Using OpenRefine

With this book on OpenRefine, managing and cleaning your large datasets suddenly got a lot easier! With a cookbook approach and free datasheets included, you’ll quickly and painlessly improve your data managing capabilities.

Using OpenRefine

Starting
Ruben Verborgh, Max De Wilde

5 customer reviews
With this book on OpenRefine, managing and cleaning your large datasets suddenly got a lot easier! With a cookbook approach and free datasheets included, you’ll quickly and painlessly improve your data managing capabilities.
$20.99
$34.99
RRP $20.99
RRP $34.99
eBook
Print + eBook

Get unlimited access to this and 3,500 other courses today!

With unlimited access to a constantly growing library of over 3,500 courses, a subscription to Mapt gives you everything you need to get that next promotion or to land that dream job. Cancel anytime.

+ Collection
Free Sample

Book Details

ISBN 139781783289080
Paperback114 pages

Book Description

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.

Table of Contents

Chapter 1: Diving Into OpenRefine
Introducing OpenRefine
Recipe 1 – installing OpenRefine
Recipe 2 – creating a new project
Recipe 3 – exploring your data
Recipe 4 – manipulating columns
Recipe 5 – using the project history
Recipe 6 – exporting a project
Recipe 7 – going for more memory
Summary
Chapter 2: Analyzing and Fixing Data
Recipe 1 – sorting data
Recipe 2 – faceting data
Recipe 3 – detecting duplicates
Recipe 4 – applying a text filter
Recipe 5 – using simple cell transformations
Recipe 6 – removing matching rows
Summary
Chapter 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
Chapter 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

What You Will Learn

  • Import data in various formats
  • Explore datasets in a matter of seconds
  • Apply basic and advanced cell transformations
  • Deal with cells that contain multiple values
  • Create instantaneous links between datasets
  • Filter and partition your data easily with regular expressions
  • Use named-entity extraction on full-text fields to automatically identify topics
  • Perform advanced data operations with the General Refine Expression Language

Authors

Table of Contents

Chapter 1: Diving Into OpenRefine
Introducing OpenRefine
Recipe 1 – installing OpenRefine
Recipe 2 – creating a new project
Recipe 3 – exploring your data
Recipe 4 – manipulating columns
Recipe 5 – using the project history
Recipe 6 – exporting a project
Recipe 7 – going for more memory
Summary
Chapter 2: Analyzing and Fixing Data
Recipe 1 – sorting data
Recipe 2 – faceting data
Recipe 3 – detecting duplicates
Recipe 4 – applying a text filter
Recipe 5 – using simple cell transformations
Recipe 6 – removing matching rows
Summary
Chapter 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
Chapter 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

Book Details

ISBN 139781783289080
Paperback114 pages
Read More
From 5 reviews

Read More Reviews