Nelson Grajales is an Associate Technical Support Engineer. He graduated from the University of Houston with a degree in Electrical Engineering, enjoys programming as a hobby, and is a machine learning enthusiast. He supports the SASPy library and PROC HTTP.
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.
Bringing the power of SAS to your Python scripts can be a game changer. An easy way to do that is by using SASPy, a Python interface to SAS allowing Python developers to use SAS® procedures within Python. However, not all SAS procedures are included in the SASPy library. So,
This article continues a series that began with Machine learning with SASPy: Exploring and preparing your data (part 1). Part 1 showed you how to explore data using SASPy with Python. Here, in part 2, you will learn how to begin to prepare your data to use it within a
SASPy is a powerful Python library that interfaces with SAS and can help with your machine-learning solutions. SASPy was created for Python programmers to leverage the power of SAS within their Python scripts. If you are not familiar with SASPy, see the following resources: Introducing SASPy: Use Python code to
