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The Data Wrangling Workshop

You're reading from   The Data Wrangling Workshop Create your own actionable insights using data from multiple raw sources

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839215001
Length 576 pages
Edition 2nd Edition
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Authors (3):
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Dr. Tirthajyoti Sarkar Dr. Tirthajyoti Sarkar
Author Profile Icon Dr. Tirthajyoti Sarkar
Dr. Tirthajyoti Sarkar
Shubhadeep Roychowdhury Shubhadeep Roychowdhury
Author Profile Icon Shubhadeep Roychowdhury
Shubhadeep Roychowdhury
Brian Lipp Brian Lipp
Author Profile Icon Brian Lipp
Brian Lipp
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Toc

Table of Contents (11) Chapters Close

Preface
1. Introduction to Data Wrangling with Python 2. Advanced Operations on Built-In Data Structures FREE CHAPTER 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

Summary

In this chapter, we learned about data wrangling and looked at examples from various real-life data science situations where data wrangling is very useful. We moved on to learn about the different built-in data structures that Python has to offer. We got our hands dirty by exploring lists, sets, dictionaries, tuples, and strings. These are the fundamental building blocks of Python data structures, and we need them all the time when working and manipulating data in Python. We did several small hands-on exercises to learn more about them. We finished this chapter with carefully designed activities that let us combine a lot of different tricks from all the different data structures and let us observe the interplay between all of them. In the next chapter, we will learn about the data structures in Python and utilize them to solve problems.

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