|aR for data science :|bimport, tidy, transform, visualize, and model data /|cHadley Wickham and Garrett Grolemund.
250
|a1st ed.
260
|aSebastopol, CA :|bO'Reilly Media,|c2016.
300
|axxv, 492 p. :|bill. (some col.) ;|c23 cm.
504
|aIncludes bibliographical references and index.
505
0
|aPart 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.
520
|a"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"--P. 4 of cover.
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![Data science & big data analytics : discovering, analyzing, visualizing and presenting data / EMC Education Services ; [key contributors, David Dietrich, Barry Heller, Beibei Yang].](https://hyweblib.nou.edu.tw/HyLibMain/upload/webpacpic/138307978111887613820172304040753.jpg "Data science & big data analytics : discovering, analyzing, visualizing and presenting data / EMC Education Services ; [key contributors, David Dietrich, Barry Heller, Beibei Yang].")
