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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

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Product type Paperback
Published in Mar 2017
Publisher Packt
ISBN-13 9781787127487
Length 330 pages
Edition 2nd Edition
Languages
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Author (1):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Table of Contents (16) Chapters Close

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

Analyzing word frequencies

The NLTK FreqDist class encapsulates a dictionary of words and counts for a given list of words. Load the Gutenberg text of Julius Caesar by William Shakespeare. Let's filter out the stopwords and punctuation:

punctuation = set(string.punctuation) 
filtered = [w.lower() for w in words if w.lower() not in sw and w.lower() not in punctuation] 

Create a FreqDist object and print the associated keys and values with the highest frequency:

fd = nltk.FreqDist(filtered) 
print("Words", fd.keys()[:5]) 
print("Counts", fd.values()[:5]) 

The keys and values are printed as follows:

Words ['d', 'caesar', 'brutus', 'bru', 'haue']
Counts [215, 190, 161, 153, 148]

The first word in this list is, of course, not an English word, so we may need to add the heuristic that words have a minimum of two characters. The NLTK FreqDist class allows dictionary-like access, but it also has convenience methods. Get the...

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