03-21-2017 03:42 PM
I'm cross-posting this announcement from @FriedEgg who shared it on SAS-L. I love the SAS-L list, but I don't want them to get all of the scoop on this exciting news for Python coders who use SAS (or is it SAS programmers who use Python?). Quoting FriedEgg here:
Just wanted to share a very exciting release from SAS on Github that happened just recently. This is a fantastic expansion of functionality and a huge step forward for those interested in Open Source Integration with SAS. I, personally, am most happy to see all of the expanded connection options.
This release changes almost everything about saspy. In version 1 saspy only had a submit method to enable the sas_kernel. It now has much much more.
Here are the highlights:
- Transfer of SAS datasets and Pandas dataframes
- SAS Data object which provides methods for working with data in SAS. Here is a few of the methods (see the doc for the complete list)
- Graphics (histogram, barchart, heatmap)
- Partitioning data
- Scoring data
- Assessing models
- Filtering (where, keep, drop)
- SAS Result object to store and display ODS results from modeling and data analysis
- Support for connections to SAS Grid Manager, PC SAS, and any other SAS IOM interface (even the mainframe)
- Analytical modeling methods
- Machine Learning
- Econometric Time Series (ETS)
- Quality Control
- Documentation using Sphinx: https://sassoftware.github.io/saspy/index.htm
We'll have more documentation and articles coming on this, including plenty of content featured from SAS Global Forum in just a couple of weeks. In the meantime -- go check out the SAS Software GitHub and play with SASPy! It works with SAS 9.4 on Windows, Unix, and even the mainframe.
(Kudos to the developers from SAS: @Jared and Tom Weber. You'll see their fingerprints all over the GitHub commits.)
04-10-2017 10:34 AM