The Koalas project makes data scientists more productive when interacting with big data, by implementing the pandas DataFrame API on top of Apache Spark.
pandas is the de facto standard (single-node) DataFrame implementation in Python, while Spark is the de facto standard for big data processing.
With this package, you can:
Be immediately productive with Spark, with no learning curve, if you are already familiar with pandas.
Have a single codebase that works both with pandas (tests, smaller datasets) and with Spark (distributed datasets).
This project is currently in beta and is rapidly evolving, with a bi-weekly release cadence. We would love to have you try it and give us feedback,
through our mailing lists or GitHub issues.
Try the Koalas 10 minutes tutorial on a live Jupyter notebook here.
The initial launch can take up to several minutes.