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Data Wrangling with Python

You're reading from   Data Wrangling with Python Creating actionable data from raw sources

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789800111
Length 452 pages
Edition 1st Edition
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Authors (2):
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Shubhadeep Roychowdhury Shubhadeep Roychowdhury
Author Profile Icon Shubhadeep Roychowdhury
Shubhadeep Roychowdhury
Dr. Tirthajyoti Sarkar Dr. Tirthajyoti Sarkar
Author Profile Icon Dr. Tirthajyoti Sarkar
Dr. Tirthajyoti Sarkar
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Table of Contents (12) Chapters Close

Data Wrangling with Python
Preface
1. Introduction to Data Wrangling with Python FREE CHAPTER 2. Advanced Data Structures and File Handling 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. Application of Data Wrangling in Real Life Appendix

Summary


In this chapter, we learned about the workings of advanced data structures such as stacks and queues. We implemented and manipulated both stacks and queues. We then focused on different methods of functional programming, including iterators, and combined lists and functions together. After this, we looked at the OS-level functions and the management of environment variables and files. We also examined a clean way to deal with files, and we created our own CSV parser in the last activity.

In the next chapter, we will be dealing with the three most important libraries, namely NumPy, pandas, and matplotlib.

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