目錄(87章)
倒序
- coverpage
- RStudio for R Statistical Computing Cookbook
- Credits
- About the Author
- About the Reviewer
- www.PacktPub.com
- eBooks discount offers and more
- Preface
- What this book covers
- What you need for this book
- Who this book is for
- Sections
- Conventions
- Reader feedback
- Customer support
- Chapter 1. Acquiring Data for Your Project
- Introduction
- Acquiring data from the Web – web scraping tasks
- Accessing an API with R
- Getting data from Twitter with the twitteR package
- Getting data from Facebook with the Rfacebook package
- Getting data from Google Analytics
- Loading your data into R with rio packages
- Converting file formats using the rio package
- Chapter 2. Preparing for Analysis – Data Cleansing and Manipulation
- Introduction
- Getting a sense of your data structure with R
- Preparing your data for analysis with the tidyr package
- Detecting and removing missing values
- Substituting missing values using the mice package
- Detecting and removing outliers
- Performing data filtering activities
- Chapter 3. Basic Visualization Techniques
- Introduction
- Looking at your data using the plot() function
- Using pairs.panel() to look at (visualize) correlations between variables
- Adding text to a ggplot2 plot at a custom location
- Changing axes appearance to ggplot2 plot (continous axes)
- Producing a matrix of graphs with ggplot2
- Drawing a route on a map with ggmap
- Making use of the igraph package to draw a network
- Showing communities in a network with the linkcomm package
- Chapter 4. Advanced and Interactive Visualization
- Introduction
- Producing a Sankey diagram with the networkD3 package
- Creating a dynamic force network with the visNetwork package
- Building a rotating 3D graph and exporting it as a GIF
- Using the DiagrammeR package to produce a process flow diagram in RStudio
- Chapter 5. Power Programming with R
- Introduction
- Writing modular code in RStudio
- Implementing parallel computation in R
- Creating custom objects and methods in R using the S3 system
- Evaluating your code performance using the profvis package
- Comparing an alternative function's performance using the microbenchmarking package
- Using GitHub with RStudio
- Chapter 6. Domain-specific Applications
- Introduction
- Dealing with regular expressions
- Analyzing PDF reports in a folder with the tm package
- Creating word clouds with the wordcloud package
- Performing a Twitter sentiment analysis
- Detecting fraud in e-commerce orders with Benford's law
- Measuring customer retention using cohort analysis in R
- Making a recommendation engine
- Performing time series decomposition using the stl() function
- Exploring time series forecasting with forecast()
- Tracking stock movements using the quantmod package
- Optimizing portfolio composition and maximising returns with the Portfolio Analytics package
- Forecasting the stock market
- Chapter 7. Developing Static Reports
- Introduction
- Using one markup language for all types of documents – rmarkdown
- Writing and styling PDF documents with RStudio
- Writing wonderful tufte handouts with the tufte package and rmarkdown
- Sharing your code and plots with slides
- Curating a blog through RStudio
- Chapter 8. Dynamic Reporting and Web Application Development
- Introduction
- Generating dynamic parametrized reports with R Markdown
- Developing a single-file Shiny app
- Changing a Shiny app UI based on user input
- Creating an interactive report with Shiny
- Constructing RStudio add-ins
- Sharing your work on RPubs
- Deploying your app on Amazon AWS with ramazon
- Index 更新時間：2021-07-16 11:04:20
推薦閱讀
- DevOps with Kubernetes
- React Native Cookbook
- Python自動化運維快速入門
- Python從入門到精通（精粹版）
- MATLAB 2020 從入門到精通
- MySQL數據庫管理與開發實踐教程 (清華電腦學堂)
- Visual C#通用范例開發金典
- Python編程從0到1（視頻教學版）
- ASP.NET程序開發范例寶典
- C語言程序設計與應用（第2版）
- Machine Learning With Go
- Arduino Wearable Projects
- Hack與HHVM權威指南
- 視窗軟件設計和開發自動化：可視化D++語言
- Java面向對象程序設計教程
- Learning Alfresco Web Scripts
- Hadoop Blueprints
- Jenkins 2.x實踐指南
- Learning jqPlot
- Python網絡運維自動化
- Mastering MeteorJS Application Development
- RPA開發：UiPath入門與實戰
- Python程序設計基礎教程（慕課版）
- Java多線程編程核心技術
- 精通Selenium WebDriver 3.0 （第2版）
- Apache Kafka Cookbook
- Learning BeagleBone Python Programming
- Magento Extensions Development
- Java從入門到精通（實例版）（第2版）（軟件開發視頻大講堂）
- Node.js權威指南
