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- 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
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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
Ebook
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 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
- Table of Contents
- Using OpenRefine
- Credits
- Foreword
- About the Authors
- About the Reviewers
- www.PacktPub.com
- Support files, eBooks, discount offers and more
- Why Subscribe?
- Free Access for Packt account holders
- Support files, eBooks, discount offers and more
- Preface
- What this book covers
- What you need for this book
- Who this book is for
- Conventions
- Reader feedback
- Customer support
- Downloading the example files
- Errata
- Piracy
- Questions
- 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
- Recipe 1 sorting data
- 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
- Regular expressions for text patterns
- Index
- Title: 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
- Author: Ruben Verborgh, Max De Wilde
- Original title: 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.
- ISBN: 9781783289097, 9781783289097
- Date of issue: 2013-09-10
- Format: Ebook
- Item ID: e_3ax8
- Publisher: Packt Publishing