From Pandas to PySpark DataFrame

From Pandas to PySpark DataFrame


39 Lessons

3h 3min

Certificate of Completion

AI Explanations
AI Explanations
From Pandas to PySpark DataFrame
54 Playgrounds
27 Illustrations

Takeaway Skills

A working knowledge of Apache Spark and the PySpark library for Python

A strong understanding of the advantages of using PySpark instead of Pandas for processing large datasets

The ability to calculate some Metrics or produce aggregated analytics reporting solutions

The ability to write Production Code in PySpark

Course Overview

Pandas is a popular Python library used to manipulate data, but it has certain limitations in its ability to process large datasets. The Apache Spark analytics library offers significant performance improvements. This course will help improve your Python-based data processing by leveraging Apache Spark’s multithreading capabilities through the PySpark library. You’ll start by reading data into a PySpark DataFrame before performing basic input/output functions, such as renaming attributes, selecting, and wr...Show More


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