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Big Data Analysis with Python

You're reading from   Big Data Analysis with Python Combine Spark and Python to unlock the powers of parallel computing and machine learning

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789955286
Length 276 pages
Edition 1st Edition
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Authors (3):
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Ivan Marin Ivan Marin
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Ivan Marin
Sarang VK Sarang VK
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Sarang VK
Ankit Shukla Ankit Shukla
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Ankit Shukla
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Toc

Table of Contents (11) Chapters Close

Big Data Analysis with Python
Preface
1. The Python Data Science Stack 2. Statistical Visualizations FREE CHAPTER 3. Working with Big Data Frameworks 4. Diving Deeper with Spark 5. Handling Missing Values and Correlation Analysis 6. Exploratory Data Analysis 7. Reproducibility in Big Data Analysis 8. Creating a Full Analysis Report Appendix

Chapter 5. Handling Missing Values and Correlation Analysis

Note

Learning Objectives

By the end of this chapter, you will be able to:

  • Detect and handle missing values in data using PySpark

  • Describe correlations between variables

  • Compute correlations between two or more variables in PySpark

  • Create a correlation matrix using PySpark

Note

In this chapter, we will be using the Iris dataset to handle missing data and find correlations between data values.

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