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Autor(en): 
  • William Yarberry
  • Cran Recipes: Dplyr, Stringr, Lubridate, and Regex in R 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 14-24 Tagen versandfertig
    Veröffentlichung:  April 2021  
    Genre:  EDV / Informatik 
    ISBN:  9781484268759 
    EAN-Code: 
    9781484268759 
    Verlag:  Apress 
    Einband:  Kartoniert  
    Sprache:  English  
    Dimensionen:  H 254 mm / B 178 mm / D 19 mm 
    Gewicht:  635 gr 
    Seiten:  344 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    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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