Python for SAS Users (PDF)
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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.
As a result, the current documentation and plethora of books and websites for learning Python are technical and not geared for most SAS users. Python for SAS Users provides the most comprehensive set of examples currently available. It contains over 200 Python scripts and approximately 75 SAS programs that are analogs tothe Python scripts. The first chapters are more Python-centric, while the remaining chapters illustrate SAS and corresponding Python examples to solve common data analysis tasks such as reading multiple input sources, missing value detection, imputation, merging/combining data, and producing output. This book is an indispensable guide for integrating SAS and Python workflows.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
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. Randy traveled the globe meeting with IT and business leaders discussing the impact of data analysis to drive their business. And they also discussed challenges they faced. At the same time, he talked to end users, wanting to hear their perspective. Together, these experiences shaped his understanding of trade-offs that businesses make allocating scarce resources to data collection, analysis, and deployment of models.
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.
- Autoren: Randy Betancourt , Sarah Chen
- 2019, 1st ed, 434 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 148425001X
- ISBN-13: 9781484250013
- Erscheinungsdatum: 06.09.2019
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Größe: 8.32 MB
- Ohne Kopierschutz
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