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.

See SparklingPandas.com.

An early version of Sparkling Pandas was discussed in Sparkling Pandas - using Apache Spark to scale Pandas - Holden Karau and Juliet Hougland

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.

Make sure you have the SPARK_HOME environment 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.

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

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