Python for SAS Users: A SAS-Oriented Introduction to Python - Tapa blanda

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Randy Betancourt’s professional career has been in and around data analysis. His journey began by managing a technical support group supporting over 2,000 technical research analysts and scientists from the US Environmental Protection Agency at one of the largest mainframe complexes run by the federal government. He moved to Duke University, working for the administration, to analyze staff resource utilization and costs. There, he was introduced to the politics of data access as the medical school had most of the data and computer resources.

He spent the majority of his career at SAS Institute Inc. in numerous roles, starting in marketing and later moving into field enablement and product management. He subsequently developed the role for Office of the CTO consultant.

More recently, he has worked as an independent consultant for firms, including the International Institute of Analytics, Microsoft's SQL Server group, and Accenture's Applied Intelligence platform.

Sarah Chen has 12 years of analytics experience in banking and insurance, including personal auto pricing, compliance, surveillance, fraud analytics, sales analytics, credit risk modeling for business, and regulatory stress testing. She is a Fellow of both the Casualty Actuarial Society and the Society of Actuaries (FCAS, FSA), an actuary, data scientist, and innovator. 

Sarah's career began with five and a half years at Verisk Analytics in the Personal Auto Actuarial division, building predictive models for various ISO products. At Verisk, she learned and honed core skills in data analysis and data management. Her skills and domain expertise were broadened when she moved to KPMG, working with leading insurers, banks, and large online platforms on diverse business and risk management problems. 

De la contraportada

Business users familiar with Base SAS programming can now learn Python by example. You will learn via examples that map SAS programming constructs and coding patterns into their Python equivalents. Your primary focus will be on pandas and data management issues related to analysis of data.

It is estimated that there are three million or more SAS users worldwide today. As the data science landscape shifts from using SAS to open source software such as Python, many users will feel the need to update their skills. Most users are not formally trained in computer science and have likely acquired their skills programming SAS as part of their job.

What You’ll Learn:

• Quickly master Python for data analysis without using a trial-and-error approach
  
• Understand the similarities and differences between Base SAS and Python
  
• Better determine which language to use, depending on your needs
  
• Obtain quick results