發表於2024-11-13
學習如何利用R語言洞察、知曉、理解原始數據。本書介紹瞭R、RStudio以及tidyverse,後者是一組相互配閤工作的R包,能夠使數據科學更快速、流暢、富有樂趣。本書旨在幫助你盡快地上手數據科學相關的工作,並不要求讀者先前具備編程經驗。
作者Hadley Wickham和Garrett Grolemund將一步步指導你對數據進行導入、提煉、探索以及建模並發布成果。除瞭處理數據所需的基本工具,你還將會對數據科學的周期擁有一個完整的、宏觀的理解。
學習如何利用R語言洞察、知曉、理解原始數據。
《數據科學:R語言實現(影印版 英文版)》介紹瞭R、RStudio以及tidyverse,後者是一組相互配閤工作的R包,能夠使數據科學快速、流暢、富有樂趣。
《數據科學:R語言實現(影印版 英文版)》旨在幫助你盡快地上手數據科學相關的工作,並不要求讀者具備編程經驗。
《數據科學:R語言實現(影印版 英文版)》Hadley Wickham和Garrett Grolernund將一步步指導你對數據進行導入、提煉、探索以及建模並發布成果。除瞭處理數據所需的基本工具,你還將會對數據科學的周期擁有一個完整的、宏觀的理解。
Hadley Wickham是RStudio的首席科學傢以及R基金會成員。他構建瞭一套使數據科學變得更加快捷、富有樂趣的工具。可以通過其個人網站瞭解更多的信息:http://hadley.nz。
Garrett Grolemund是一名統計學傢、教師以及RStudio的碩士生導師。他還是《Hands-On Programming with R 》(O'Reilly)一書的作者。Garrett的很多授課視頻可以在oreilly.com/safari上找到。
“Hadley Wickham是數據科學領域的一位傳奇人物,他創造齣瞭一套之前無人想到過的進行數據分析的全新方法。他這本和Garrett Grolemund閤著的新書用代碼展示瞭這種新奇的方法,本書可謂是數據分析方麵的聖經。” —— Roger D.Peng (約翰?霍普金斯大學布隆博格公共衛生學院生物統計學教授)
Preface
Part I. Explore
1. Data Visualization with ggplot2
Introduction
First Steps
Aesthetic Mappings
Common Problems
Facets
Geometric Objects
Statistical Transformations
Position Adjustments
Coordinate Systems
The Layered Grammar of Graphics
2. Workflow: Basics
Coding Basics
What's in a Name?
Calling Functions
3. Data Transformation with dplyr
Introduction
Filter Rows with filter()
Arrange Rows with arrange()
Select Columns with select()
Add New Variables with mutate()
Grouped Summaries with summarize()
Grouped Mutates (and Filters)
4. W0rkfl0w: Scripts
Running Code
RStudio Diagnostics
5. Exploratory Data Analysis
Introduction
Questions
Variation
Missing Values
Covariation
Patterns and Models
ggplot2 Calls
Learning More
6. Workflow: Projects
What Is Real?
Where Does Your Analysis Live?
Paths and Directories
RStudio Projects
Summary
Part II. Wrangle
7. Tibbles with tibble
Introduction
Creating Tibbles
Tibbles Versus data.frame
Interacting with Older Code
8. Data Import with readr
Introduction
Getting Started
Parsing a Vector
Parsing a File
Writing to a File
Other Types of Data
9. Tidy Data with tidyr
Introduction
Tidy Data
Spreading and Gathering
Separating and Pull
Missing Values
Case Study
Nontidy Data
10. Relational Data with dplyr
Introduction
nycflightsl3
Keys
Mutating loins
Filtering loins
loin Problems
Set Operations
11. Strings with stringr
Introduction
String Basics
Matching Patterns with Regular Expressions
Tools
Other Types of Pattern
Other Uses of Regular Expressions
stringi
12. Factors with forcats
Introduction
Creating Factors
General Social Survey
Modifying Factor Order
Modifying Factor Levels
13. Dates and Times with lubridate
Introduction
Creating Date/Times
Date-Time Components
Time Spans
Time Zones
Part III. Program
14. Pipeswith magrittr
Introduction
Piping Alternatives
When Not to Use the Pipe
Other Tools from magrittr
15. Functions
Introduction
When Should You Write a Function?
Functions Are for Humans and Computers
Conditional Execution
Function Arguments
Return Values
Environment
16. Vectors
Introduction
Vector Basics
Important Types of Atomic Vector
Using Atomic Vectors
Recursive Vectors (Lists)
Attributes
Augmented Vectors
17. Iteration with purrr
Introduction
For Loops
For Loop Variations
For Loops Versus Functionals
The Map Functions
Dealing with Failure
Mapping over Multiple Arguments
Walk
Other Patterns of For Loops
Part IV. Model
18. Model Basics with modelr
Introduction
A Simple Model
Visualizing Models
Formulas and Model Families
Missing Values
Other Model Families
19. Model Building
Introduction
Why Are Low-Quality Diamonds More Expensive?
What Affects the Number of Daily Flights?
Learning More About Models
20. Many Models with purrr and broom
Introduction
gapminder
List-Columns
Creating List-Columns
Simplifying List-Columns
Making Tidy Data with broom
Part V. Communicate
21. R Markdown
Introduction
R Markdown Basics
Text Formatting with Markdown
Code Chunks
Troubleshooting
YAML Header
Learning More
22. Graphics for Communication with ggplot2
Introduction
Label
Annotations
Scales
Zooming
Themes
Saving Your Plots
Learning More
23. R Markdown Formats
Introduction
Output Options
Documents
Notebooks
Presentations
Dashboards
Interactivity
Websites
Other Formats
Learning More
24. R Markdown Workflow
Index
數據科學:R語言實現(影印版 英文版) [R for Data Science] 下載 mobi pdf epub txt 電子書 格式 2024
數據科學:R語言實現(影印版 英文版) [R for Data Science] 下載 mobi epub pdf 電子書600-400買的很劃算啊……京東今年真的很環保,這麼多書都用袋子裝,真的不可以用紙箱嗎……二哥今天晚上不睡覺
評分本書十分適閤初學者,迅速瀏覽完即可去尋找更硬核的教程,比如隔壁《TensorFlow實戰》,顯然深入的多。
評分600-400買的很劃算啊……京東今年真的很環保,這麼多書都用袋子裝,真的不可以用紙箱嗎……二姐傢的小寶貝
評分看見很多人推薦這個,喜歡
評分影印版英文書籍 對於學習ML很有幫助
評分值得推薦的一本書,機器學習入門很有用
評分價格便宜送貨快,不錯不錯,贊一個!!!
評分書質量看著可以, 慢慢看吧
評分專業書都超級貴,燒錢。但確實用的上,不得不買。
數據科學:R語言實現(影印版 英文版) [R for Data Science] mobi epub pdf txt 電子書 格式下載 2024