Welcome!

Java Authors: Carmen Gonzalez, Pat Romanski, Victoria Livschitz, Liz McMillan, Elizabeth White

Blog Feed Post

An Introduction to SAS for R Programmers

by Joseph Rickert Life decisions are usually much too complicated to be attributed to any single cause, but one important reason that I am here at Revolution today is that I ignored suggestions from well-meaning faculty back in graduate school to work more in SAS rather than doing everything in R. There was a heavy emphasis on SAS then: the faculty were worried about us getting jobs. This was before the rise of the data scientist and the the corporate model my professors had in mind was: PhD statisticians do statistics and everyone else writes SAS code. I would not be surprised if this is still not the prevailing model in traditional Statistics programs. My bet is there are statisticians everywhere who have yet to come to grips with the concept of a “data scientist”.  Anyway, because of the great cosmic balance, or the bad karma that comes from ignoring well-intentioned advice and the fact that there are quite a few companies out there that want to convert their SAS code to R, I occasionally get to look at SAS code. In the process of interviewing candidates for this kind of work it struck me that there are many people coming to data science through the programming or machine learning routes who have some R knowledge as well as experience with Java, Python and C++ who have never worked with SAS. To this group I offer the following very brief “Introduction to SAS for R Programmers”. So what is SAS exactly? Originally, SAS  stood for “Statistical Analysis System”. Indeed, towards the beginning of his invaluable book, “R for SAS and SPSS Users”, Bob Muenchen characterizes SAS as a system for statistical computation that has five main components: A data management system for reading, transforming and organizing data (The Data Step) A large number of procedures (PROCs) for statistical analysis and graphics The Output Delivery System for extracting output from PROCs and customizing printed output A macro language for programming in the data step and calling PROCS The Interactive Matrix programming language (IML) for developing new algorithms SAS is not a single programming language. It is an entire ecosystem of products (not all seamlessly integrated) that contains at least two languages! While becoming a competent SAS programmer clearly requires mastering an impressive number of skills, quite a bit can be accomplished in SAS with a basic knowledge of the Data Step and the more common procedures (PROCs) in the base and Stat packages. Moreover, as it turns out, these two foundational components of SAS are the very two things that an R programmer is likely to find most strange about SAS. There is really only one data structure in SAS, a file with rows of observations and columns of variables that always gets processed by means of an implied loop. A Data Step “program” starts with the first row of a SAS file executes all of the code it encounters until it comes to a run; statement then looks at the second row of the file and runs through the code again. The Data Step proceeds sequentially through the entire file in this fashion. An excellent presentation from Steven J. First illustrates the process nicely. See slides 36 through 45 for an example of SAS code with a very clear PowerPoint animation of how this all works. It is true that SAS programmers can work with arrays, but this is actually a computational sleight of hand. Arrays are actually special columns in a data set. R programmers are used to an interactive computational experience. Within a session, at any point in time the objects that resulted from a previous computation are available as inputs to the next calculation. There is always a sense of moving forward. If you didn’t compute something as part of the last function you ran, just write another function and compute it now. In SAS, however, one uses the various PROCS to conjure the results in a methodical, premeditated way. For example, something like the following code would run a simple regression in SAS sending the results to the console. proc reg data = myData;model Y = X;run:  However, if you wanted to have the fitted values and residuals available for a further computation, you would have to rerun the regression specifying an output file and the keywords for computing the fitted values and residuals. proc reg DATA = myData;MODEL Y = X / stb clb;OUTPUT OUT=OUTREG P=PREDCIT R=RESED;run; Kathy Welch a statistical consultant at the University of Michigan, provides a very clear example of this linear way of working. Most SAS programming probably gets done by writing SAS macros. Look at Bob Muenchen’s book (or this article) for practical examples of R functions to replace SAS macros. For more advanced work,the SAS/Tool Kit (yet another add on) allows SAS probrammers to write custom procedures. But, from a R programmer’s perspective probably the most exciting SAS product is the IML System which provides the ability to call R from within an IML procedure. The documentation  provides an example of transferring data stored in SAS/IML vectors to R, running a model in R and then, importing the results back into SAS/IML vectors. Actually, if you are an R programmer, all you might really want to do is import data from SAS to R. Thre are at least five ways to do this using functions from various open source R libraries. (Note that some of these methods require preparation steps to be done in SAS.) The document “An Introduction to S and The Hmisc and Design Libraries” on CRAN is also helpful. However, I recommend using rxImport feature in RevoScaleR package that ships with Revolution R Enterprise. Importing a SAS file with rxImport looks like this: rxImport(inData=data,outFile="sasFileName") Not only is it a one step process that does not require having SAS installed on your system, but it reads .sas7bdat files directly into Revolution Analytics' .xdf file format. You can easily work with SAS files that are too large to fit into memory Once in .xdf file format the data can be worked on with RevoScaleR’s parallel external memory algorithms (PEMAs) or written to .csv files or data frames.

Read the original blog entry...

More Stories By David Smith

David Smith is Vice President of Marketing and Community at Revolution Analytics. He has a long history with the R and statistics communities. After graduating with a degree in Statistics from the University of Adelaide, South Australia, he spent four years researching statistical methodology at Lancaster University in the United Kingdom, where he also developed a number of packages for the S-PLUS statistical modeling environment. He continued his association with S-PLUS at Insightful (now TIBCO Spotfire) overseeing the product management of S-PLUS and other statistical and data mining products.<

David smith is the co-author (with Bill Venables) of the popular tutorial manual, An Introduction to R, and one of the originating developers of the ESS: Emacs Speaks Statistics project. Today, he leads marketing for REvolution R, supports R communities worldwide, and is responsible for the Revolutions blog. Prior to joining Revolution Analytics, he served as vice president of product management at Zynchros, Inc. Follow him on twitter at @RevoDavid

@ThingsExpo Stories
The 3rd International Internet of @ThingsExpo, co-located with the 16th International Cloud Expo - to be held June 9-11, 2015, at the Javits Center in New York City, NY - announces that its Call for Papers is now open. The Internet of Things (IoT) is the biggest idea since the creation of the Worldwide Web more than 20 years ago.
Cultural, regulatory, environmental, political and economic (CREPE) conditions over the past decade are creating cross-industry solution spaces that require processes and technologies from both the Internet of Things (IoT), and Data Management and Analytics (DMA). These solution spaces are evolving into Sensor Analytics Ecosystems (SAE) that represent significant new opportunities for organizations of all types. Public Utilities throughout the world, providing electricity, natural gas and water, are pursuing SmartGrid initiatives that represent one of the more mature examples of SAE. We have s...
The security devil is always in the details of the attack: the ones you've endured, the ones you prepare yourself to fend off, and the ones that, you fear, will catch you completely unaware and defenseless. The Internet of Things (IoT) is nothing if not an endless proliferation of details. It's the vision of a world in which continuous Internet connectivity and addressability is embedded into a growing range of human artifacts, into the natural world, and even into our smartphones, appliances, and physical persons. In the IoT vision, every new "thing" - sensor, actuator, data source, data con...
The Internet of Things is tied together with a thin strand that is known as time. Coincidentally, at the core of nearly all data analytics is a timestamp. When working with time series data there are a few core principles that everyone should consider, especially across datasets where time is the common boundary. In his session at Internet of @ThingsExpo, Jim Scott, Director of Enterprise Strategy & Architecture at MapR Technologies, discussed single-value, geo-spatial, and log time series data. By focusing on enterprise applications and the data center, he will use OpenTSDB as an example t...
How do APIs and IoT relate? The answer is not as simple as merely adding an API on top of a dumb device, but rather about understanding the architectural patterns for implementing an IoT fabric. There are typically two or three trends: Exposing the device to a management framework Exposing that management framework to a business centric logic Exposing that business layer and data to end users. This last trend is the IoT stack, which involves a new shift in the separation of what stuff happens, where data lives and where the interface lies. For instance, it's a mix of architectural styles ...
An entirely new security model is needed for the Internet of Things, or is it? Can we save some old and tested controls for this new and different environment? In his session at @ThingsExpo, New York's at the Javits Center, Davi Ottenheimer, EMC Senior Director of Trust, reviewed hands-on lessons with IoT devices and reveal a new risk balance you might not expect. Davi Ottenheimer, EMC Senior Director of Trust, has more than nineteen years' experience managing global security operations and assessments, including a decade of leading incident response and digital forensics. He is co-author of t...
The Internet of Things will greatly expand the opportunities for data collection and new business models driven off of that data. In her session at @ThingsExpo, Esmeralda Swartz, CMO of MetraTech, discussed how for this to be effective you not only need to have infrastructure and operational models capable of utilizing this new phenomenon, but increasingly service providers will need to convince a skeptical public to participate. Get ready to show them the money!
The Internet of Things will put IT to its ultimate test by creating infinite new opportunities to digitize products and services, generate and analyze new data to improve customer satisfaction, and discover new ways to gain a competitive advantage across nearly every industry. In order to help corporate business units to capitalize on the rapidly evolving IoT opportunities, IT must stand up to a new set of challenges. In his session at @ThingsExpo, Jeff Kaplan, Managing Director of THINKstrategies, will examine why IT must finally fulfill its role in support of its SBUs or face a new round of...
One of the biggest challenges when developing connected devices is identifying user value and delivering it through successful user experiences. In his session at Internet of @ThingsExpo, Mike Kuniavsky, Principal Scientist, Innovation Services at PARC, described an IoT-specific approach to user experience design that combines approaches from interaction design, industrial design and service design to create experiences that go beyond simple connected gadgets to create lasting, multi-device experiences grounded in people's real needs and desires.
Enthusiasm for the Internet of Things has reached an all-time high. In 2013 alone, venture capitalists spent more than $1 billion dollars investing in the IoT space. With "smart" appliances and devices, IoT covers wearable smart devices, cloud services to hardware companies. Nest, a Google company, detects temperatures inside homes and automatically adjusts it by tracking its user's habit. These technologies are quickly developing and with it come challenges such as bridging infrastructure gaps, abiding by privacy concerns and making the concept a reality. These challenges can't be addressed w...
The Domain Name Service (DNS) is one of the most important components in networking infrastructure, enabling users and services to access applications by translating URLs (names) into IP addresses (numbers). Because every icon and URL and all embedded content on a website requires a DNS lookup loading complex sites necessitates hundreds of DNS queries. In addition, as more internet-enabled ‘Things' get connected, people will rely on DNS to name and find their fridges, toasters and toilets. According to a recent IDG Research Services Survey this rate of traffic will only grow. What's driving t...
Scott Jenson leads a project called The Physical Web within the Chrome team at Google. Project members are working to take the scalability and openness of the web and use it to talk to the exponentially exploding range of smart devices. Nearly every company today working on the IoT comes up with the same basic solution: use my server and you'll be fine. But if we really believe there will be trillions of these devices, that just can't scale. We need a system that is open a scalable and by using the URL as a basic building block, we open this up and get the same resilience that the web enjoys.
Connected devices and the Internet of Things are getting significant momentum in 2014. In his session at Internet of @ThingsExpo, Jim Hunter, Chief Scientist & Technology Evangelist at Greenwave Systems, examined three key elements that together will drive mass adoption of the IoT before the end of 2015. The first element is the recent advent of robust open source protocols (like AllJoyn and WebRTC) that facilitate M2M communication. The second is broad availability of flexible, cost-effective storage designed to handle the massive surge in back-end data in a world where timely analytics is e...
We are reaching the end of the beginning with WebRTC, and real systems using this technology have begun to appear. One challenge that faces every WebRTC deployment (in some form or another) is identity management. For example, if you have an existing service – possibly built on a variety of different PaaS/SaaS offerings – and you want to add real-time communications you are faced with a challenge relating to user management, authentication, authorization, and validation. Service providers will want to use their existing identities, but these will have credentials already that are (hopefully) i...
"Matrix is an ambitious open standard and implementation that's set up to break down the fragmentation problems that exist in IP messaging and VoIP communication," explained John Woolf, Technical Evangelist at Matrix, in this SYS-CON.tv interview at @ThingsExpo, held Nov 4–6, 2014, at the Santa Clara Convention Center in Santa Clara, CA.
P2P RTC will impact the landscape of communications, shifting from traditional telephony style communications models to OTT (Over-The-Top) cloud assisted & PaaS (Platform as a Service) communication services. The P2P shift will impact many areas of our lives, from mobile communication, human interactive web services, RTC and telephony infrastructure, user federation, security and privacy implications, business costs, and scalability. In his session at @ThingsExpo, Robin Raymond, Chief Architect at Hookflash, will walk through the shifting landscape of traditional telephone and voice services ...
Explosive growth in connected devices. Enormous amounts of data for collection and analysis. Critical use of data for split-second decision making and actionable information. All three are factors in making the Internet of Things a reality. Yet, any one factor would have an IT organization pondering its infrastructure strategy. How should your organization enhance its IT framework to enable an Internet of Things implementation? In his session at Internet of @ThingsExpo, James Kirkland, Chief Architect for the Internet of Things and Intelligent Systems at Red Hat, described how to revolutioniz...
Bit6 today issued a challenge to the technology community implementing Web Real Time Communication (WebRTC). To leap beyond WebRTC’s significant limitations and fully leverage its underlying value to accelerate innovation, application developers need to consider the entire communications ecosystem.
The definition of IoT is not new, in fact it’s been around for over a decade. What has changed is the public's awareness that the technology we use on a daily basis has caught up on the vision of an always on, always connected world. If you look into the details of what comprises the IoT, you’ll see that it includes everything from cloud computing, Big Data analytics, “Things,” Web communication, applications, network, storage, etc. It is essentially including everything connected online from hardware to software, or as we like to say, it’s an Internet of many different things. The difference ...
Cloud Expo 2014 TV commercials will feature @ThingsExpo, which was launched in June, 2014 at New York City's Javits Center as the largest 'Internet of Things' event in the world.