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Python Data Analysis, Second Edition

You're reading from Python Data Analysis, Second Edition Data manipulation and complex data analysis with Python

Product type Paperback

Published in Mar 2017

Publisher Packt

ISBN-13 9781787127487

Length 330 pages

Edition 2nd Edition

Languages

Python

Tools

Scikit-learn

Concepts

Data Analysis

Author (1):

Ivan Idris

View More author details

Table of Contents (16) Chapters

Preface

1. Getting Started with Python Libraries FREE CHAPTER

2. NumPy Arrays

3. The Pandas Primer

4. Statistics and Linear Algebra

5. Retrieving, Processing, and Storing Data

6. Data Visualization

7. Signal Processing and Time Series

8. Working with Databases

9. Analyzing Textual Data and Social Media

10. Predictive Analytics and Machine Learning

11. Environments Outside the Python Ecosystem and Cloud Computing

12. Performance Tuning, Profiling, and Concurrency

A. Key Concepts

B. Useful Functions

C. Online Resources

Parsing HTML with Beautiful Soup

Hypertext Markup Language (HTML) is the fundamental technology used to create web pages. HTML is composed of HTML elements that consist of so-called tags enveloped in slanted brackets (for example, <html>). Often, tags are paired with a starting and closing tag in a hierarchical, tree-like structure. An HTML-related draft specification was first published by Berners-Lee in 1991. Initially, there were only 18 HTML elements. The formal HTML definition was published by the Internet Engineering Task Force (IETF) in 1993. The IETF completed the HTML 2.0 standard in 1995. Around 2013, the latest HTML version, HTML5, was specified. HTML is not a very strict standard compared to XHTML and XML.

Modern browsers tolerate a lot of violations of the standard, making web pages a form of unstructured data. We can treat HTML as a big string and perform string operations on it with regular expressions, for example. This approach works only for simple projects.

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Authors (1)

Idris

Idris

Ivan Idris has an MSc in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a Java developer, data warehouse developer, and QA analyst. His main professional interests are business intelligence, big data, and cloud computing. Ivan Idris enjoys writing clean, testable code and interesting technical articles. Ivan Idris is the author of NumPy 1.5. Beginner's Guide and NumPy Cookbook by Packt Publishing.

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