Book Image

Python Data Analysis - Second Edition

By : Ivan Idris
Book Image

Python Data Analysis - Second Edition

By: Ivan Idris

Overview of this book

Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries.
Table of Contents (22 chapters)
Python Data Analysis - Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Key Concepts
Online Resources

Parsing RSS and Atom feeds


Really Simple Syndication (RSS) and Atom feeds (refer to http://en.wikipedia.org/wiki/RSS) are often used for blogs and news. These types of feeds follow the publish/subscribe model. For instance, Packt Publishing has an RSS feed with article and book announcements. We can subscribe to the feed to get timely updates. The Python feedparser module allows us to parse RSS and Atom feeds easily without dealing with a lot of technical details. The feedparser module can be installed with pip as follows:

$ pip3 install feedparser

After parsing an RSS file, we can access the underlying data using a dotted notation. Parse the Packt Publishing RSS feed and print the number of entries:

import feedparser as fp 
 
rss = fp.parse("http://www.packtpub.com/rss.xml") 
 
print("# Entries", len(rss.entries)) 

The number of entries is printed (the number may vary for each program run):

# Entries 10

Print entry titles and summaries if the entry contains the...