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.
The DATA step remains a popular way to create and manipulate SAS data sets. Whether you are reshaping a data set entirely or simply assigning values to a new variable, there are numerous tips and tricks that you can use to save time and keystrokes.
Grace Whiteis of SAS Technical Support shows you how to capitalize on arrays using SAS software -- and streamline your code, whether it involves arrays or not.
Generating a word cloud (also known as a tag cloud) is a good way to mine internet text. Word (or tag) clouds visually represent the occurrence of keywords found in internet data such as Twitter feeds.
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
A few examples to demonstrate some of the common output-related problems with ODS Graphics Procedures. If your graphical output does not appear as you wanted, consider the options that you are using and make sure that you are using the correct option.
The RANK procedure (PROC RANK) is useful for ranking numeric variables in a data set across observations. You often see PROC RANK used to rank data into quartiles, deciles, or percentiles. This action requires that you use the GROUPS= option in the PROC RANK statement. This blog answers three questions
For every project in SAS®, the first step is almost always making your data available. This blog shows you how to load three of the most common input data types—a data set, a text file, and a Microsoft Excel file—into SAS® Cloud Analytic Services (CAS) tables. The three methods that
Did you know that you can run Lua code within Base SAS? Learn more about what PROC LUA can do through some examples.
