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R for data science import, tidy, transform, visualize, and model data

Use R to turn data into insight, knowledge, and understanding. With this practical book, aspiring data scientists will learn how to do data science with R and RStudio, along with the tidyverse—a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if yo...

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Bibliographic Details
Main Authors: Wickham, Hadley, Çetinkaya-Rundel, Mine (Author), Grolemund, Garrett (Author)
Format: eBook
Language:English
Published: Sebastopol, CA O'Reilly Media, Inc. 2023
Edition:2nd edition
Subjects:
Data Mining / Computer Programs
R (langage De Programmation)
Big Data / Fast
Big Data / Http://id.loc.gov/authorities/subjects/sh2012003227
Information Visualization / Computer Programs
R (computer Program Language) / Fast
Visualisation De L'information / Logiciels
Données Volumineuses
Exploration De Données (informatique) / Logiciels
Information Visualization / Computer Programs / Fast
Databases / Fast
Databases / Http://id.loc.gov/authorities/subjects/sh86007767
R (computer Program Language) / Http://id.loc.gov/authorities/subjects/sh2002004407
Online Access:
Collection: O'Reilly - Collection details see MPG.ReNa
Table of Contents:
  • Includes bibliographical references and index
  • Part I. Whole game. Data visualization ; Workflow : basics ; Data transformation ; Workflow : code style ; Data tidying ; Workflow : scripts and projects ; Data import ; Workflow : getting help
  • Part II. Visualize. Layers ; Exploratory data analysis ; Communication
  • Part III. Transfer. Local vectors ; Numbers ; Strings ; Regular expressions ; Factors ; Dates and times Missing values ; Joins – Part IV. Import. Spreadsheets ; Databases ; Arrow ; Hierarchical data ; Web scraping
  • Part V. Program. Functions ; Iteration ; A field guide to Base R – Part VI. Communicate. Quarto ; Quarto formats

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