SAS has taken another step to embrace open source by bringing SAS and Jupyter Notebook together. SAS coding in Jupyter Notebook is available in April for SAS Linux, and in July for SAS University Edition. I'll use Jupyter notebooks to compare the output of Kaplan-Meier (KM) survival estimatation using SAS and Python.

Business never stands still, and neither does business data. Every data set is just a snapshot of a business. Each feature in data has a time frame before a snapshot date. Even within a time frame, some data still has temporal dynamics. We'll detail this point using three examples. The first is about historical prices of stock market; the third introduces a paper which shows a subtle temporal nature in beer reviews. The two are described briefly. The second is about the effect of cutoff dates on the target feature in survival analysis.