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210503 ||| eng |
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|a 9781484268766
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| 100 |
1 |
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|a Yarberry, William
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| 245 |
0 |
0 |
|a CRAN Recipes
|h Elektronische Ressource
|b DPLYR, Stringr, Lubridate, and RegEx in R
|c by William Yarberry
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| 250 |
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|a 1st ed. 2021
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| 260 |
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|a Berkeley, CA
|b Apress
|c 2021, 2021
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| 300 |
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|a XXI, 344 p. 53 illus., 35 illus. in color
|b online resource
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| 505 |
0 |
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|a 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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| 653 |
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|a Data Analysis and Big Data
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| 653 |
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|a Methodology of Data Collection and Processing
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| 653 |
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|a Computer science
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| 653 |
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|a Sampling (Statistics)
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| 653 |
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|a Computer Science
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| 653 |
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|a Programming languages (Electronic computers)
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| 653 |
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|a Quantitative research
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| 653 |
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|a Mathematical statistics / Data processing
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| 653 |
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|a Statistics and Computing
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| 653 |
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|a Programming Language
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 028 |
5 |
0 |
|a 10.1007/978-1-4842-6876-6
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-1-4842-6876-6?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 005.13
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| 520 |
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|a 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
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