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SAS for R Users
BRIDGES THE GAP BETWEEN SAS AND R, ALLOWING USERS TRAINED IN ONE LANGUAGE TO EASILY LEARN THE OTHER SAS and R are widely-used, very different software environments. Prized for its statistical and graphical tools, R is an open-source programming language that is popular with statisticians and data mi...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Somerset :
John Wiley & Sons, Incorporated,
2019.
|
| Temas: | |
| Acceso en línea: | Texto completo |
MARC
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| 020 | |a 9781119256427 | ||
| 020 | |a 1119256429 | ||
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| 035 | |a (OCoLC)1111974914 | ||
| 050 | 4 | |a QA76.73.S27 |b .O375 2020 | |
| 082 | 0 | 4 | |a 005.55 |2 23 |
| 049 | |a UAMI | ||
| 100 | 1 | |a Ohri, Ajay. | |
| 245 | 1 | 0 | |a SAS for R Users |
| 260 | |a Somerset : |b John Wiley & Sons, Incorporated, |c 2019. | ||
| 300 | |a 1 online resource (211 pages) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Cover; Title Page; Copyright Page; Contents; Preface; Scope; Chapter 1 About SAS and R; 1.1 About SAS; 1.1.1 Installation; 1.2 About R; 1.2.1 The R Environment; 1.2.2 Installation of R; 1.3 Notable Points in SAS and R Languages; 1.4 Some Important Functions with Comparative Comparisons Respectively; 1.5 Summary; 1.6 Quiz Questions; Quiz Answers; Chapter 2 Data Input, Import and Print; 2.1 Importing Data; 2.1.1 Packages in R; 2.2 Importing Data in SAS; 2.2.1 Data Input in SAS; 2.2.2 Using Proc Import to Import a Raw File; 2.2.3 Creating a temporary dataset from a permanent one using "set." | |
| 505 | 8 | |a 2.3 Importing Data in R2.3.1 Importing from Comma Separated Value (CSV) Files; 2.3.2 Importing from Excel Files; 2.3.3 Importing from SAS; 2.3.4 Importing from SPSS and STATA; 2.3.5 Assigning the Values Imported to a Data Object in R; 2.4 Providing Data Input; 2.4.1 Data Input in R; 2.4.1.1 Using the c() function is the simplest way to create a list in R; 2.4.1.2 Providing missing values to the vector; 2.4.1.3 To Input multiple columns of data; 2.4.1.4 Using loops to input; 2.5 Data Input in SAS; 2.6 Printing Data; 2.6.1 Print in SAS; 2.6.2 Print in R; 2.7 Summary; 2.8 Quiz Questions | |
| 505 | 8 | |a Quiz AnswersChapter 3 Data Inspection and Cleaning; 3.1 Introduction; 3.2 Data Inspection; 3.2.1 Data Inspection in SAS; 3.2.2 Data Inspection in R; 3.3 Missing Values; 3.3.1 Missing Values in SAS; 3.3.2 Missing Values in R; 3.4 Data Cleaning; 3.4.1 Data Cleaning in SAS; 3.4.2 Data Cleaning in R; 3.5 Quiz Questions; Quiz Answers; Chapter 4 Handling Dates, Strings, Numbers; 4.1 Working with Numeric Data; 4.1.1 Handling Numbers in SAS; 4.1.2 Numeric Data in R; 4.2 Working with Date Data; 4.2.1 Handling Dates in SAS; 4.2.2 Handling Dates in R; 4.3 Handling Strings Data | |
| 505 | 8 | |a 4.3.1 Handling Strings Data in SAS4.3.2 Handling Strings Data in R; 4.4 Quiz Questions; Quiz Answers; Chapter 5 Numerical Summary and Groupby Analysis; 5.1 Numerical Summary and Groupby Analysis; 5.2 Numerical Summary and Groupby Analysis in SAS; 5.3 Numerical Summary and Group by Analysis in R; 5.3.1 Hmisc and Data. Table Packages; 5.3.2 Dplyr Package; 5.4 Quiz Questions; Quiz Answers; Chapter 6 Frequency Distributions and Cross Tabulations; 6.1 Frequency Distributions in SAS; 6.2 Frequency Distributions in R; 6.2.1 Frequency Tabulations in R | |
| 505 | 8 | |a 6.2.2 Frequency Tabulations in R with Other Variables StatisticsChapter 7 Using SQL with SAS and R; 7.1 What is SQL?; 7.1.1 Basic Terminology; 7.1.2 CAP Theorem; 7.1.3 SQL in SAS and R; 7.2 SQL Select; 7.2.1 SQL WHERE; 7.2.2 SQL Order By; 7.2.3 AND, OR, NOT in SQL; 7.2.4 SQL Select Distinct; 7.2.5 SQL INSERT INTO; 7.2.6 SQL Delete; 7.2.7 SQL Aggregate Functions; 7.2.8 SQL ALIASES; 7.2.9 SQL ALTER TABLE; 7.2.10 SQL UPDATE; 7.2.11 SQL IS NULL; 7.2.12 SQL LIKE and BETWEEN; 7.2.13 SQL GROUP BY; 7.2.14 SQL HAVING; 7.2.15 SQL CREATE TABLE and SQL CONSTRAINTS; 7.2.16 SQL UNION; 7.2.17 SQL JOINS | |
| 500 | |a 7.3 Merges | ||
| 520 | |a BRIDGES THE GAP BETWEEN SAS AND R, ALLOWING USERS TRAINED IN ONE LANGUAGE TO EASILY LEARN THE OTHER SAS and R are widely-used, very different software environments. Prized for its statistical and graphical tools, R is an open-source programming language that is popular with statisticians and data miners who develop statistical software and analyze data. SAS (Statistical Analysis System) is the leading corporate software in analytics thanks to its faster data handling and smaller learning curve. SAS for R Users enables entry-level data scientists to take advantage of the best aspects of both tools by providing a cross-functional framework for users who already know R but may need to work with SAS. Those with knowledge of both R and SAS are of far greater value to employers, particularly in corporate settings. Using a clear, step-by-step approach, this book presents an analytics workflow that mirrors that of the everyday data scientist. This up-to-date guide is compatible with the latest R packages as well as SAS University Edition. Useful for anyone seeking employment in data science, this book: Instructs both practitioners and students fluent in one language seeking to learn the other Provides command-by-command translations of R to SAS and SAS to R Offers examples and applications in both R and SAS Presents step-by-step guidance on workflows, color illustrations, sample code, chapter quizzes, and more Includes sections on advanced methods and applications Designed for professionals, researchers, and students, SAS for R Users is a valuable resource for those with some knowledge of coding and basic statistics who wish to enter the realm of data science and business analytics. AJAY OHRI is the founder of analytics startup Decisionstats.com. His research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces to cloud computing, investigating climate change, and knowledge flows. He currently advises startups in analytics off shoring, analytics services, and analytics. He is the author of Python for R Users: A Data Science Approach (Wiley), R for Business Analytics, and R for Cloud Computing. | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a SAS (Computer program language) | |
| 650 | 0 | |a Statistics |x Data processing. | |
| 650 | 0 | |a R (Computer program language) | |
| 650 | 6 | |a SAS (Langage de programmation) | |
| 650 | 6 | |a Statistique |x Informatique. | |
| 650 | 6 | |a R (Langage de programmation) | |
| 650 | 7 | |a R (Computer program language) |2 fast | |
| 650 | 7 | |a SAS (Computer program language) |2 fast | |
| 650 | 7 | |a Statistics |x Data processing |2 fast | |
| 758 | |i has work: |a SAS for R users (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGmQb8TfwBbFQKCKqYVqHC |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Ohri, Ajay. |t SAS for R Users. |d Somerset : John Wiley & Sons, Incorporated, ©2019 |z 9781119256410 |
| 856 | 4 | 0 | |u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=5847433 |z Texto completo |
| 938 | |a ProQuest Ebook Central |b EBLB |n EBL5847433 | ||
| 994 | |a 92 |b IZTAP | ||