By Deborah Nolan, Duncan Temple Lang
Web applied sciences are more and more suitable to scientists operating with facts, for either having access to info and growing wealthy dynamic and interactive displays. The XML and JSON info codecs are generic in internet companies, common websites and JavaScript code, and visualization codecs comparable to SVG and KML for Google Earth and Google Maps. furthermore, scientists use HTTP and different community protocols to scrape info from websites, entry leisure and cleaning soap internet providers, and have interaction with NoSQL databases and textual content seek applications. This publication presents a realistic hands-on creation to those applied sciences, together with high-level features the authors have constructed for facts scientists. It describes options and ways for extracting information from HTML, XML, and JSON codecs and the way to programmatically entry info from the Web.
Along with those normal talents, the authors illustrate numerous functions which are suitable to facts scientists, reminiscent of analyzing and writing spreadsheet records either in the neighborhood and through Google medical doctors, growing interactive and dynamic visualizations, exhibiting spatial-temporal screens with Google Earth, and producing code from descriptions of knowledge buildings to learn and write data. those issues exhibit the wealthy chances and possibilities to do new issues with those sleek technologies. The e-book includes many examples and case-studies that readers can use without delay and adapt to their very own work. The authors have fascinated by the mixing of those applied sciences with the R statistical computing environment. even though, the guidelines and abilities offered listed below are extra normal, and statisticians who use different computing environments also will locate them suitable to their work.
Deborah Nolan is Professor of data at college of California, Berkeley.
Duncan Temple Lang is affiliate Professor of facts at collage of California, Davis and has been a member of either the S and R improvement teams.
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Extra resources for XML and Web Technologies for Data Sciences with R (Use R!)
Example text
The next example demonstrates this approach. 1: Wikipedia Table of Country Populations. This HTML table of country populations is one of five tables embedded in the Web page. With readHTMLTable(), the country populations can be extracted easily from the table of interest. org/wiki/Country_population was captured in September, 2011. Example 1-1 Extracting Country Populations from a Wikipedia HTML Table At its simplest, we pass readHTMLTable() either the URL or name of a local HTML file and it reads the data in the table within the document into a data frame.
There are additional rules that must be adhered to in order to be well-formed, but those found here cover the vast majority of the cases. We explain the rules for well-formed XML in more detail. • An XML document must have one root element that completely contains all other elements. The document can have special nodes such as the XML declaration, processing instructions, or comments before the root node. However, there must be exactly one regular XML element at the top-level of the document. We have seen some documents be created by concatenating different XML documents together, or writing several elements to a file.
Rather than starting from scratch to create their vocabulary for climate science modeling, NERC built on an existing grammar, Geographic Markup Language (GML), which already had many of the needed XML elements and features for CSML. This is an example of the extensibility represented by the “X” in XML. The following snippet of CSML data contains daily rainfall measurements at a specified location for each day in the month of January.