Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Python Data Analysis

You're reading from   Python Data Analysis Learn how to apply powerful data analysis techniques with popular open source Python modules

Arrow left icon
Product type Paperback
Published in Oct 2014
Publisher
ISBN-13 9781783553358
Length 348 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Arrow right icon
View More author details
Toc

Table of Contents (17) Chapters Close

Preface 1. Getting Started with Python Libraries 2. NumPy Arrays FREE CHAPTER 3. Statistics and Linear Algebra 4. pandas Primer 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
Index

Filtering out stopwords, names, and numbers


It's a common requirement in text analysis to get rid of stopwords (common words with low information value). NLTK has a stopwords corpora for a number of languages. Load the English stopwords corpus and print some of the words:

sw = set(nltk.corpus.stopwords.words('english'))
print "Stop words", list(sw)[:7]

The following common words are printed:

Stop words ['all', 'just', 'being', 'over', 'both', 'through', 'yourselves']

Notice that all the words in this corpus are in lowercase.

NLTK also has a Gutenberg corpus. The Gutenberg project is a digital library of books mostly with expired copyright, which are available for free on the Internet (see http://www.gutenberg.org/).

Load the Gutenberg corpus and print some of its filenames:

gb = nltk.corpus.gutenberg
print "Gutenberg files", gb.fileids()[-5:]

Some of the titles printed may be familiar to you:

Gutenberg files ['milton-paradise.txt', 'shakespeare-caesar.txt', 'shakespeare-hamlet.txt', 'shakespeare...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image