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Enable Pandas on PySpark

Project description

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SparklingPandas
==============

SparklingPandas aims to make it easy to use the distributed computing power
of PySpark to scale your data analysis with Pandas. SparklingPandas builds on
Spark's DataFrame class to give you a polished, pythonic, and Pandas like API.

Documentation
=========

None (right now).


Videos
=========
An early version of Sparkling Pandas was discussed in [Sparkling Pandas - using
Apache Spark to scale Pandas - Holden Karau and Juliet Hougland](https://www.youtube.com/watch?v=AcyI_V8FeIU)

Requirements
=========

The primary requirement of SparklingPandas is that you have a recent (v1.4
currently) version of Spark installed - <http://spark.apache.org> and Python
2.7.

Using
=========

Make sure you have the SPARK_HOME enviroment variable set correctly, as
SparklingPandas uses this for including the PySpark libraries

Other than that you can install SparklingPandas with pip and just import it.

State
=========

This is in early development. Feedback is taken seriously and is seriously appreciated.
As you can tell Us SparklingPandas are a pretty serious bunch.

Support
=========

Check out our Google group at https://groups.google.com/forum/#!forum/sparklingpandas

Project details


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sparklingpandas-0.0.4.tar.gz (18.1 MB view hashes)

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