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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

The Basics of Web Scraping and the Beautiful Soup Library

In today's connected world, one of the most valued and widely used skill for a data wrangling professional is the ability to extract and read data from web pages and databases hosted on the web. Most organizations host data on the cloud (public or private), and the majority of web microservices these days provide some kind of API for the external users to access data:

Figure 7.1: Data wrangling HTTP request and an XML/JSON reply

It is necessary that, as a data wrangling engineer, you know about the structure of web pages and Python libraries so that you are able to extract data from a web page. The World Wide Web is an ever-growing, ever-changing universe, in which different data exchange protocols and formats are used. A few of these are widely used and have become standard.

Libraries in Python

Python comes equipped with built-in modules, such as urllib 3, which that can place HTTP requests over the internet and receive data from the...

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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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