Book description
Access and clean up data easily using JMP®!
Data acquisition and preparation commonly consume approximately 75% of the effort and time of total data analysis. JMP provides many visual, intuitive, and even innovative data-preparation capabilities that enable you to make the most of your organization's data.
Preparing Data for Analysis with JMP® is organized within a framework of statistical investigations and model-building and illustrates the new data-handling features in JMP, such as the Query Builder. Useful to students and programmers with little or no JMP experience, or those looking to learn the new data-management features and techniques, it uses a practical approach to getting started with plenty of examples. Using step-by-step demonstrations and screenshots, this book walks you through the most commonly used data-management techniques that also include lots of tips on how to avoid common problems.
With this book, you will learn how to:
- Manage database operations using the JMP Query Builder
- Get data into JMP from other formats, such as Excel, csv, SAS, HTML, JSON, and the web
- Identify and avoid problems with the help of JMP’s visual and automated data-exploration tools
- Consolidate data from multiple sources with Query Builder for tables
- Deal with common issues and repairs that include the following tasks:
- reshaping tables (stack/unstack)
- managing missing data with techniques such as imputation and Principal Components Analysis
- cleaning and correcting dirty data
- computing new variables
- transforming variables for modelling
- reconciling time and date
- Subset and filter your data
- Save data tables for exchange with other platforms
Table of contents
- About This Book
- About The Author
- Chapter 1: Data Management in the Analytics Process
- Introduction
- A Continuous Process
- Asking Questions That Data Can Help to Answer
- Sourcing Relevant Data
- Reproducibility
- Combining and Reconciling Multiple Sources
- Identifying and Addressing Data Issues
- Data Requirements Shaped by Modeling Strategies
- Plan of the Book
- Conclusion
- References
- Chapter 2: Data Management Foundations
- Introduction
- Matching Form to Function
- JMP Data Tables
- Data Types and Modeling Types
- Basics of Relational Databases
- Conclusion
- References
- Chapter 3: Sources of Data and Their Challenges
- Introduction
- Internal Data in Flat Files
- Relational Databases
- External Data on the World Wide Web
- Ethical and Legal Considerations
- Conclusion
- References
- Chapter 4: Single Files
- Introduction
- Review of JMP File Types
- Common Formats Other than JMP
- Other Data File Formats
- Conclusion
- References
- Chapter 5: Database Queries
- Introduction
- Sample Databases in This Chapter
- Connecting to a Database
- Extracting Data from One Table in a Database
- Querying a Database from JMP
- Query Builder for SAS Server Data
- Conclusion
- References
- Chapter 6: Importing Data from Websites
- Introduction
- Variety of Web Formats
- Internet Open
- Common Issues to Anticipate
- Conclusion
- References
- Chapter 7: Reshaping a Data Table
- Introduction
- What Shape Is a Data Table?
- Reasons for Wide and Long Formats
- Stacking Wide Data
- Unstacking Narrow Data
- Additional Examples
- Reshaping the WDI Data
- Conclusion
- References
- Chapter 8: Joining, Subsetting, and Filtering
- Introduction
- Combining Data from Multiple Tables with Join
- Saving Memory with a Virtual Join
- Why and How to Select a Subset
- Row Filters: Global and Local
- Combining Rows with Concatenate
- Query Builder for Tables
- Conclusion
- References
- Chapter 9: Data Exploration: Visual and Automated Tools to Detect Problems
- Introduction
- Common Issues to Anticipate
- On the Hunt for Dirty Data
- Distribution
- Columns Viewer
- Multivariate (Correlations and Scatterplot Matrix)
- Explore Outliers
- Explore Missing
- Conclusion
- References
- Chapter 10: Missing Data Strategies
- Introduction
- Much Ado about Nothing?
- Four Basic Approaches
- Working with Complete Cases
- Analysis with Sampling Weights
- Imputation-based Methods
- Conclusion and a Note of Caution
- References
- Chapter 11: Data Preparation for Analysis
- Introduction
- Common Issues and Appropriate Strategies
- Distribution of Observations
- High Dimensionality: Abundance of Columns
- Abundance of Rows
- Date and Time-Related Issues
- Conclusion
- References
- Chapter 12: Exporting Work to Other Platforms
- Introduction
- Why Export or Exchange Data?
- Fit the Method to the Purpose
- Exporting Reports
- Conclusion
- References
- Index
Product information
- Title: Preparing Data for Analysis with JMP
- Author(s):
- Release date: May 2017
- Publisher(s): SAS Institute
- ISBN: 9781635261486
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