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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
Authors (3):
Brian Lipp Brian Lipp
Profile icon Brian Lipp
Shubhadeep Roychowdhury Shubhadeep Roychowdhury
Profile icon Shubhadeep Roychowdhury
Dr. Tirthajyoti Sarkar Dr. Tirthajyoti Sarkar
Profile icon Dr. Tirthajyoti Sarkar
View More author details

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

An Extension to Data Wrangling

This is the concluding chapter of this book; we want to give you a broad overview of some of the exciting technologies and frameworks that you may need to learn about beyond data wrangling to work as a full-stack data scientist. Data wrangling is an essential part of the whole data science and analytics pipeline, but it is not the whole enterprise. You have learned invaluable skills and techniques in this book, but it is always good to broaden your horizons and look beyond to see what other tools that are out there that can give you an edge in this competitive and ever-changing world.

Additional Skills Required to Become a Data Scientist

To practice as a fully qualified data scientist/analyst, you should have some basic skills in your repertoire, irrespective of the particular programming language you choose to focus on. These skills and know-how are language-agnostic and can be utilized with any framework that you have to embrace, depending on...

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