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Python for SAS Users
A SAS-Oriented Introduction to Python
Taschenbuch von Sarah Chen (u. a.)
Sprache: Englisch

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Beschreibung
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 to the 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 Yoüll 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

Who This Book Is For

SAS users, SAS programmers, data scientists, data scientist leaders, and Python users who need to work with SAS
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 to the 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 Yoüll 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

Who This Book Is For

SAS users, SAS programmers, data scientists, data scientist leaders, and Python users who need to work with SAS
Über den Autor

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.

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. 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.

Zusammenfassung

Provides working code examples and detailed explanations

Helps SAS users easily upgrade and expand their existing skills

Uses real-world examples and common problems faced with data management and analysis tasks

Identifies areas where Python and SAS diverge, and illustrates options to converge them

Inhaltsverzeichnis

Chapter 1: Why Python.- Chapter 2: Python Types and Formatting.- Chapter 3: pandas Library.- Chapter 4: Indexing and GroupBy.- Chapter 5: Data Management.- Chapter 6: pandas Readers and Writers.- Chapter 7: Date and Time.- Chapter 8: saspy Module.- Appendix A: Generating the Tickets DataFrame.- Appendix B: Many-to-Many Use Case.-

Details
Erscheinungsjahr: 2019
Fachbereich: Programmiersprachen
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xvii
434 S.
119 s/w Illustr.
434 p. 119 illus.
ISBN-13: 9781484250006
ISBN-10: 1484250001
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Chen, Sarah
Betancourt, Randy
Auflage: 1st ed.
Hersteller: Apress
Apress L.P.
Maße: 254 x 178 x 25 mm
Von/Mit: Sarah Chen (u. a.)
Erscheinungsdatum: 06.09.2019
Gewicht: 0,844 kg
Artikel-ID: 116550847
Über den Autor

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.

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. 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.

Zusammenfassung

Provides working code examples and detailed explanations

Helps SAS users easily upgrade and expand their existing skills

Uses real-world examples and common problems faced with data management and analysis tasks

Identifies areas where Python and SAS diverge, and illustrates options to converge them

Inhaltsverzeichnis

Chapter 1: Why Python.- Chapter 2: Python Types and Formatting.- Chapter 3: pandas Library.- Chapter 4: Indexing and GroupBy.- Chapter 5: Data Management.- Chapter 6: pandas Readers and Writers.- Chapter 7: Date and Time.- Chapter 8: saspy Module.- Appendix A: Generating the Tickets DataFrame.- Appendix B: Many-to-Many Use Case.-

Details
Erscheinungsjahr: 2019
Fachbereich: Programmiersprachen
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xvii
434 S.
119 s/w Illustr.
434 p. 119 illus.
ISBN-13: 9781484250006
ISBN-10: 1484250001
Sprache: Englisch
Ausstattung / Beilage: Paperback
Einband: Kartoniert / Broschiert
Autor: Chen, Sarah
Betancourt, Randy
Auflage: 1st ed.
Hersteller: Apress
Apress L.P.
Maße: 254 x 178 x 25 mm
Von/Mit: Sarah Chen (u. a.)
Erscheinungsdatum: 06.09.2019
Gewicht: 0,844 kg
Artikel-ID: 116550847
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