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CRAN - Package SortableHTMLTables
Statistics, R, Graphics and Fun | Yihui Xie
WebScraping with R

Questions containing '[r] xml xpath'
semin-r
Table of Contents This is a guide to importing and exporting data to and from R. This manual is for R, version 3.0.2 (2013-09-25). Copyright © 2000–2013 R Core Team Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. R Data Import/Export R Data Import/Export
Table of Contents This is a guide to installation and administration for R. This manual is for R, version 3.0.2 (2013-09-25). Copyright © 2001–2013 R Core Team Permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and this permission notice are preserved on all copies. Permission is granted to copy and distribute modified versions of this manual under the conditions for verbatim copying, provided that the entire resulting derived work is distributed under the terms of a permission notice identical to this one. R Installation and Administration R Installation and Administration
R_note -- The Exploration of Statistical Software R ( έp n R ` ׾ I) R_note -- The Exploration of Statistical Software R ( έp n R ` ׾ I) Section: About R_note About the readers Who are interesting in this note? Where are they from? A record from google analytics shows the possible visits.
Revolution R Enterprise: Production-Grade Analysis for Business & Large-Scale Research Revolution R Enterprise: Production-Grade Analysis for Business & Large-Scale Research Industry’s Most Capable Big Data Big Analytics Platform Revolution R Enterprise is the fastest, most cost effective enterprise-class big data big analytics platform available today. Supporting a variety of big data statistics, predictive modeling and machine learning capabilities, Revolution R Enterprise is also 100% R.
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It's crantastic!
Introduction Analyzing time series data of all sorts is a fundamental business analytics task to which the R language is beautifully suited. In addition to the time series functions built into base stats library there are dozens of R packages devoted to time series http://crantastic.org/task_views/TimeSeries. Some packages help with basic tasks such as creating date data types, others offer specialized functions for financial applications. Extracting Time Series from Large Data Sets Extracting Time Series from Large Data Sets
Skip to Content A Community Site for R – Sponsored by Revolution Analytics Home » How to » Finding Data on the Internet Finding Data on the Internet By RevoJoe Finding Data on the Internet Finding Data on the Internet
Mining Twitter for Airline Consumer Sentiment Mining Twitter for Airline Consumer Sentiment Airlines, Consumers, and Twitter Anyone who travels regularly recognizes that airlines struggle to deliver a consistent, positive customer experience. Through extensive interview and survey work, the American Customer Satisfaction Index (http://theacsi.org/) quantifies this impression. As a group, airlines falls at the bottom of their industry rankings, below the Post Office and insurance companies: Meanwhile, the immediacy and accessibility of Twitter provides a real-time glimpse into consumer's frustration: This tutorial demonstrates how to use R to collect tweets and apply a (very) naive algorithm to estimate their emotional sentiment.
Description Functions to create, open and close connections. Usage connections {base} connections {base}
Description These functions provide the base mechanisms for defining new functions in the R language. Usage function( arglist ) exprreturn(value) function {base} function {base}
Description This function creates data frames, tightly coupled collections of variables which share many of the properties of matrices and of lists, used as the fundamental data structure by most of R's modeling software. Usage data.frame {base} data.frame {base}
As an intern in an economic research team, I was given the task to find a way to automatically collect specific data on a real estate ad website, using R. I assume that the concerned packages are XML and RCurl, but my understanding of their work is very limited. Here is the main page of the website: http://www.leboncoin.fr/ventes_immobilieres/offres/nord_pas_de_calais/? xml - Web scraping with R over real estate ads
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Latest version: XML_1.6-3.tar.gz R Package Support for S4/Splus5 for the Tree Parsing Event driven parsing and function callbacks not yet added for S4/Splus5. R & SPlus XML Parsers
unnamed pearl Abstract The idea here is to provide simple examples of how to get started with processing XML in R using some reasonably straightforward "flat" XML files and not worrying about efficiency. Here is an example of a simple file in XML containing grades for students for three different tests. <?xml version="1.0" ?><TABLE><GRADES><STUDENT> Fred </STUDENT><TEST1> 66 </TEST1><TEST2> 80 </TEST2><FINAL> 70 </FINAL></GRADES><GRADES><STUDENT> Wilma </STUDENT><TEST1> 97 </TEST1><TEST2> 91 </TEST2><FINAL> 98 </FINAL></GRADES></TABLE>
A Short Introduction to the XML package for R To parse an XML document, you can use xmlInternalTreeParse() or xmlTreeParse() (with useInternalNodes specified as TRUE or FALSE) or xmlEventParse() . If you are dealing with HTML content which is frequently malformed (i.e. nodes not terminated, attributes not quoted, etc.), you can use htmlTreeParse() . You can give these functions the name of a file, a URL (HTTP or FTP) or XML text that you have previously created or read from a file. If you are working with small to moderately sized XML files, it is easiest to use xmlInternalTreeParse() to first read the XML tree into memory.
Re: [R] Need help extracting info from XML file using XML package from Duncan Temple Lang on 2009-03-03 (R help archive)
Grabbing Tables in Webpages Using the XML Package
R preferred by Kaggle competitors
CRAN: Manuals
CRAN Task View: Natural Language Processing
R-Forge: RGoogleData: Project Home
R Data Import/Export
R: Data Output
How to Learn R
R - R help | Mailing List Archive
Romain Francois, Professional R Enthusiast
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r - How to transform XML data into a data.frame
sorenmacbeth/googleanalytics4r
R] Downloading data from from internet
Tuto : Extraire des données d'une page web avec R - 3 - Données sur plusieurs pages | Le blog de François Guillem
Tuto : Extraire des données d'une page web avec R - 2 - Données structurées | Le blog de François Guillem
Tuto : Extraire des données d'une page web avec R - 1 - Les tableaux | Le blog de François Guillem
[BioC] PostForm() with KEGG
R/htmlToText/htmlToText.R at master from tonybreyal/Blog-Reference-Functions - GitHub
R bloggers
unnamed pearl
Extracting comments from a Blogger.com blog post with R
Web scraping
Syntaxe de base. / Le langage. / Aide mémoire R.
Lecture et Ecriture de fichiers. / Le langage. / Aide mémoire R.
Système et fichiers. / Le langage. / Aide mémoire R.
Chaînes de caractères. / Le langage. / Aide mémoire R.
numeric {base}
grep {base}
The R Journal >> Current Issue
CRAN Packages By Date
Executer un programme R avec PHP
Algèbre linéaire
French users of R in social sciences ()
R for Windows FAQ
Input and Output
Package ff
unnamed pearl
Automating R script with Windows 7
r_allocstringbuffer
R commands
One R Tip a Day (rlangtip) sur Twitter
Groupe des utilisateurs du logiciel R :: Index
CouchDB and R
Geting started with CouchDB
tips:programming:code_optim2 [R Wiki]
cURL - How To Use
Example .  An example of nested downloads using RCurl.
RCurl
MCMC programming in R, Python, Java and C « Darren Wilkinson's research blog
Thinking inside the box
Integrating R with C++: Rcpp, RInside, and RProtobuf
Rcpp: Seamless R and C++ Integration
how to incorporate C or C++ code into my R code to speed up a MCMC program, using a Metropolis-Hastings algorithm
Installing Rcpp on Windows 7 for R and C++ integration « Consistently Infrequent
R « Consistently Infrequent
Visualize your Facebook friends network with R
Great Maps with ggplot2
Upcoming | ACM San Francisco Bay Area Professional Chapter
Machine Learning for Hackers
Creating beautiful maps with R
snow Simplified: a user guide to the snow R package
Technical Notes on the R programming language
Welcome to a Little Book of R for Time Series! — Time Series 0.1 documentation
Introduction to Statistical Thinking (With R, Without Calculus)
D G Rossiter - Publications & Computer Programs
Another aspect of speeding up loops in R
How to speed up loops in R
Making Data Work: Strata 2012 - O'Reilly Conferences, February 28 - March 01, 2012
Revolution Analytics - Commercial Software & Support for the R Statistics Language
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