: http://ray.readthedocs.io/en/latest/index.html
.. _`Tutorial`: https://github.com/ray-project/tutorial
.. _`Blog`: https://ray-project.github.io/
.. _`Ray paper`: https://arxiv.org/abs/1712.05889
.. _`Ray HotOS paper`: https://arxiv.org/abs/1703.03924

Getting Involved
----------------

- Ask questions on our mailing list `ray-dev@googlegroups.com`_.
- Please report bugs by submitting a `GitHub issue`_.
- Submit contributions using `pull requests`_.

.. _`ray-dev@googlegroups.com`: https://groups.google.com/forum/#!forum/ray-dev
.. _`GitHub issue`: https://github.com/ray-project/ray/issues
.. _`pull requests`: https://github.com/ray-project/ray/pulls
S
Description
An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.
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