Anthony Damico ajdamico

## most recent 100 books posted to paperbackswap.R
library(XML)
url <- "http://www.paperbackswap.com/api/v1/index.php?RequestType=RecentlyPosted&Limit=100"
u <- xmlParse( url )
v <- getNodeSet( u , "/Response/Books/Book/ISBN-10" )
w <- sapply( v , xmlValue )

## let it be.R
title = "Let it be"

wow = "words of wisdom"

Verse.1 =
	c(	"When I find myself in times of trouble" ,
		"Mother Mary comes to me" ,
		paste( "Speaking" , wow ) ,
		title )


## listlabeling.R
#roger peng's listlabeling challenge from
#http://simplystatistics.tumblr.com/post/11988685443/computing-on-the-language

#create three example variables for a list
x <- 1
y <- 2
z <- "hello"

#create the function
makeList <- function(...) {

## analyzing big survey data with limited computing resources.R
########################################
###read large csv into SQL DB
########################################

#set to the number of GB of RAM on computer
gbram <- 0.5

#set to CSV file directory
setwd("C:\\American Community Survey\\2009\\")

## determine what pecent of fractions are non-repeating.R
# calculate the percent of fractions that are repeating vs. non-repeating

# install stringr if you don't already have it
#install.packages("stringr")

library( stringr )
options( digits=22 )

# this program looks at..
# 1/1, 1/2, 1/3, 1/4.. up to 1/x

## furman intro to r lecture.R
#three reasons to use R-

#it's free

#it's open source- package system

#it's a programming language for statistics.

x <- 1:5

## multicore win64.R
library(snowfall)

bigProcess <- function( x ) {
	mean( replicate ( 10^6 , max( rnorm( 100 , x ) ) ) )
	}

#run the function twice in parallel
start <- Sys.time()
sfInit(cpus=2,type='SOCK',parallel=TRUE)
sfSapply( c(1,5) , bigProcess )

## calculate your ten thousandth day on earth with R
#replace my birthday with yours
birthday <- strptime(c("8.18.1982"), format = "%m.%d.%Y", tz="EST")

#r counts everything in seconds, so this code multiplies by 60 seconds in a minute, 60 minutes in an hour, 24 hours in a day.
days <- function(u) {
x <- u * 60 * 60 * 24
return(x)
}

#change these numbers to whichever days you'd like to see, separated by commas

## import SAS ASCII file into R with SAS INPUT text file
##select file containing SAS input procedure
SASinput <- readLines(file.choose())

##find the first INPUT line
firstline<-min(grep("INPUT @1",toupper(SASinput)))

##find the first semicolon ending that input line
a<-grep(";",toupper(SASinput))
lastline<-min(a[a>firstline])

## wwow.R
# setwd( "C:/My Directory/wwow/" )

path.to.7z <- normalizePath( "C:/Program Files (x86)/7-zip/7z.exe" )

library(stringr)
library(downloader)
library(raster)
library(rasterVis)

source_url(
	library(XML)
	url <- "http://www.paperbackswap.com/api/v1/index.php?RequestType=RecentlyPosted&Limit=100"
	u <- xmlParse( url )
	v <- getNodeSet( u , "/Response/Books/Book/ISBN-10" )
	w <- sapply( v , xmlValue )
	title = "Let it be"

	wow = "words of wisdom"

	Verse.1 =
	c( "When I find myself in times of trouble" ,
	"Mother Mary comes to me" ,
	paste( "Speaking" , wow ) ,
	title )
	#roger peng's listlabeling challenge from
	#http://simplystatistics.tumblr.com/post/11988685443/computing-on-the-language

	#create three example variables for a list
	x <- 1
	y <- 2
	z <- "hello"

	#create the function
	makeList <- function(...) {
	########################################
	###read large csv into SQL DB
	########################################

	#set to the number of GB of RAM on computer
	gbram <- 0.5

	#set to CSV file directory
	setwd("C:\\American Community Survey\\2009\\")
	# calculate the percent of fractions that are repeating vs. non-repeating

	# install stringr if you don't already have it
	#install.packages("stringr")

	library( stringr )
	options( digits=22 )

	# this program looks at..
	# 1/1, 1/2, 1/3, 1/4.. up to 1/x
	#three reasons to use R-

	#it's free

	#it's open source- package system

	#it's a programming language for statistics.

	x <- 1:5
	library(snowfall)

	bigProcess <- function( x ) {
	mean( replicate ( 10^6 , max( rnorm( 100 , x ) ) ) )
	}

	#run the function twice in parallel
	start <- Sys.time()
	sfInit(cpus=2,type='SOCK',parallel=TRUE)
	sfSapply( c(1,5) , bigProcess )
	#replace my birthday with yours
	birthday <- strptime(c("8.18.1982"), format = "%m.%d.%Y", tz="EST")

	#r counts everything in seconds, so this code multiplies by 60 seconds in a minute, 60 minutes in an hour, 24 hours in a day.
	days <- function(u) {
	x <- u * 60 * 60 * 24
	return(x)
	}

	#change these numbers to whichever days you'd like to see, separated by commas
	##select file containing SAS input procedure
	SASinput <- readLines(file.choose())

	##find the first INPUT line
	firstline<-min(grep("INPUT @1",toupper(SASinput)))

	##find the first semicolon ending that input line
	a<-grep(";",toupper(SASinput))
	lastline<-min(a[a>firstline])
	# setwd( "C:/My Directory/wwow/" )

	path.to.7z <- normalizePath( "C:/Program Files (x86)/7-zip/7z.exe" )

	library(stringr)
	library(downloader)
	library(raster)
	library(rasterVis)

	source_url(