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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

Social network analysis

Social network analysis studies social relations using network theory. Nodes represent participants in a network. Lines between nodes represent relationships. Formally, this is called a graph. Due to the constraints of this book, we will only have a quick look at a simple graph that comes with the popular NetworkX Python library. matplotlib will help with the visualization of the graph.

Install NetworkX with the following command:

$ pip3 install networkx

The import convention for NetworkX is as follows:

import networkx as nx 

NetworkX provides a number of sample graphs, which can be listed as follows:

print([s for s in dir(nx) if s.endswith('graph')]) 

Load the Davis Southern women graph and plot a histogram of the degree of connections:

G = nx.davis_southern_women_graph() 
plt.figure(1) 
plt.hist(nx.degree(G).values()) 

The resulting histogram is shown as follows:

Social network analysis

Draw the graph with node labels as follows:

plt.figure(2) 
pos = nx.spring_layout(G) 
nx.draw...
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