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You're reading from Practical Data Analysis For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.

Product type Paperback

Published in Oct 2013

Publisher Packt

ISBN-13 9781783280995

Length 360 pages

Edition 1st Edition

Languages

Python

Tools

NLTK

Concepts

Data Analysis

Author (1):

Hector Cuesta

View More author details

Table of Contents (24) Chapters

Practical Data Analysis

Credits

Foreword

About the Author

Acknowledgments

About the Reviewers

www.PacktPub.com

Preface

1. Getting Started FREE CHAPTER

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

The rest of the chapter is locked

Tech Concepts

Programming languages

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You're reading from Practical Data Analysis For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.

Table of Contents (24) Chapters

Chapter 2. Working with Data

Authors (1)

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You're reading from Practical Data Analysis For small businesses, analyzing the information contained in their data using open source technology could be game-changing. All you need is some basic programming and mathematical skills to do just that.

Table of Contents (24) Chapters

Chapter 2. Working with Data

Authors (1)

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