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Want to use the power of R sooner rather than later? Don’t have time to plow through wordy texts and online manuals? Use this book for quick, simple code to get your projects up and running. It includes code and examples applicable to many disciplines. Written in everyday language with a minimum of complexity, each chapter provides the building blocks you need to fit R’s astounding capabilities to your analytics, reporting, and visualization needs. CRAN Recipes recognizes how needless jargon and complexity get in your way. Busy professionals need simple examples and intuitive descriptions;…mehr
Want to use the power of R sooner rather than later? Don’t have time to plow through wordy texts and online manuals? Use this book for quick, simple code to get your projects up and running. It includes code and examples applicable to many disciplines. Written in everyday language with a minimum of complexity, each chapter provides the building blocks you need to fit R’s astounding capabilities to your analytics, reporting, and visualization needs.
CRAN Recipes recognizes how needless jargon and complexity get in your way. Busy professionals need simple examples and intuitive descriptions; side trips and meandering philosophical discussions are left for other books.
Here R scripts are condensed, to the extent possible, to copy-paste-run format. Chapters and examples are structured to purpose rather than particular functions (e.g., “dirty data cleanup” rather than the R package name “janitor”). Everyday language eliminatesthe need to know functions/packages in advance.
What You Will Learn
Carry out input/output; visualizations; data munging; manipulations at the group level; and quick data exploration
Handle forecasting (multivariate, time series, logistic regression, Facebook’s Prophet, and others)
Use text analytics; sampling; financial analysis; and advanced pattern matching (regex)
Manipulate data using DPLYR: filter, sort, summarize, add new fields to datasets, and apply powerful IF functions
Create combinations or subsets of files using joins
Write efficient code using pipes to eliminate intermediate steps (MAGRITTR)
Work with string/character manipulation of all types (STRINGR)
Discover counts, patterns, and how to locate whole words
Do wild-card matching, extraction, and invert-match
Work with dates using LUBRIDATE
Fix dirty data; attractive formatting; bad habits to avoid
Who This Book Is For
Programmers/data scientists with at least some prior exposure to R.
William A. Yarberry, Jr., CPA, CISA, is principal consultant, ICCM Consulting LLC, based in Houston, Texas. His practice is focused on IT governance, Sarbanes-Oxley compliance, security consulting, and business analytics for cost management. He was previously a senior manager with PricewaterhouseCoopers, responsible for telecom and network services in the Southwest region. Yarberry has more than 30 years’ experience in a variety of IT-related services, including application development, internal audit management, outsourcing administration, and Sarbanes-Oxley consulting.
His books include The Effective CIO (co-authored), Computer Telephony Integration, $250K Consulting, DPLYR, 50,000 Random Numbers, Telecommunications Cost Management, and GDPR: A Short Primer. In addition, he has written over 20 professional articles on topics ranging from wireless security to change management. One of his articles, "Audit Rights in anOutsource Environment," received the Institute of Internal Auditors Outstanding Contributor Award.
Prior to joining PricewaterhouseCoopers, Yarberry was director of telephony services for Enron Corporation. He was responsible for operations, planning, and architectural design for voice communications servers and related systems for more than 7,000 employees. Yarberry graduated Phi Beta Kappa in chemistry from the University of Tennessee and earned an MBA at the University of Memphis. He enjoys reading history, swimming, hiking, and spending time with family.
Inhaltsangabe
1: DPLYR.- 2: STRINGR.- 3: Lubridate.- 4: Regular Expressions: Introduction.- 5: Typical Uses.- 6: Some Simple Patterns.- 7: Character Classes.- 8: Elements of Regular Expressions.- 9: The Magnificent Seven.- 10: Regular Expressions in Stringr.- 11: Unicode.- 12: Tools for Development and Resources.- 13: Regex Summary.- 14: Recipes for Common R Tasks.- 15: Data Structures.- 16: Visualization.- 17: Simple Prediction Methods.- 18: Smorgasbord of Simple Statistical Tests.- 19: Validation of Data.- 20: Shortcuts and Miscellaneous.- 21: Conclusion.- Appendix A: Suggested Websites.- Appendix B: Cheat Sheet for Regex in R.- Appendix C: General R Comments by John D. Cook, Consultant.- Appendix D: Understanding a Long Regular Expression.- Appendix E: Regular Expression-enabled Languages.- Appendix F: Sample Data Analysis Questions.- Appendix G: Formats Recognized by Lubridate.
1: DPLYR.- 2: STRINGR.- 3: Lubridate.- 4: Regular Expressions: Introduction.- 5: Typical Uses.- 6: Some Simple Patterns.- 7: Character Classes.- 8: Elements of Regular Expressions.- 9: The Magnificent Seven.- 10: Regular Expressions in Stringr.- 11: Unicode.- 12: Tools for Development and Resources.- 13: Regex Summary.- 14: Recipes for Common R Tasks.- 15: Data Structures.- 16: Visualization.- 17: Simple Prediction Methods.- 18: Smorgasbord of Simple Statistical Tests.- 19: Validation of Data.- 20: Shortcuts and Miscellaneous.- 21: Conclusion.- Appendix A: Suggested Websites.- Appendix B: Cheat Sheet for Regex in R.- Appendix C: General R Comments by John D. Cook, Consultant.- Appendix D: Understanding a Long Regular Expression.- Appendix E: Regular Expression-enabled Languages.- Appendix F: Sample Data Analysis Questions.- Appendix G: Formats Recognized by Lubridate.
1: DPLYR.- 2: STRINGR.- 3: Lubridate.- 4: Regular Expressions: Introduction.- 5: Typical Uses.- 6: Some Simple Patterns.- 7: Character Classes.- 8: Elements of Regular Expressions.- 9: The Magnificent Seven.- 10: Regular Expressions in Stringr.- 11: Unicode.- 12: Tools for Development and Resources.- 13: Regex Summary.- 14: Recipes for Common R Tasks.- 15: Data Structures.- 16: Visualization.- 17: Simple Prediction Methods.- 18: Smorgasbord of Simple Statistical Tests.- 19: Validation of Data.- 20: Shortcuts and Miscellaneous.- 21: Conclusion.- Appendix A: Suggested Websites.- Appendix B: Cheat Sheet for Regex in R.- Appendix C: General R Comments by John D. Cook, Consultant.- Appendix D: Understanding a Long Regular Expression.- Appendix E: Regular Expression-enabled Languages.- Appendix F: Sample Data Analysis Questions.- Appendix G: Formats Recognized by Lubridate.
1: DPLYR.- 2: STRINGR.- 3: Lubridate.- 4: Regular Expressions: Introduction.- 5: Typical Uses.- 6: Some Simple Patterns.- 7: Character Classes.- 8: Elements of Regular Expressions.- 9: The Magnificent Seven.- 10: Regular Expressions in Stringr.- 11: Unicode.- 12: Tools for Development and Resources.- 13: Regex Summary.- 14: Recipes for Common R Tasks.- 15: Data Structures.- 16: Visualization.- 17: Simple Prediction Methods.- 18: Smorgasbord of Simple Statistical Tests.- 19: Validation of Data.- 20: Shortcuts and Miscellaneous.- 21: Conclusion.- Appendix A: Suggested Websites.- Appendix B: Cheat Sheet for Regex in R.- Appendix C: General R Comments by John D. Cook, Consultant.- Appendix D: Understanding a Long Regular Expression.- Appendix E: Regular Expression-enabled Languages.- Appendix F: Sample Data Analysis Questions.- Appendix G: Formats Recognized by Lubridate.
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