It takes the average reader and 39 minutes to read Data Mashups in R by Jeremy Leipzig
Assuming a reading speed of 250 words per minute. Learn more
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
Data Mashups in R by Jeremy Leipzig is 38 pages long, and a total of 9,804 words.
This makes it 13% the length of the average book. It also has 12% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes and 53 minutes to read Data Mashups in R aloud.
Data Mashups in R is suitable for students ages 8 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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