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Big Data Analysis with Python

You're reading from  Big Data Analysis with Python

Product type Book
Published in Apr 2019
Publisher Packt
ISBN-13 9781789955286
Pages 276 pages
Edition 1st Edition
Languages
Authors (3):
Ivan Marin Ivan Marin
Profile icon Ivan Marin
Ankit Shukla Ankit Shukla
Profile icon Ankit Shukla
Sarang VK Sarang VK
Profile icon Sarang VK
View More author details

Table of Contents (11) Chapters

Big Data Analysis with Python
Preface
1. The Python Data Science Stack 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 6. Exploratory 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 by using IPython scripts

Note

In this chapter, we will learn what problem definition is and how to use the KPI analysis techniques to enable coherent and well rounded analysis from the data.

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