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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

Chapter 6. Data Visualization

One of the first steps in data analysis is visualization. Even when looking at a table of values, we can form a mental image of what the data might look like when graphed. Data visualization involves the conception and analysis of the visual representation of information, signifying data that has been abstracted in some formal pattern, including properties or quantities for units of measurement of the data. Data visualization is closely associated with scientific visualization and statistical graphics. The Python matplotlib library is a well-known plotting library based on NumPy, which we will be using in this chapter. It has an object-oriented and a procedural Matlab-like API, which can be used in parallel. A gallery with matplotlib examples can be found at http://matplotlib.org/gallery.html is a cloud based service for data visualization. We shall briefly cover this service at the end of this chapter. The following is a list of topics that...

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