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Python Data Mining Quick Start Guide

You're reading from   Python Data Mining Quick Start Guide A beginner's guide to extracting valuable insights from your data

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789800265
Length 188 pages
Edition 1st Edition
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Author (1):
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Nathan Greeneltch Nathan Greeneltch
Author Profile Icon Nathan Greeneltch
Nathan Greeneltch
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Table of Contents (9) Chapters Close

Preface 1. Data Mining and Getting Started with Python Tools 2. Basic Terminology and Our End-to-End Example FREE CHAPTER 3. Collecting, Exploring, and Visualizing Data 4. Cleaning and Readying Data for Analysis 5. Grouping and Clustering Data 6. Prediction with Regression and Classification 7. Advanced Topics - Building a Data Processing Pipeline and Deploying It 8. Other Books You May Enjoy

Collecting, Exploring, and Visualizing Data

As a first step, it is important to understand how to acquire data and how to access it in computer memory. Once data is loaded, sound practices for exploration can save time downstream. This chapter will start by showing you how to interact with different data sources such as databases, disks, and streaming. Despite the practicality of these topics, many new analysts overlook them. Indeed, you cannot actually do any work if you cannot get past this beginning step. The second half of the chapter will introduce you to Seaborn for visualizing data, and then recommend types of plots for relevant and popular problem statements.

The following topics will be covered in this chapter:

  • Types of data sources and loading into pandas
  • Access, search, and sanity checks with pandas
  • Basic plotting in Seaborn
  • Relevant types of plots for visualizing...
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