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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.
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)
The primary requirement of SparklingPandas is that you have a recent (v1.4
currently) version of Spark installed - <http: spark.apache.org=""> and Python
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
TODO: Brief introduction on what you do with files - including link to relevant help section.