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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 FREE CHAPTER 2. Statistical Visualizations 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 7. Reproducibility in Big Data Analysis

Note

Learning Objectives

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

  • Implement the concept of reproducibility with Jupyter notebooks

  • Perform data gathering in a reproducible way

  • Implement suitable code practices and standards to keep analysis reproducible

  • Avoid the duplication of work with IPython scripts

Note

In this chapter, we will discover how reproducibility plays a vital role in big data analysis.

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