Using OpenRefine 1st Edition by Ruben Verborgh, Max De Wilde ISBN 9781783289080 1783289082

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Product details:

ISBN 10: 1783289082
ISBN 13: 9781783289080
Author: Ruben Verborgh, Max De Wilde

Data today is like gold – but how can you manage your most valuable assets? Managing large datasets used to be a task for specialists, but the game has changed – data analysis is an open playing field. Messy data is now in your hands! With OpenRefine the task is a little easier, as it provides you with the necessary tools for cleaning and presenting even the most complex data. Once it’s clean, that’s when you can start finding value. Using OpenRefine takes you on a practical and actionable through this popular data transformation tool. Packed with cookbook style recipes that will help you properly get to grips with data, this book is an accessible tutorial for anyone that wants to maximize the value of their data. This book will teach you all the necessary skills to handle any large dataset and to turn it into high-quality data for the Web. After you learn how to analyze data and spot issues, we’ll see how we can solve them to obtain a clean dataset. Messy and inconsistent data is recovered through advanced techniques such as automated clustering. We’ll then show extract links from keyword and full-text fields using reconciliation and named-entity extraction. Using OpenRefine is more than a manual: it’s a guide stuffed with tips and tricks to get the best out of your data.

Using OpenRefine 1st Edition Table of contents:

1. Diving Into OpenRefine

Introducing OpenRefine

Recipe 1 – installing OpenRefine

Windows

Mac

Linux

Recipe 2 – creating a new project

File formats supported by OpenRefine

Recipe 3 – exploring your data

Recipe 4 – manipulating columns

Collapsing and expanding columns

Moving columns around

Renaming and removing columns

Recipe 5 – using the project history

Recipe 6 – exporting a project

Recipe 7 – going for more memory

Windows

Mac

Linux

Summary

2. Analyzing and Fixing Data

Recipe 1 – sorting data

Reordering rows

Recipe 2 – faceting data

Text facets

Numeric facets

Customized facets

Faceting by star or flag

Recipe 3 – detecting duplicates

Recipe 4 – applying a text filter

Recipe 5 – using simple cell transformations

Recipe 6 – removing matching rows

Summary

3. Advanced Data Operations

Recipe 1 – handling multi-valued cells

Recipe 2 – alternating between rows and records mode

Recipe 3 – clustering similar cells

Recipe 4 – transforming cell values

Recipe 5 – adding derived columns

Recipe 6 – splitting data across columns

Recipe 7 – transposing rows and columns

Summary

4. Linking Datasets

Recipe 1 – reconciling values with Freebase

Recipe 2 – installing extensions

Recipe 3 – adding a reconciliation service

Recipe 4 – reconciling with Linked Data

Recipe 5 – extracting named entities

Summary

A. Regular Expressions and GREL

Regular expressions for text patterns

Character classes

Quantifiers

Anchors

Choices

Groups

Overview

General Refine Expression Language (GREL)

Transforming data

Creating custom facets

Solving problems with GREL

Index

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Tags: Ruben Verborgh, Max De Wilde, Using OpenRefine