Welcome to the fourth installment in my series Getting Started with Python Integration to SAS Viya. In previous posts, I discussed how to connect to the CAS server, how to execute CAS actions, and how to work with the results. Now it's time to understand how your data is organized
Tag: Python
Are you looking for a specific CAS action to use in your project? Maybe you need to create a linear or logistic regression and can't seem to find the CAS action? In this post in the Getting Started with Python Integration to SAS® Viya® series, we are going to look
In the second post of the Getting Started with Python Integration to SAS® Viya® series we will learn about Working with CAS Actions and CASResults Objects. CAS actions are commands sent to the CAS server to run a task, and CASResults objects contain information returned from the CAS server. This
CAS Actions and Action Sets - a brief intro - A quick introduction about the distributed CAS server in SAS® Viya®. Index of articles on Getting Started with Python Integration to SAS Viya. Making a Connection - An introduction to SAS Viya and the massively parallel processing CAS engine, and
Learning never stops. When SAS had to change this year’s SAS Global Forum (SASGF) to a virtual event, everyone was disappointed. I am, however, super excited about all of the papers and stream of video releases over the last month (and I encourage you to register for the upcoming live
With increasing interest in Continuous Integration/Continuous Delivery (CI/CD), many SAS Users want to know what can be done for Visual Analytics reports. In this article, I will explain how to use Python and SAS Viya REST APIs to extract a report from a SAS Viya environment and import it into another environment.
Welcome to the first post for the Getting Started with Python Integration to SAS Viya series! With the popularity of the Python programming language for data analysis and SAS Viya's ability to integrate with Python, I thought, why not create tutorials for users integrating the two? To begin the series
Whether you like it or not, Microsoft Excel is still a big hit in the data analysis world. From small to big customers, we still see fit for daily routines such as filtering, generating plots, calculating items on ad-hoc analysis or even running statistical models. Whenever I talk to customers,
SAS' Kris Stobbe shows how you can predict survival rates of Titanic passengers with a combination of both Python and CAS using SWAT, then see how the models performed.
Parts 1 and 2 of this blog post discussed exploring and preparing your data using SASPy. To recap, Part 1 discussed how to explore data using the SASPy interface with Python. Part 2 continued with an explanation of how to prepare your data to use it with a machine-learning model.