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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 2. Statistical Visualizations

Note

Learning Objectives

We will start our journey by understanding the power of Python to manipulate and visualize data, creating useful analysis.

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

  • Use graphs for data analysis

  • Create graphs of various types

  • Change graph parameters such as color, title, and axis

  • Export graphs for presentation, printing, and other uses

Note

In this chapter, we will illustrate how the students can generate visualizations with Matplotlib and Seaborn.

You have been reading a chapter from
Big Data Analysis with Python
Published in: Apr 2019
Publisher: Packt
ISBN-13: 9781789955286
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