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The Data Wrangling Workshop - Second Edition

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

Product type Book
Published in Jul 2020
Publisher Packt
ISBN-13 9781839215001
Pages 576 pages
Edition 2nd Edition
Languages
Concepts
Authors (3):
Brian Lipp Brian Lipp
Profile icon Brian Lipp
LinkedIn
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.
See other products by Brian Lipp
Shubhadeep Roychowdhury Shubhadeep Roychowdhury
Profile icon Shubhadeep Roychowdhury
LinkedIn
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.
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Dr. Tirthajyoti Sarkar Dr. Tirthajyoti Sarkar
Profile icon Dr. Tirthajyoti Sarkar
LinkedIn
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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Table of Contents (11) Chapters

Preface
1. Introduction to Data Wrangling with Python 2. Advanced Operations on Built-In Data Structures 3. Introduction to NumPy, Pandas, and Matplotlib 4. A Deep Dive into Data Wrangling with Python 5. Getting Comfortable with Different Kinds of Data Sources 6. Learning the Hidden Secrets of Data Wrangling 7. Advanced Web Scraping and Data Gathering 8. RDBMS and SQL 9. Applications in Business Use Cases and Conclusion of the Course Appendix

Introduction

In the preceding chapters, we covered some advanced data structures, such as stack, queue, iterator, and file operations in Python. In this chapter, we will cover three essential libraries, namely NumPy, pandas, and matplotlib. NumPy is an advanced math library in Python with an extensive range of functionality. pandas is a library built on NumPy that allows developers to model the data in a table structure similar to a database; malplotlib, on the other hand, is a charting library that is influenced by Matlab. With these libraries, you will be able to handle most data wrangling tasks.

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Authors (3)

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Profile icon Brian Lipp
LinkedIn
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.
See other products by Brian Lipp
Profile icon Shubhadeep Roychowdhury
LinkedIn
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.
See other products by Shubhadeep Roychowdhury
Profile icon Dr. Tirthajyoti Sarkar
LinkedIn
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.
See other products by Dr. Tirthajyoti Sarkar
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