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)
具体描述
http://r4ds.had.co.nz/
用户评价
评分
##基本上是hadley在安利他的各种包tidyr, dplyr, purrr, ggplot2，hadley的东西有更高的抽象，用起来还是比较舒服的。只不过base包的东西已经很熟，表示老狗学新把戏的意愿不是很高。本书在手机上看完，囧rz..
评分##大概因为有点pandas和sklearn的基础，一刷非常顺畅~暑假跟着R for finance类的教材初学R真是不堪回首=。= #选对入门书太重要!
评分##大概因为有点pandas和sklearn的基础，一刷非常顺畅~暑假跟着R for finance类的教材初学R真是不堪回首=。= #选对入门书太重要!
评分##R 是个丑八怪， tidyverse 给 R 整了个容
评分##大牛的作品，果然不一般，清楚简明易懂。
评分##大概因为有点pandas和sklearn的基础，一刷非常顺畅~暑假跟着R for finance类的教材初学R真是不堪回首=。= #选对入门书太重要!
评分##入门书籍，tidyverse占了大头，基本上也是很主流的包比如ggplot2还有tibble这种，重点是第四部分的函数建模部分，主要是了解lm（x~y）的写法。至于第五章讲交互的意义就真的很迷了，真的不是拿来凑数的？
评分##赞美Hadley!!
评分##Hadley Wickham的数据哲学
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