Pakillo

https://github.com/brentthorne/posterdown

https://github.com/rstudio/pagedown

https://github.com/GerkeLab/betterposter

https://github.com/pzhaonet/postr

https://github.com/odeleongt/postr

hrbrmstr

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

somada141

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/

yihui

Moved to https://github.com/yihui/shiny-apps/tree/master/voice

randyzwitch

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",

dmarcelinobr

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),

jbryer

require(ipeds)
require(ggplot2)
require(reshape2)
require(scales)
data(surveys)

View(surveys)

# Directory
ipedsHelp('HD', 2012)

inkhorn

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=".")

blmoore

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, ";")))

araastat

#’ 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