Rafik Margaryan raffdoc

We start with the imports:

import dicom
import os
import numpy

The pydicom package can be installed through pip and can be found in https://pypi.python.org/pypi/pydicom/

	library(ggplot2)
	library(dplyr)
	library(tidyr)
	library(stringr)
	library(scales)
	library(gridExtra)
	library(grid)

	# use the NPR story data file ---------------------------------------------
	# and be kind to NPR's bandwidth budget

	library("RSiteCatalyst")
	library("d3Network")

	#### Authentication
	SCAuth("key", "secret")

	#### Get Pathing data: Single page, then ::anything:: pattern
	pathpattern <- c("http://randyzwitch.com/big-data-hadoop-amazon-ec2-cloudera-part-1", "::anything::")
	next_page <- QueuePathing("zwitchdev",
	"2014-01-01",

	library(MCMCpack)
	## Coping with polls: the more recent, the better they are.
	##http://en.wikipedia.org/wiki/Opinion_polling_for_the_Scottish_independence_referendum,_2014

	polls = NULL
	polls <- data.frame( rbind(
	Survation = c(37, 50, 1010),
	YouGov = c(35, 55, 1142),
	TNSBMRB = c(32, 45, 1003),
	IpsosMORI = c(40, 54, 1006),

	library(plyr)
	library(ggplot2)
	library(ggmap)

	libraries = read.csv("ontario_library_stats_2010.csv")
	libraries$isFN = ifelse(libraries$Library.Service.Type == "First Nations Library",1,0)

	# Here we create the 'proportionate' versions of all the variables
	libraries[,143:265] = sapply(libraries[,20:142], function (x) x/libraries[,13])
	names(libraries)[143:265] = paste(names(libraries)[20:142], "P",sep=".")

	options(PlosApiKey = "<insert your API key here!>")
	#install_github("rplos", "ropensci")
	library("rplos")
	library("ggplot2")
	require("dplyr")

	# Convert author strings to counts
	countAuths <- function(cell)
	length(unlist(strsplit(cell, ";")))

	#’ Create a Kaplan-Meier plot using ggplot2
	#’
	#’ @param sfit a \code{\link[survival]{survfit}} object
	#’ @param returns logical: if \code{TRUE}, return an ggplot object
	#’ @param xlabs x-axis label
	#’ @param ylabs y-axis label
	#’ @param ystratalabs The strata labels. \code{Default = levels(summary(sfit)$strata)}
	#’ @param ystrataname The legend name. Default = “Strata”
	#’ @param timeby numeric: control the granularity along the time-axis
	#’ @param main plot title