Business users familiar with Base SAS programming can learn Python through practical examples that translate SAS coding constructs into their Python equivalents. The focus is primarily on pandas and data management for data analysis. With over three million SAS users globally, many are transitioning to open-source software like Python and need to update their skills. Most SAS users lack formal computer science training and have learned through on-the-job experience, making traditional Python resources often too technical for their needs. This guide offers a comprehensive collection of over 200 Python scripts alongside approximately 75 corresponding SAS programs, making it a valuable resource. The initial chapters emphasize Python, while later sections provide SAS examples that align with Python scripts to tackle common data analysis tasks, such as reading multiple data sources, detecting and imputing missing values, merging data, and generating outputs. This book serves as an essential resource for integrating SAS and Python workflows, enabling users to quickly master Python for data analysis, understand the nuances between Base SAS and Python, and choose the appropriate language for their specific needs. It is ideal for SAS users, programmers, data scientists, and those needing to bridge the gap between SAS and Python.
Randy Betancourt Bücher
