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You're reading from  The Data Wrangling Workshop - Second Edition

Product typeBook
Published inJul 2020
Reading LevelIntermediate
PublisherPackt
ISBN-139781839215001
Edition2nd Edition
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Authors (3):
Brian Lipp
Brian Lipp
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Brian Lipp

Brian Lipp is a Technology Polyglot, Engineer, and Solution Architect with a wide skillset in many technology domains. His programming background has ranged from R, Python, and Scala, to Go and Rust development. He has worked on Big Data systems, Data Lakes, data warehouses, and backend software engineering. Brian earned a Master of Science, CSIS from Pace University in 2009. He is currently a Sr. Data Engineer working with large Tech firms to build Data Ecosystems.
Read more about Brian Lipp

Shubhadeep Roychowdhury
Shubhadeep Roychowdhury
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Shubhadeep Roychowdhury

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.
Read more about Shubhadeep Roychowdhury

Dr. Tirthajyoti Sarkar
Dr. Tirthajyoti Sarkar
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Dr. Tirthajyoti Sarkar

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.
Read more about Dr. Tirthajyoti Sarkar

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Advanced List Comprehension and the zip Function

In this section, we will deep dive into the heart of list comprehension. We have already seen a basic form of it, including something as simple as a = [i for i in range(0, 30)] to something a bit more complex that involves one conditional statement. However, as we already mentioned, list comprehension is a very powerful tool and, in this section, we will explore this amazing tool further. We will investigate another close relative of list comprehension called generators, which also provides a way to create lists, and work with zip and its related functions and methods. By the end of this section, you will be confident in handling complicated logical problems.

Introduction to Generator Expressions

In the previous chapter, while discussing advanced data structures, we witnessed functions such as repeat. We said that they represent a special type of function known as iterators. We also showed you how the lazy evaluation of an iterator...

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The Data Wrangling Workshop - Second Edition
Published in: Jul 2020Publisher: PacktISBN-13: 9781839215001

Authors (3)

author image
Brian Lipp

Brian Lipp is a Technology Polyglot, Engineer, and Solution Architect with a wide skillset in many technology domains. His programming background has ranged from R, Python, and Scala, to Go and Rust development. He has worked on Big Data systems, Data Lakes, data warehouses, and backend software engineering. Brian earned a Master of Science, CSIS from Pace University in 2009. He is currently a Sr. Data Engineer working with large Tech firms to build Data Ecosystems.
Read more about Brian Lipp

author image
Shubhadeep Roychowdhury

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.
Read more about Shubhadeep Roychowdhury

author image
Dr. Tirthajyoti Sarkar

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.
Read more about Dr. Tirthajyoti Sarkar