Opening book details…
Can I read Data mashups in R on EtoBox?
Data mashups in R by Jeremy Leipzig and Xiao-Yi Li is a nonfiction available to read on EtoBox.
What is Data mashups in R about?
How do you use R to import, manage, visualize, and analyze real-world data? With this short, hands-on tutorial, you learn how to collect online data, massage it into a reasonable form, and work with it using R facilities to interact with web servers, parse HTML and XML, and more. Rather than use canned sample data, you'll plot and analyze current home foreclosure auctions in Philadelphia. This practical mashup exercise shows you how to access spatial data in several formats locally and over the Web to produce a map of home foreclosures. It's an excellent way to explore how the R environment works with R packages and performs statistical analysis. Parse messy data from public foreclosure auction postings Plot the data using R's PBSmapping package Import US Census data to add context to foreclosure data Use R's lattice and latticeExtra packages for data visualization Create multidimensional correlation graphs with the pairs() scatterplot matrix package
Who reads Data mashups in R?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Jeremy Leipzig and Xiao-Yi Li
- Publisher
- O'Reilly Media, Incorporated
- Published
- 2011
- Language
- EN
- ISBN
- 9781449307257
- Category
- nonfiction
- Subjects
- Science, Mathematics, Engineering
Other editions & translations
More by Jeremy Leipzig and Xiao-Yi Li
Browse all works by Jeremy Leipzig and Xiao-Yi Li
Similar books
- R for Data Science — Hadley Wickham, Garrett Grolemund, and Mine Cetinkaya-Rundel (2023)
- Mastering Data Analysis with R : Gain Sharp Insights Into Your Data and Solve Real-world Data Science Problems with R—from Data Munging to Modeling and Visualization — Gergely Daróczi (2015)
- R in Action. Data Analysis and Graphics with R — Robert I. Kabacoff (2015)
- Functional Data Structures in R : Advanced Statistical Programming in R — Thomas Mailund (2017)
- R Programming: 3 books in 1 : R Basics for Beginners + R Data Analysis and Statistics + R Data Visualization — Andy Vickler (2022)
- Data Wrangling with R (Use R!) — Bradley C. Boehmke, Ph.D. (auth.) (2016)