Chapter 1 Data Visualization with ggplot2
Chapter 2 Workflow: Basics
Chapter 3 Data Transformation with dplyr
Chapter 4 Workflow: Scripts
Chapter 5 Exploratory Data Analysis
Chapter 6 Workflow: Projects
Chapter 7 Tibbles with tibble
Chapter 8 Data Import with readr
Chapter 9 Tidy Data with tidyr
Chapter 10 Relational Data with dplyr
Chapter 11 Strings with stringr
Chapter 12 Factors with forcats
Chapter 13 Dates and Times with lubridate
Chapter 14 Pipes with magrittr
Chapter 15 Functions
Chapter 16 Vectors
Chapter 17 Iteration with purrr
Chapter 18 Model Basics with modelr
Chapter 19 Model Building
Chapter 20 Many Models with purrr and broom
Chapter 21 R Markdown
Chapter 22 Graphics for Communication with ggplot2
Chapter 23 R Markdown Formats
Chapter 24 R Markdown Workflow
· · · · · · (收起)
Chapter 2 Workflow: Basics
Chapter 3 Data Transformation with dplyr
Chapter 4 Workflow: Scripts
Chapter 5 Exploratory Data Analysis
Chapter 6 Workflow: Projects
Chapter 7 Tibbles with tibble
Chapter 8 Data Import with readr
Chapter 9 Tidy Data with tidyr
Chapter 10 Relational Data with dplyr
Chapter 11 Strings with stringr
Chapter 12 Factors with forcats
Chapter 13 Dates and Times with lubridate
Chapter 14 Pipes with magrittr
Chapter 15 Functions
Chapter 16 Vectors
Chapter 17 Iteration with purrr
Chapter 18 Model Basics with modelr
Chapter 19 Model Building
Chapter 20 Many Models with purrr and broom
Chapter 21 R Markdown
Chapter 22 Graphics for Communication with ggplot2
Chapter 23 R Markdown Formats
Chapter 24 R Markdown Workflow
· · · · · · (收起)
具體描述
http://r4ds.had.co.nz/
用戶評價
評分
##手頭常備。
評分##基本上是hadley在安利他的各種包tidyr, dplyr, purrr, ggplot2，hadley的東西有更高的抽象，用起來還是比較舒服的。隻不過base包的東西已經很熟，錶示老狗學新把戲的意願不是很高。本書在手機上看完，囧rz..
評分##大概因為有點pandas和sklearn的基礎，一刷非常順暢~暑假跟著R for finance類的教材初學R真是不堪迴首=。= #選對入門書太重要!
評分##大牛的作品，果然不一般，清楚簡明易懂。
評分##入門書籍，tidyverse占瞭大頭，基本上也是很主流的包比如ggplot2還有tibble這種，重點是第四部分的函數建模部分，主要是瞭解lm（x~y）的寫法。至於第五章講交互的意義就真的很迷瞭，真的不是拿來湊數的？
評分##大概因為有點pandas和sklearn的基礎，一刷非常順暢~暑假跟著R for finance類的教材初學R真是不堪迴首=。= #選對入門書太重要!
評分##贊美Hadley!!
評分##Hadley Wickham的數據哲學
評分##tidyverse太美啦！
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