DenisIzmaylov

OS X 10.11 (El Capitan) / Node.js and io.js Developer Environment

Custom recipe to get OS X 10.11 El Capitan running from scratch with useful applications and Node.js Developer environment. I use this gist to keep track of the important software and steps required to have a functioning system after fresh install.

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abresler

library(dplyr)
library(tidyr)
library(magrittr)
library(ggplot2)
"http://academic.udayton.edu/kissock/http/Weather/gsod95-current/NYNEWYOR.txt" %>%
	read.table() %>% data.frame %>% tbl_df -> data
names(data) <- c("month", "day", "year", "temp")

data %>%
	group_by(year, month) %>%

timelyportfolio

library(ggplot2)
library(pipeR)
library(rCharts)

#using ggplot2 stat_density help example

library(plyr) # to access round_any
movies$decade <- round_any(movies$year, 10)

zmjones

pkgs <- c("party", "parallel")
invisible(lapply(pkgs, require, character.only = TRUE))

partial_dependence <- function(fit, ivar, cores = 1, ...) {
    ## calculates the partial dependence of the response on explanatory variable(s)
    ## fit must be a party object
    ## ivar must be a character vector of length >= 1 all of which
    ## exist in the dataframe used to fit the model
    ## if the length of ivar > 1, joint dependence is calculated
    df <- data.frame(get("input", fit@data@env), get("response", fit@data@env))

christophergandrud

# Set up RStudio and JAGS on an Amazon EC2 instance
# Using Ubuntu 64-bit
# Partially from http://blog.yhathq.com/posts/r-in-the-cloud-part-1.html 
# See yhat for EC2 instance set up

# Navigate to key pair
# ssh -i YOUR_KEYPAIR.pem ubuntu@PUBLIC_DNS

# Add a user/password.
# This will become your RStudio username and password.

hadley

library(httr)
library(XML)
library(selectr)

xpath <- function(x) structure(x, class = "xpath")
sel <- function(x) xpath(css_to_xpath(x, prefix = "//"))

url <- "http://www.boxofficemojo.com/movies/?id=ateam.htm"
html <- content(GET(url), "parsed")

skranz

# Helper functions that allow string arguments for  dplyr's data modification functions like arrange, select etc. 
# Author: Sebastian Kranz

# Examples are below

#' Modified version of dplyr's filter that uses string arguments
#' @export
s_filter = function(.data, ...) {
  eval.string.dplyr(.data,"filter", ...)
}

hadley

# This script uses httr to download data from Google's API
# Notice ther is a limit of 2,500 calls per day

library(httr)
base_url <- "http://maps.google.com/maps/api/geocode/json"

geoCode <- function(address,verbose=FALSE) {
  r <- GET(base_url, query = list(address = address, sensor = "false"))
  stop_for_status(r)
  

dmarcelinobr

path = "~/Documents/My Data/BRAZIL/Elections/"
out.file<-""
file.names <- dir(path, pattern =".txt")
for(i in 1:length(file.names)){
  file <- read.table(file.names[i],header=TRUE, sep=";", stringsAsFactors=FALSE)
  out.file <- rbind(out.file, file)
}
 write.table(out.file, file = "cand_Brazil.txt",sep=";", 
             row.names = FALSE, qmethod = "double",fileEncoding="windows-1252")
             

benmarwick

# sources:
# http://www.jgoodwin.net/?p=1223
# http://orgtheory.wordpress.com/2012/05/16/the-fragile-network-of-econ-soc-readings/
# http://nealcaren.web.unc.edu/a-sociology-citation-network/
# http://kieranhealy.org/blog/archives/2014/11/15/top-ten-by-decade/
# http://www.jgoodwin.net/lit-cites.png


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# This first section scrapes content from the Web of Science webpage. It takes