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Data Wrangling with Python

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

Product type Paperback

Published in Feb 2019

Publisher Packt

ISBN-13 9781789800111

Length 452 pages

Edition 1st Edition

Languages

Python

Tools

NumPy

Concepts

Data Analysis

Authors (2):

Shubhadeep Roychowdhury

Dr. Tirthajyoti Sarkar

View More author details

Table of Contents (12) Chapters

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

Introduction to Beautiful Soup 4 and Web Page Parsing

The ability to read and understand web pages is one of paramount interest for a person collecting and formatting data. For example, consider the task of gathering data about movies and then formatting it for a downstream system. Data for the movies is best obtained by the websites such as IMDB and that data does not come pre-packaged in nice forms(CSV, JSON< and so on), so you need to know how to download and read web page.

Furthermore, you also need to be equipped with the knowledge of the structure of a web page so that you can design a system that can search for (query) a particular piece of information from a whole web page and get the value of it. This involves understanding the grammar of markup languages and being able to write something that can parse them. Doing this, and keeping all the edge cases in mind, for something like HTML is already incredibly complex, and if you extend the scope of the bespoke markup language to include...

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Authors (2)

Dr. Tirthajyoti Sarkar

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.

See other products by Dr. Tirthajyoti Sarkar

Shubhadeep Roychowdhury

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.

See other products by Shubhadeep Roychowdhury

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