Python
www.python.org/
Anaconda – Data Science Python Distribution by Continuum Analytics www.continuum.io/
Pandas – Python Data Analysis Library pandas.pydata.org/
Jupyter – Scientific notebook application jupyter.org/
Example Code and Data
You can access the example code and data for this book by linking to its author page at https://support.sas.com/authors or on GitHub at: https://github.com/sassoftware/sas-viya-the-python-perspective.
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About These Authors
Kevin D. Smith has been a software developer at SAS since 1997. He has been involved in the development of PROC TEMPLATE and other underlying ODS technologies for most of his tenure. He has spoken at numerous SAS Global Forum conferences, as well as at regional and local SAS users groups with the “From Scratch” series of presentations that were created to help users of any level master various ODS technologies. More recently, he has been involved in the creation of the scripting language interfaces to SAS Cloud Analytic Services on the SAS Viya platform.
Xiangxiang Meng, PhD, is a Senior Product Manager at SAS. The current focus of his work is on SAS® Visual Statistics, cognitive computing, the Python interface to SAS Cloud Analytic Services, and other new product initiatives. Previously, Xiangxiang worked on SAS® LASR™ Analytic Server, SAS® In-Memory Statistics for Hadoop, SAS Recommendation Systems, and SAS® Enterprise Miner™. His research interests include decision trees and tree ensemble models, automated and cognitive pipelines for business intelligence and machine learning, and parallelization of machine learning algorithms on distributed data. Xiangxiang received his PhD and MS from the University of Cincinnati.
Learn more about these authors by visiting their author pages, where you can download free book excerpts, access example code and data, read the latest reviews, get updates, and more:
http://support.sas.com/smithk http://support.sas.com/meng
Chapter 1: Installing Python, SAS SWAT, and CAS
There are three primary pieces of software that must be installed in order to use SAS Cloud Analytic Services (CAS) from Python:
● Python 2.7 if you use Python 2, or a minimum of Python 3.4 if you use Python 3
● the SAS SWAT Python package
● the CAS server
We cover the recommended ways to install each piece of software in this chapter.
Installing Python
The Python packages that are used to connect to CAS have a minimum requirement of Python 2.7. If you are using version 3 of Python, you need a minimum of Python 3.4. There are some significant differences between Python 2 and Python 3, which are only touched on in this book. We recommend that you conduct your own research about the two primary versions of Python and choose the version that is appropriate for your needs. If you are not familiar with Python or if you don’t have a version preference, we recommend that you use the most recent release of Python 3. If you have an installation of Python 2 that you are using for existing work, then you can continue to use it. The Python package that is used to connect to CAS is compatible with both Python 2 and Python 3.
If you plan to use Microsoft Windows as your client operating system, you might not have an existing Python installation. If you use the Linux operating system or the Macintosh operating system, you probably have a Python installation already. In either case, you might need to install some prerequisite packages. We recommend that you start with a Python distribution such as Anaconda from Continuum Analytics at www.continuum.io which contains all of the prerequisites.
The Anaconda Python distribution includes dozens of the most popular Python packages, which can be installed easily on Windows, Linux, and Macintosh platforms. It also enables you to install a complete Python installation at any location on your system, including your home directory, so that you don’t need administrator privileges. Even if you do have administrator privileges and you have an existing Python installation on the Linux or Macintosh platforms, installing Anaconda as a separate Python is a good idea in order to prevent any mishaps that might occur while installing packages in the existing Python installation.
After you have installed Python, the next step is to install the SWAT package.
Installing SAS SWAT
The SAS SWAT package is the Python package created by SAS which is used to
