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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

Summary

This chapter covered the basics of loading data from database, disk, and web sources. It also covered basic SQL queries and pandas' access and search functions. The last sections of the chapter introduced common types of plots using Seaborn. You should be able to transfer these basic code examples to many of your analysis projects for data mining. The examples were chosen to demonstrate how to use these libraries, so if your specific need or requirement is not covered, you should be able to replace the method calls with ease, simply by looking up the syntax on the library's website. The next chapter will cover data wrangling and cleaning up data in order to prepare it for analysis.

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