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Python for SAS Users = A SAS-Oriented Introduction to Python /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Python for SAS Users/ by Randy Betancourt, Sarah Chen.
其他題名:	A SAS-Oriented Introduction to Python /
作者:	Betancourt, Randy.
其他作者:	Chen, Sarah.
面頁冊數:	XVII, 434 p. 119 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Python (Computer program language). -
電子資源:	https://doi.org/10.1007/978-1-4842-5001-3
ISBN:	9781484250013

Python for SAS Users = A SAS-Oriented Introduction to Python /
Betancourt, Randy.

Python for SAS UsersA SAS-Oriented Introduction to Python /[electronic resource] :by Randy Betancourt, Sarah Chen. - 1st ed. 2019. - XVII, 434 p. 119 illus.online resource.

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 -- .

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 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.

ISBN: 9781484250013

Standard No.: 10.1007/978-1-4842-5001-3doiSubjects--Topical Terms:

1127623
Python (Computer program language).

LC Class. No.: QA76.73.P98

Dewey Class. No.: 005.133

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