cpsievert

library(shiny)
library(animation)
library(Cairo)
library(pitchRx)
library(shinyRGL)
library(rgl)


valid <- function(input, default) { 
  if (is.null(input)) return(FALSE)

cpsievert

#Taken from http://rstudio.github.com/shiny/tutorial/#hello-shiny
#All credits to Joe Cheng

library(shiny)

# Define server logic required to generate and plot a random distribution
shinyServer(function(input, output) {

  # Function that generates a plot of the distribution. The function
  # is wrapped in a call to reactivePlot to indicate that:

cpsievert

#template for fixing bad xml files from nba.com
library(XML)
con <- url("http://www.nba.com/games/game_component/dynamic/20130528/MIAIND/pbp_all.xml")
corrupt <- readLines(con)
close(con)
tmp <- gsub("<![CDATA[", "", corrupt, fixed=TRUE)  #do I really need "&lt;![CDATA"?
file <- gsub("]]>", "", tmp, fixed=TRUE)           #do I really need "]]&gt;"?
doc <- xmlParseString(xml(file))
node <- getNodeSet(doc, path="/")
l <- xmlToList(node[[1]])

cpsievert

setwd("~/Downloads")
obs <- XML2Obs("out.xml", url.map=TRUE)
unique(names(obs)) #you might want to re_name or add_key before collapsing
tables <- collapse(obs)
head(tables[["osm//node//tag"]])

cpsievert

library(shiny)
library(ggvis)
x <- seq(-4, 4, .1)
dat <- data.frame(x, y=dnorm(x))
g1 <- ggvis(dat, props(x = ~x, y = ~y), mark_path())

shinyServer(function(input, output, session) {

  # A subset of mtcars
  dat2 <- reactive({ dat[dat$x <= input$z,] })

cpsievert

#This example will require version 0.0.5 of XML2R
library(devtools)
install_github("XML2R", "cpsievert")
library(XML2R)
#you could use multiple files here if you wanted...
files <- "https://www.misoenergy.org/ria/Consolidated.aspx?format=xml"
obs <- XML2Obs(files)
names(obs)[grep("PricingNode", names(obs))] <- "PricingNode"
tables <- collapse_obs(obs)
head(tables[[5]])

cpsievert

library(XML2R)

file <- "http://stats.oecd.org/restsdmx/sdmx.ashx/GetData/UN_DEN/AUS+CAN+FRA+DEU+NZL+GBR+USA+OECD/OECD?startTime=1960&endTime=2012"

obs <- XML2Obs(file)
# Rename observations so we can 'recycle' country labels to time/value
nms <- names(obs)
nms[grepl("SeriesKey//Value$", nms)] <- "root"
nms[grepl("Obs//Time$", nms)] <- "root//time"
nms[grepl("Obs//ObsValue$", nms)] <- "root//value"

cpsievert

library(pitchRx)
library(dplyr)
library(mgcv)

# Establish a SQLite database connection
my_db <- src_sqlite("pitchRx.sqlite3")

# DISLCAIMER: this 'pitchfx.sqlite3' database was obtained using pitchRx version 1.2
# The code below probably won't work if you are using data collected from earlier versions or other methods
# Anyway, if you want to recreate this analysis, make sure you have pitchRx 1.2 or higher, then run:

cpsievert

---
output:
  knitrBootstrap::bootstrap_document:
    title: "Stat 226 Home Page"
    theme: amelia
    highlight: sunburst
    theme.chooser: TRUE
    highlight.chooser: TRUE
    bootstrap.panel: FALSE
---

cpsievert

library(XML)
library(RCurl)
library(stringr)
library(elife)

# Obtain all the dois! Well, at least every one on GitHub.
# Should/could this be an option in searchelife? It doesn't take that long...
con <- getURL("https://github.com/elifesciences/elife-articles")
doc <- htmlParse(con, asText = TRUE)
nodes <- getNodeSet(doc, path="//a[@class='js-directory-link']")