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The Data Wrangling Workshop. Create your own actionable insights using data from multiple raw sources - Second Edition

Język publikacji: angielskim
The Data Wrangling Workshop. Create your own actionable insights using data from multiple raw sources - Second Edition Brian Lipp, Shubhadeep Roychowdhury, Dr. Tirthajyoti Sarkar - okladka książki

The Data Wrangling Workshop. Create your own actionable insights using data from multiple raw sources - Second Edition Brian Lipp, Shubhadeep Roychowdhury, Dr. Tirthajyoti Sarkar - okladka książki

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While a huge amount of data is readily available to us, it is not useful in its raw form. For data to be meaningful, it must be curated and refined.

If you’re a beginner, then The Data Wrangling Workshop will help to break down the process for you. You’ll start with the basics and build your knowledge, progressing from the core aspects behind data wrangling, to using the most popular tools and techniques.

This book starts by showing you how to work with data structures using Python. Through examples and activities, you’ll understand why you should stay away from traditional methods of data cleaning used in other languages and take advantage of the specialized pre-built routines in Python. Later, you’ll learn how to use the same Python backend to extract and transform data from an array of sources, including the internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, the book teaches you how to handle missing or incorrect data, and reformat it based on the requirements from your downstream analytics tool.

By the end of this book, you will have developed a solid understanding of how to perform data wrangling with Python, and learned several techniques and best practices to extract, clean, transform, and format your data efficiently, from a diverse array of sources.
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O autorach książki

Brian Lipp is a technology polygot who is always in search of interesting and innovative technology. His current languages of choice are Python, Go, and Scala.
Shubhadeep Roychowdhury holds a master’s degree in computer science from West Bengal University of Technology and certifications in machine learning from Stanford. He works as a senior software engineer at a Paris-based cybersecurity startup, where he is applying state-of-the-art computer vision and data engineering algorithms and tools to develop cutting-edge products. He often writes about algorithm implementation in Python and similar topics.
Dr. Tirthajyoti Sarkar works as a senior principal engineer in the semiconductor technology domain, where he applies cutting-edge data science/machine learning techniques for design automation and predictive analytics. He writes regularly about Python programming and data science topics. He holds a Ph.D. from the University of Illinois and certifications in artificial intelligence and machine learning from Stanford and MIT.

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