Python for SAS Users: A Sas-Oriented Introduction to Python
暫譯: SAS 使用者的 Python：針對 SAS 的 Python 入門指南
Betancourt, Randy, Chen, Sarah
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相關主題
商品描述
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
Who This Book Is For
SAS users, SAS programmers, data scientists, data scientist leaders, and Python users who need to work with SAS
商品描述(中文翻譯)
商業用戶如果熟悉 Base SAS 程式設計，現在可以透過範例學習 Python。您將通過範例學習如何將 SAS 程式設計結構和編碼模式映射到其 Python 對應項。您的主要重點將放在 pandas 和與數據分析相關的數據管理問題上。
目前全球估計有超過三百萬名 SAS 用戶。隨著數據科學領域從使用 SAS 轉向開源軟體如 Python，許多用戶將感受到更新技能的需求。大多數用戶並未接受正式的計算機科學訓練，並且可能是在工作中逐步學會 SAS 程式設計的技能。
因此，目前的文檔以及大量學習 Python 的書籍和網站都是技術性質的，並不適合大多數 SAS 用戶。《Python for SAS Users》提供了目前最全面的範例集。它包含超過 200 個 Python 腳本和約 75 個與 Python 腳本相對應的 SAS 程式。前幾章更偏向於 Python，而其餘章節則展示 SAS 和相應的 Python 範例，以解決常見的數據分析任務，例如讀取多個輸入來源、缺失值檢測、插補、合併/結合數據以及生成輸出。本書是整合 SAS 和 Python 工作流程的不可或缺的指南。
您將學到什麼
- 快速掌握 Python 進行數據分析，而無需使用試錯法
- 理解 Base SAS 和 Python 之間的相似性和差異
- 更好地根據您的需求決定使用哪種語言
- 獲得快速結果
本書適合誰
SAS 用戶、SAS 程式設計師、數據科學家、數據科學領導者，以及需要與 SAS 一起工作的 Python 用戶
作者簡介
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.
作者簡介(中文翻譯)
專業生涯一直圍繞著數據分析。他的旅程始於管理一個技術支援小組，該小組支持來自美國環保署的2000多名技術研究分析師和科學家，工作地點是由聯邦政府運營的最大主機複合體之一。他後來轉到杜克大學，為行政部門工作，分析員工資源的利用和成本。在那裡，他接觸到了數據訪問的政治，因為醫學院擁有大部分數據和計算資源。
他在SAS Institute Inc.度過了大部分職業生涯，擔任多個角色，最初從事市場營銷，後來轉向現場啟用和產品管理。隨後，他發展了首席技術官辦公室顧問的角色。
Randy環遊世界，與IT和商業領袖會面，討論數據分析對推動業務的影響。他們還討論了面臨的挑戰。同時，他也與最終用戶交談，想聽取他們的觀點。這些經歷共同塑造了他對企業在分配稀缺資源以進行數據收集、分析和模型部署時所做取捨的理解。
最近，他作為獨立顧問為多家公司工作，包括國際分析學院、微軟的SQL Server團隊和埃森哲的應用智能平台。
擁有12年的銀行和保險分析經驗，包括個人汽車定價、合規性、監控、詐騙分析、銷售分析、商業信用風險建模和監管壓力測試。她是意外精算學會和精算學會的會員（FCAS, FSA），是一名精算師、數據科學家和創新者。
Sarah的職業生涯始於在Verisk Analytics的個人汽車精算部門工作五年半，為各種ISO產品建立預測模型。在Verisk，她學習並磨練了數據分析和數據管理的核心技能。當她轉到KPMG時，她的技能和領域專業知識得到了擴展，與領先的保險公司、銀行和大型在線平台合作，解決各種商業和風險管理問題。
