This post discusses similar constructs in Python and Pyspark. As in my earlier post R vs Python: Different similarities and similar differences the focus is on the key and common constructs to highlight the similarities.
Important Note:You can also access this notebook at databricks public site Big Data-1: Move into the big league:Graduate from Python to Pyspark (the formatting here is much better!!).
For this notebook I have used Databricks community edition
You can download the notebook from Github at Big Data-1:PythontoPysparkAndRtoSparkR
Hope you found this useful!
Note: There are still a few more important constructs which I will be adding to this post.
Also see
1. My book “Deep Learning from first principles” now on Amazon
2. My book ‘Practical Machine Learning in R and Python: Second edition’ on Amazon
3. Re-introducing cricketr! : An R package to analyze performances of cricketers
4. GooglyPlus: yorkr analyzes IPL players, teams, matches with plots and tables
5. Deblurring with OpenCV: Weiner filter reloaded
6. Design Principles of Scalable, Distributed Systems
Giga thoughts ... 
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