CRAN recipes : DPLYR, Stringr, Lubridate, and RegEx in R / William Yarberry.
Yarberry, William.
2021
QA276.45.R3
Available Online

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Title CRAN recipes : DPLYR, Stringr, Lubridate, and RegEx in R / William Yarberry.
Author Yarberry, William.
ISBN 9781484268766 (electronic bk.)
1484268768 (electronic bk.)
9781484268759 (print)
148426875X
DOI https://doi.org/10.1007/978-1-4842-6876-6
Publication Details Berkeley, CA : Apress, 2021.
Language English
Description 1 online resource (348 pages)
Item Number 10.1007/978-1-4842-6876-6 doi
Call Number QA276.45.R3
Dewey Decimal Classification 519.502855133
Summary 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 eliminates the need to know functions/packages in advance. You will: 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
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed May 4, 2021).
Available in Other Form CRAN Recipes.
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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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