SAS Viya. Kevin D. Smith

Regression Trees

       Conclusion

       Chapter 9: Modeling Categorical Variables

       Logistic Regression

       Decision Trees

       Gradient Boosting, Forests, and Neural Networks

       Conclusion

       Chapter 10: Advanced Topics

       Binary vs. REST Interfaces

       The Binary Interface

       The REST Interface

       The Pros and Cons of Each Interface

       Result Processing Workflows

       The Easy Way

       Using Response and Result Callback Functions

       Handling Responses from Multiple Sessions Simultaneously

       Connecting to Existing Sessions

       Communicating Securely

       Conclusion

       Appendix A: A Crash Course in Python

       IPython and Jupyter

       Data Types and Collections

       Numeric Data Types

       Character Data Types

       Booleans

       Lists and Tuples

       Other Types

       Flow Control

       Conditional Code

       Looping

       Functions

       Classes and Objects

       Exceptions

       Context Managers

       Using the Pandas Package

       Data Structures

       Data Selection

       Creating Plots and Charts

       Plotting from Pandas DataFrame Methods

       Plotting DataFrames with Plotly and Cufflinks

       Creating Graphics with Matplotlib

       Interactive Visualization with Bokeh

       Conclusion

       Appendix B: Troubleshooting

       Software Version Issues

       Connection Issues

       Missing Linux Library Dependencies

       Incorrect SAS Threaded Kernel Configuration

       Unable to Import _pyXXswat

       Refused Connection

       Authentication Problems

       Index

      Foreword

      SAS^® Viya^® marks a new and important chapter in our ever-evolving SAS software. A unified, open, powerful, and cloud-ready platform built on excellence in data management, advanced analytics, and high-performance computing.

      These pillars of SAS Viya are important individually, but it is through their combination that the platform comes to life. The ability to access a central data management and computing environment through public APIs and from multiple programming languages, with consistent security and data models is a core competency of the modern analytic platform.

      The Python language has quickly grown into one of the important programming languages for data science and analytics. As the SAS R&D team embarked on building SAS Cloud Analytic Services (CAS), the engine of the SAS Viya platform, it was obvious that access from Python would be important.

      The Python client for SAS Viya was developed by Kevin Smith as a member of the core team that designed and developed SAS Cloud Analytic Services. This book by Kevin and Xiangxiang Meng takes you on a journey to learn and apply Python programming in the context of the SAS Viya platform. Their deep understanding of the SAS Viya server architecture, the client architecture, and the Python language implementation shines through in every chapter.

      As a lifelong learner, I greatly enjoyed the journey and am sure that you will, too.

      Oliver Schabenberger, PhD Executive Vice President, Chief Operating Officer and Chief Technology Officer SAS

      About This Book

      What Does This Book Cover?

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