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\n\n[](https://travis-ci.org/sparklingpandas/sparklingpandas)\n\nSparklingPandas\n==============\n\nSparklingPandas aims to make it easy to use the distributed computing power\nof PySpark to scale your data analysis with Pandas. SparklingPandas builds on\nSpark's DataFrame class to give you a polished, pythonic, and Pandas-like API.\n\nDocumentation\n=========\n\nSee [SparklingPandas.com.](http://sparklingpandas.com/)\n\nVideos\n=========\nAn early version of Sparkling Pandas was discussed in [Sparkling Pandas - using \nApache Spark to scale Pandas - Holden Karau and Juliet Hougland](https://www.youtube.com/watch?v=AcyI_V8FeIU)\n\nRequirements\n=========\n\nThe primary requirement of SparklingPandas is that you have a recent (v1.4\ncurrently) version of Spark installed - and Python\n2.7.\n\nUsing\n=========\n\nMake sure you have the SPARK_HOME environment variable set correctly, as\nSparklingPandas uses this for including the PySpark libraries\n\nOther than that you can install SparklingPandas with pip and just import it.\n\nState\n=========\n\nThis is in early development. Feedback is taken seriously and is seriously appreciated.\nAs you can tell, us SparklingPandas are a pretty serious bunch.\n\nSupport\n=========\n\nCheck out our Google group at https://groups.google.com/forum/#!forum/sparklingpandas",
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