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Mastering Numerical Computing with NumPy

You're reading from   Mastering Numerical Computing with NumPy Master scientific computing and perform complex operations with ease

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Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788993357
Length 248 pages
Edition 1st Edition
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Authors (3):
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Tiago Antao Tiago Antao
Author Profile Icon Tiago Antao
Tiago Antao
Mert Cuhadaroglu Mert Cuhadaroglu
Author Profile Icon Mert Cuhadaroglu
Mert Cuhadaroglu
Umit Mert Cakmak Umit Mert Cakmak
Author Profile Icon Umit Mert Cakmak
Umit Mert Cakmak
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Table of Contents (11) Chapters Close

Preface 1. Working with NumPy Arrays FREE CHAPTER 2. Linear Algebra with NumPy 3. Exploratory Data Analysis of Boston Housing Data with NumPy Statistics 4. Predicting Housing Prices Using Linear Regression 5. Clustering Clients of a Wholesale Distributor Using NumPy 6. NumPy, SciPy, Pandas, and Scikit-Learn 7. Advanced Numpy 8. Overview of High-Performance Numerical Computing Libraries 9. Performance Benchmarks 10. Other Books You May Enjoy

Computing correlations

This section is dedicated to bivariate analysis, where you analyze two columns. In such cases, we generally investigate the association between these two variables, which is called correlation. Correlation shows the relationship between two variables and answers questions such as what will happen to variable A if variable B increases by 10%? In this section, we will explain how to calculate the correlation of our data and represent it in a two-dimensional scatter plot.

In general, correlation refers to any statistical dependency. A correlation coefficient is a quantitative value that calculates the measure of correlation. You can think of the relationship between correlation and a correlation coefficient as being of a similar relationship between a hygrometer and humidity. One of the most popular types of correlation coefficient is the Pearson product-moment...

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