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Artem Ryblov’s Data Science Weekly Artem Ryblov’s Data Science Weekly @data_science_weekly · 685 subscribers
Post #109 516
Data Analysis with Python and PySpark by Jonathan Rioux

In Data Analysis with Python and PySpark you will learn how to:

- Manage your data as it scales across multiple machines
- Scale up your data programs with full confidence
- Read and write data to and from a variety of sources and formats
- Deal with messy data with PySpark’s data manipulation functionality
- Discover new data sets and perform exploratory data analysis
- Build automated data pipelines that transform, summarize, and get insights from data
- Troubleshoot common PySpark errors
- Creating reliable long-running jobs

Data Analysis with Python and PySpark is your guide to delivering successful Python-driven data projects. Packed with relevant examples and essential techniques, this practical book teaches you to build pipelines for reporting, machine learning, and other data-centric tasks. Quick exercises in every chapter help you practice what you’ve learned, and rapidly start implementing PySpark into your data systems. No previous knowledge of Spark is required.

Link: Direct

Navigational hashtags: #armknowledgesharing #armbooks
General hashtags: #spark #pyspark #bigdata

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