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Numpy Beginner's Guide (Update)

You're reading from   Numpy Beginner's Guide (Update) Build efficient, high-speed programs using the high-performance NumPy mathematical library

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Product type Paperback
Published in Jun 2015
Publisher
ISBN-13 9781785281969
Length 348 pages
Edition 1st Edition
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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. NumPy Quick Start 2. Beginning with NumPy Fundamentals FREE CHAPTER 3. Getting Familiar with Commonly Used Functions 4. Convenience Functions for Your Convenience 5. Working with Matrices and ufuncs 6. Moving Further with NumPy Modules 7. Peeking into Special Routines 8. Assuring Quality with Testing 9. Plotting with matplotlib 10. When NumPy Is Not Enough – SciPy and Beyond 11. Playing with Pygame A. Pop Quiz Answers B. Additional Online Resources C. NumPy Functions' References
Index

Correlation


Have you noticed that the stock price of some companies will be closely followed by another, usually a rival in the same sector? The theoretical explanation is that because these two companies are in the same type of business, they share the same challenges, require the same materials and resources, and compete for the same type of customers.

You could think of many possible pairs, but you need to check for a real relationship. One way is to take a look at the correlation of the stock returns of both stocks (see https://www.khanacademy.org/math/probability/statistical-studies/types-of-studies/v/correlation-and-causality). A high correlation implies a relationship of some sort. It is not proof of causality though, especially if you don't use sufficient data.

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