This blog demonstrates how to create a report that provides only the column headings for data that is missing. The blog also explains how to create, select, and exclude output objects as well as how to generate reports with the SAS® Output Delivery System (ODS). These concepts are relevant to the task of generating a report with the column headings for a data set that contains no (0) observations.
Tag: data sets
Last time we discussed the fundamentals of SAS data and how we reference that data in SAS Foundation. Now, we will turn our attention to how you access and protect data when you want to expose data through SAS clients versus the traditional LIBNAME method.
Sometimes I need to "disassemble" a SAS data set into a DATA step program. It's kind of like creating a "freeze-dried" version of the data that you can carry around and use anywhere, re-hydrating it in the SAS session where you next need it. Some example uses for this: Build
The project that I'm currently working on requires several input data tables, and those tables must have a specific schema. That is, each input table must contain columns of a specific name, type, and length in order for the rest of the system to function correctly. The schema requirements aren't
In a previous post I showed how you can use Windows PowerShell (with the SAS Local Data Provider) to create a SAS data set viewer. This approach doesn't require that you have SAS installed, and allows you to read or export the records within a SAS data set file. In
In about 30 lines of PowerShell script, we can build a SAS data set viewer that: Does not require SAS on the PC Provides very basic filtering capability Also allows for easy export to CSV All you need is the ability to run PowerShell scripts, and the SAS Local Data
I used to get an email with a joke in it every Friday from my former boss, he called it Friday's Funnies. Some were really funny. Some - not so much. Well, I've decided to start my own Friday treat - a new series - called Friday's Innovation Inspiration. I'll be using
Kathleen Harkins, Carolyn Maass and Mary Anne Rutkowski, from Merck Sharp and Dohme, collaborated to write T.I.P.S: Techniques and information for programming in SAS® for NESUG 2011. These three women are highly experienced programmers: Harkins has more than 20 years of experience in the pharmaceutical and aerospace industries; Maass has
Are you afraid of big commitments? Do you like to shop around thoroughly before making a purchase decision? I can't help you with most of Life's Big Choices, but I can help you in one way: I can show you how to learn more about your data set before you