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Code debugging and program history in SAS Enterprise Guide

debugging, Git, SAS Enterprise Guide, sas global forum, sas programming No Responses »

8月 192017

SAS programmers have high expectations for their coding environment, and why shouldn't they? Companies have a huge investment in their SAS code base, and it's important to have tools that help you understand that code and track changes over time. Few things are more satisfying as a SAS program that works as designed and delivers perfect results. (Oh, hyperbole you say? I don't think so.) But when your program isn't working the way it should, there are two features that can help you get back on track: a code debugger, and program revision history. Both of these capabilities are built into SAS Enterprise Guide. Program history was added in v7.1, and the debugger was added in v7.13.

I've written about the DATA step debugger before -- both as a teaching tool and as a productivity tool. In this article, I'm sharing a demo of the debugger's features, led by SAS developer Joe Flynn. Before joining the SAS Enterprise Guide development team, Joe worked in SAS Technical Support. He's very familiar with "bugs," and reported his share of them to SAS R&D. Now -- like every programmer -- Joe makes the bugs. But of course, he fixes most of them before they ever see the light of day. How does he do that? Debugging.

This video is only about 8 minutes long, but it's packed with good information. In the debugger demo, you'll learn how you can use standard debugging methods, such as breakpoints, step over and step through, watch variables, jump to, evaluate expression, and more. There is no better way to understand exactly what is causing your DATA step to misbehave.

In the program history demo (the second part of the video), you'll learn how team members can collaborate using standard source management tools (such as Git). If you establish a good practice of storing code in a central place with solid source management techniques, SAS Enterprise Guide can help you see who changed what, and when. SAS Enterprise Guide also offers a built-in code version comparison tool, which enhances your ability to find the breaking changes. You can also use the code comparison technique on its own, outside of the program history feature.

Take a few minutes to watch the video, and then try out the features yourself. You don't need a Git installation to play with program history at the project level, though it helps when you want to extend that feature to support team collaboration.

Students and professors earn recognition for their work at SAS Global Forum

professors, sas global forum, student scholarship program, university programs No Responses »

5月 222017

Whether it is through your research, projects you tackle or by teaching, you work hard to accomplish your goals and that deserves recognition. At SAS, we support students and lecturers who want to make an impact in their careers by given them the opportunity to attend and present at an [...]

The post Students and professors earn recognition for their work at SAS Global Forum appeared first on SAS Analytics U Blog.

Finding meaning in the moment

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4月 212017

Jess Ekstrom is an inspiration. When she was a sophomore in college at NC State University, Ekstrom interned at Disney World with the Make-A-Wish Foundation. One child in particular touched her life forever. Renee had brain cancer. Her family found out right before they were headed to Disney World to [...]

The post Finding meaning in the moment appeared first on SAS Analytics U Blog.

How to control the name of Excel sheets when they are all created at once

SAS Author's Tip, sas global forum, sas press, Tips and Tricks No Responses »

4月 182017

Ok, so you know how to create multiple sheets in Excel, but can anyone tell me how to control the name of the sheets when they are all created at once? In the ODS destination for Excel, the suboption SHEET_INTERVAL is set to TABLE by default. So what does that [...]

The post How to control the name of Excel sheets when they are all created at once appeared first on SAS Learning Post.

Nurturing the #lifelearner in all of us

sas global forum, SAS R&D, Tech No Responses »

4月 182017

In addition to his day job as Chief Technology Officer at SAS, Oliver Schabenberger is a committed lifelong learner. During his opening remarks for the SAS Technology Connection at SAS Global Forum 2017, Schabenberger confessed to having a persistent nervous curiosity, and insisted that he’s “learning every day.” And, he encouraged attendees to do the same, officially proclaiming lifelong learning as a primary theme of the conference and announcing a social media campaign to explore the issue with attendees.

This theme of lifelong learning served a backdrop – figuratively at first, literally once the conference began! – when Schabenberger, R&D Vice President Oita Coleman and Senior R&D Project Manager Lisa Morton sat down earlier this year to determine the focus for the Catalyst Café at SAS Global Forum 2017.

A centerpiece of SAS Global Forum’s Quad area, the Catalyst Café is an interactive space for attendees to try out new SAS technology and provide SAS R&D with insight to help guide future software development. At its core, the Catalyst Café is an incubator for innovation, making it the perfect place to highlight the power of learning.

After consulting with SAS Social Media Manager Kirsten Hamstra and her team, Schabenberger, Coleman and Morton decided to explore the theme by asking three questions related to lifelong learning, one a day during each day of the conference. Attendees, and others following the conference via social media channels, would respond using the hashtag #lifelearner. Morton then visualized the responses on a 13-foot-long by 8-foot-high wall, appropriately titled the Social Listening Mural, for all to enjoy during the event.

Questions for a #lifelearner

The opening day of the conference brought this question:

Day two featured this question:

Finally, day three, and this question:

"Committed to lifelong learning"

Hamstra said the response from the SAS community was overwhelming, with hundreds of individuals contributing.

Morton working on the Social Listening Mural at the SAS Global Forum Catalyst Café

“It was so interesting to see what people shared as their first jobs,” said Morton. “One started out as a bus boy and ended up a CEO, another went from stocking shelves to analytical consulting, and a couple said they immediately started their analytical careers by becoming data analysts right out of school.”

The “what do you want to learn next?” question brought some interesting responses as well. While many respondents cited topics you’d expect from a technically-inclined crowd – things like SAS Viya, the Go Programming Language and SASPy – others said they wanted to learn Italian, how to design websites or teach kids how to play soccer.

Morton said the connections that were made during the process was fascinating and made the creation of the mural so simple and inspiring. “The project showed me how incredibly diverse our SAS users are and what a wide variety of backgrounds and interests they have.”

In the end, Morton said she learned one thing for sure about SAS users: “It’s clear our users are just as committed to lifelong learning as we are here at SAS!”

My guess is that wherever you’ll find Schabenberger at this moment – writing code in his office, behind a book at the campus library, or discussing AI with Dr. Goodnight – he’s nodding in agreement.

The final product

Nurturing the #lifelearner in all of us was published on SAS Users.

Introducing SASPy: Use Python code to access SAS

Open Source, python, sas global forum, Tech Talk No Responses »

4月 092017

Thanks to a new open source project from SAS, Python coders can now bring the power of SAS into their Python scripts. The project is SASPy, and it's available on the SAS Software GitHub. It works with SAS 9.4 and higher, and requires Python 3.x.

I spoke with Jared Dean about the SASPy project. Jared is a Principal Data Scientist at SAS and one of the lead developers on SASPy and a related project called Pipefitter. Here's a video of our conversation, which includes an interactive demo. Jared is obviously pretty excited about the whole thing.

Use SAS like a Python coder

SASPy brings a "Python-ic" sensibility to this approach for using SAS. That means that all of your access to SAS data and methods are surfaced using objects and syntax that are familiar to Python users. This includes the ability to exchange data via pandas, the ubiquitous Python data analysis framework. And even the native SAS objects are accessed in a very "pandas-like" way.

import saspy
import pandas as pd
sas = saspy.SASsession(cfgname='winlocal')
cars = sas.sasdata("CARS","SASHELP")
cars.describe()

The output is what you expect from pandas...but with statistics that SAS users are accustomed to. PROC MEANS anyone?

In[3]: cars.describe()
Out[3]: 
       Variable Label    N  NMiss   Median          Mean        StdDev  
0         MSRP     .   428      0  27635.0  32774.855140  19431.716674   
1      Invoice     .   428      0  25294.5  30014.700935  17642.117750   
2   EngineSize     .   428      0      3.0      3.196729      1.108595   
3    Cylinders     .   426      2      6.0      5.807512      1.558443   
4   Horsepower     .   428      0    210.0    215.885514     71.836032   
5     MPG_City     .   428      0     19.0     20.060748      5.238218   
6  MPG_Highway     .   428      0     26.0     26.843458      5.741201   
7       Weight     .   428      0   3474.5   3577.953271    758.983215   
8    Wheelbase     .   428      0    107.0    108.154206      8.311813   
9       Length     .   428      0    187.0    186.362150     14.357991   

       Min       P25      P50      P75       Max  
0  10280.0  20329.50  27635.0  39215.0  192465.0  
1   9875.0  18851.00  25294.5  35732.5  173560.0  
2      1.3      2.35      3.0      3.9       8.3  
3      3.0      4.00      6.0      6.0      12.0  
4     73.0    165.00    210.0    255.0     500.0  
5     10.0     17.00     19.0     21.5      60.0  
6     12.0     24.00     26.0     29.0      66.0  
7   1850.0   3103.00   3474.5   3978.5    7190.0  
8     89.0    103.00    107.0    112.0     144.0  
9    143.0    178.00    187.0    194.0     238.0

SASPy also provides high-level Python objects for the most popular and powerful SAS procedures. These are organized by SAS product, such as SAS/STAT, SAS/ETS and so on. To explore, issue a dir() command on your SAS session object. In this example, I've created a sasstat object and I used dot<TAB> to list the available SAS analyses:

The SAS Pipefitter project extends the SASPy project by providing access to advanced analytics and machine learning algorithms. In our video interview, Jared presents a cool example of a decision tree applied to the passenger survival factors on the Titanic. It's powered by PROC HPSPLIT behind the scenes, but Python users don't need to know all of that "inside baseball."

Installing SASPy and getting started

Like most things Python, installing the SASPy package is simple. You can use the pip installation manager to fetch the latest version:

pip install saspy

However, since you need to connect to a SAS session to get to the SAS goodness, you will need some additional files to broker that connection. Most notably, you need a few Java jar files that SAS provides. You can find these in the SAS Deployment Manager folder for your SAS installation:

../deploywiz/sas.svc.connection.jar
..deploywiz/log4j.jar
../deploywiz/sas.security.sspi.jar
../deploywiz/sas.core.jar

The jar files are compatible between Windows and Unix, so if you find them in a Unix SAS install you can still copy them to your Python Windows client. You'll need to modify the sascgf.py file (installed with the SASPy package) to point to where you've stashed these. If using local SAS on Windows, you also need to make sure that the sspiauth.dll is in your Windows system PATH. The easiest method to add SASHOMESASFoundation9.4coresasexe to your system PATH variable.

All of this is documented in the "Installation and Configuration" section of the project documentation. The connectivity options support an impressively diverse set of SAS configs: Windows, Unix, SAS Grid Computing, and even SAS on the mainframe!

Download, comment, contribute

SASPy is an open source project, and all of the Python code is available for your inspection and improvement. The developers at SAS welcome you to give it a try and enter issues when you see something that needs to be improved. And if you're a hotshot Python coder, feel free to fork the project and issue a pull request with your suggested changes!

The post Introducing SASPy: Use Python code to access SAS appeared first on The SAS Dummy.

Using data for good with GatherIQ

data for good, GatherIQ, IOM, sas global forum No Responses »

4月 072017

“This conference has been one of my best because I’ve learned about GatherIQ, a social, good cause initiative that’s made me think about the bigger picture, and how I can help people who need help,” said a SAS Global Forum attendee who heard about SAS’ new data-for-good crowdsourcing app at [...]

Using data for good with GatherIQ was published on SAS Voices by Becky Graebe

Using data for good with GatherIQ

data for good, GatherIQ, IOM, sas global forum No Responses »

4月 072017

Using data for good with GatherIQ was published on SAS Voices by Becky Graebe

7 tips for becoming a data science unicorn

communication skills, data scientist, sas global forum, Tech No Responses »

4月 052017

Emma Warrillow, President of Data Insight Group, Inc., believes analysts add business value when they ask questions of the business, the data and the approach. “Don’t be an order taker,” she said.

Emma Warrillow at SAS Global Forum.

Warrillow held to her promise that attendees wouldn’t see a stitch of SAS programming code in her session Monday, April 3, at SAS Global Forum.

Not that she doesn’t believe programming skills and SAS Certifications aren’t important. She does.

Why you need communication skills

But Warrillow believes that as technology takes on more of the heavy lifting from the analysis side, communication skills, interpretation skills and storytelling skills are quickly becoming the data analyst’s magic wand.

Warrillow likened it to the centuries-old question: If a tree falls in a forest, and no one is around to hear it, did it make a sound? “If you have a great analysis, but no one gets it or takes action, was it really a great analysis?” she asked.

If you have a great analysis, but no one gets it or takes action, was it really a great analysis?
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To create real business value and be the unicorn – that rare breed of marketing technologist who understands both marketing and marketing technology – analysts have to understand the business and its goals and operations.

She offered several actionable tips to help make the transition, including:

1. Never just send the spreadsheet.

Or the PowerPoint or the email. “The recipient might ignore it, get frustrated or, worse yet, misinterpret it,” she said. “Instead, communicate what you’ve seen in the analysis.”

2. Be a POET.

Warrillow is a huge fan of the work of Laura Warren of Storylytics.ca. who recommends an acronym approach to data-based storytelling and making sure every presentation offers:

Purpose: The purpose of this chart is to …
Observation: To illustrate that …
Explanation: What this means to us is …
Take-away or Transition: As a next step, we recommend …

3. Brand your work.

“Many of us suffer from a lack of profile in our organizations,” she said. “Take a lesson from public relations and brand yourselves. Just make sure you’re a brand people can trust. Have checks and balances in place to make sure your data is accurate.”

4. Don’t be an order taker.

Be consultative and remember that you are the expert when it comes to knowing how to structure the campaign modeling. It can be tough in some organizations, Warrillow admitted, but asking some questions and offering suggestions can be a great way to begin.

5. Tell the truth.

“Storytelling can be associated with big, tall tales,” she said. “You have to have stories that are compelling but also have truth and resonance.” One of her best resources is The Four Truths of the Storyteller” by Peter Gruber, which first appeared in Harvard Business Review December 2007.

6. Go higher.

Knowledge and comprehension are important, “but we need to start moving further up the chain,” Warrillow said. She used Bloom’s Taxonomy to describe the importance of making data move at the speed of business – getting people to take action by moving into application, analysis, synthesis and evaluation phases.

7. Prepare for the future.

“Don’t become the person who says, ‘I’m this kind of analyst,’” she said. “We need to explore new environments, prepare ourselves with great skills. In the short term, we’re going to need more programming skills. Over time, however, we’re going to need interpretation, communication and storytelling skills.” She encouraged attendees to answer the SAS Global Forum challenge of becoming a #LifeLearner.

For more from Warrillow, read the post, Making data personal: big data made small.

7 tips for becoming a data science unicorn was published on SAS Users.

What can a BBC data journalist teach you about data visualization?

data journalism, sas global forum No Responses »

4月 052017

In an industry full of word people, it's not uncommon to hear journalists lament, “Data, what are you doing here!?” But today, data is a tool in the newsroom, and reporters need to know how to analyze and present data to readers as part of their role in communicating information to the public. Amanda [...]

What can a BBC data journalist teach you about data visualization? was published on SAS Voices by Becky Graebe