R for data science
import, tidy, transform, visualize, and model data
Wickham, Hadley
creator
author.
Grolemund, Garrett
author.
text
bibliography
cc
2016
First edition.
monographic
eng
xxiv, 492 pages : illustrations (some color) ; 23 cm.
This work introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, it is designed to get you doing data science as quickly as possible. $b Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way.You'll learn how to:Wrangle-transform your datasets into a form convenient for analysis Program-learn powerful R tools for solving data problems with greater clarity and ease Explore-examine your data, generate hypotheses, and quickly test them Model-provide a low-dimensional summary that captures true "signals" in your dataset Communicate-learn R Markdown for integrating prose, code, and results.
Part I. Explore. Data visualization with ggplot2 -- Workflow: basics -- Data transformation with dplyr -- Workflow: scripts -- Exploratory data analysis -- Workflow: projects -- Part II. Wrangle. Tibbles with tibble -- Data import with readr --Tidy data with tidyr -- Relational data with dplyr -- Strings with stringr -- Factors with forcats -- Dates and times with lubridate -- Part III. Program. Pipes with magrittr -- Functions -- Vectors -- Iteration with purrr -- Part IV. Model. Model basics with modelr -- Model building -- Many models with purrr and broom -- Part V. Communicate. R Markdown -- Graphics for communication with ggplot2 -- R Markdown formats -- R Markdown workflow.
Hadley Wickham, Garrett Grolemund.
Includes bibliographical references and index.
R (Computer program language)
Data mining
Computer programs
Information visualization
Computer programs
Big data
Databases
QA276.45.R3 W53 2016
006.312 WI.R 2016
519.2
9781491910399
2017300238
JBL
171117
20220210112739.0
20146192
eng