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Practical Data Analysis

You're reading from Practical Data Analysis

Product type Book

Published in Oct 2013

Publisher Packt

ISBN-13 9781783280995

Pages 360 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Hector Cuesta

Table of Contents (24) Chapters

Practical Data Analysis

Credits

Foreword

About the Author

Acknowledgments

About the Reviewers

www.PacktPub.com

Preface

1. Getting Started

2. Working with Data

3. Data Visualization

4. Text Classification

5. Similarity-based Image Retrieval

6. Simulation of Stock Prices

7. Predicting Gold Prices

8. Working with Support Vector Machines

9. Modeling Infectious Disease with Cellular Automata

10. Working with Social Graphs

11. Sentiment Analysis of Twitter Data

12. Data Processing and Aggregation with MongoDB

13. Working with MapReduce

14. Online Data Analysis with IPython and Wakari

Setting Up the Infrastructure

Index

Chapter 2. Working with Data

Building real world's data analytics requires accurate data. In this chapter we discuss how to obtain, clean, normalize, and transform raw data into a standard format such as Comma-Separated Values (CSV) or JavaScript Object Notation (JSON) using OpenRefine.

In this chapter we will cover:

Datasource
- Open data
- Text files
- Excel files
- SQL databases
- NoSQL databases
- Multimedia
- Web scraping
Data scrubbing
- Statistical methods
- Text parsing
- Data transformation
Data formats
- CSV
- JSON
- XML
- YAML
Getting started with OpenRefine

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Authors (1)

Hector Cuesta

Hector Cuesta is founder and Chief Data Scientist at Dataxios, a machine intelligence research company. Holds a BA in Informatics and a M.Sc. in Computer Science. He provides consulting services for data-driven product design with experience in a variety of industries including financial services, retail, fintech, e-learning and Human Resources. He is an enthusiast of Robotics in his spare time. You can follow him on Twitter at https://twitter.com/hmCuesta.

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