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Practical Data Analysis Using Jupyter Notebook

You're reading from   Practical Data Analysis Using Jupyter Notebook Learn how to speak the language of data by extracting useful and actionable insights using Python

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Product type Paperback
Published in Jun 2020
Publisher Packt
ISBN-13 9781838826031
Length 322 pages
Edition 1st Edition
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Author (1):
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Marc Wintjen Marc Wintjen
Author Profile Icon Marc Wintjen
Marc Wintjen
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Table of Contents (18) Chapters Close

Preface 1. Section 1: Data Analysis Essentials
2. Fundamentals of Data Analysis FREE CHAPTER 3. Overview of Python and Installing Jupyter Notebook 4. Getting Started with NumPy 5. Creating Your First pandas DataFrame 6. Gathering and Loading Data in Python 7. Section 2: Solutions for Data Discovery
8. Visualizing and Working with Time Series Data 9. Exploring, Cleaning, Refining, and Blending Datasets 10. Understanding Joins, Relationships, and Aggregates 11. Plotting, Visualization, and Storytelling 12. Section 3: Working with Unstructured Big Data
13. Exploring Text Data and Unstructured Data 14. Practical Sentiment Analysis 15. Bringing It All Together 16. Works Cited
17. Other Books You May Enjoy
Plotting, Visualization, and Storytelling

This chapter will teach you how to visualize data by exploring additional chart options such as histograms, box plots, and scatter plots to advance your data literacy skills. Storytelling with data starts with understanding the relationships that exist within the numbers, so we will learn about distribution curves and how they apply to analysis. During this discovery phase of analysis of your data, you will learn how to identify outliers and patterns along with best practices in visualizing geographic data. We will wrap up this chapter by learning the difference between correlation versus causation.

We will cover the following topics in this chapter:

  • Explaining distribution analysis
  • Understanding outliers and trends
  • Geoanalytical techniques and tips
  • Finding patterns in data
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