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Using OpenRefine

Book Description

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.

  • Create links between your dataset and others in an instant
  • Effectively transform data with regular expressions and the General Refine Expression Language
  • Spot issues in your dataset and take effective action with just a few clicks

In Detail

Data is supposed to be the new gold, but how can you unlock the value in your data? Managing large datasets used to be a task for specialists, but you don't have to worry about inconsistencies or errors anymore. OpenRefine lets you clean, link, and publish your dataset in a breeze.

Using OpenRefine takes you on a practical tour of all the handy features of this well-known data transformation tool. It is a hands-on recipe book that teaches you data techniques by example. Starting from the basics, it gradually transforms you into an OpenRefine expert.

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

  1. Using OpenRefine
    1. Table of Contents
    2. Using OpenRefine
    3. Credits
    4. Foreword
    5. About the Authors
    6. About the Reviewers
    7. www.PacktPub.com
      1. Support files, eBooks, discount offers and more
        1. Why Subscribe?
        2. Free Access for Packt account holders
    8. Preface
      1. What this book covers
      2. What you need for this book
      3. Who this book is for
      4. Conventions
      5. Reader feedback
      6. Customer support
        1. Downloading the example files
        2. Errata
        3. Piracy
        4. Questions
    9. 1. Diving Into OpenRefine
      1. Introducing OpenRefine
      2. Recipe 1 – installing OpenRefine
        1. Windows
        2. Mac
        3. Linux
      3. Recipe 2 – creating a new project
        1. File formats supported by OpenRefine
      4. Recipe 3 – exploring your data
      5. Recipe 4 – manipulating columns
        1. Collapsing and expanding columns
        2. Moving columns around
        3. Renaming and removing columns
      6. Recipe 5 – using the project history
      7. Recipe 6 – exporting a project
      8. Recipe 7 – going for more memory
        1. Windows
        2. Mac
        3. Linux
      9. Summary
    10. 2. Analyzing and Fixing Data
      1. Recipe 1 – sorting data
        1. Reordering rows
      2. Recipe 2 – faceting data
        1. Text facets
        2. Numeric facets
        3. Customized facets
        4. Faceting by star or flag
      3. Recipe 3 – detecting duplicates
      4. Recipe 4 – applying a text filter
      5. Recipe 5 – using simple cell transformations
      6. Recipe 6 – removing matching rows
      7. Summary
    11. 3. Advanced Data Operations
      1. Recipe 1 – handling multi-valued cells
      2. Recipe 2 – alternating between rows and records mode
      3. Recipe 3 – clustering similar cells
      4. Recipe 4 – transforming cell values
      5. Recipe 5 – adding derived columns
      6. Recipe 6 – splitting data across columns
      7. Recipe 7 – transposing rows and columns
      8. Summary
    12. 4. Linking Datasets
      1. Recipe 1 – reconciling values with Freebase
      2. Recipe 2 – installing extensions
      3. Recipe 3 – adding a reconciliation service
      4. Recipe 4 – reconciling with Linked Data
      5. Recipe 5 – extracting named entities
      6. Summary
    13. A. Regular Expressions and GREL
      1. Regular expressions for text patterns
        1. Character classes
        2. Quantifiers
        3. Anchors
        4. Choices
        5. Groups
      2. Overview
      3. General Refine Expression Language (GREL)
        1. Transforming data
        2. Creating custom facets
        3. Solving problems with GREL
    14. Index